(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

>>Hello and welcome to the Cube's coverage here at AWS Reinvent 2022. This is the Executive Summit with Accenture. I'm John Furry, your host of the Cube at two great guests coming on today, really talking about the future, the role of humans. Radically human is gonna be the topic. Paul Dardy, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, global managing director of thought Leadership and Technology research. Accenture. Gentlemen, thank you for coming on the cube for this conversation around your new hit book. Radically human. >>Thanks, John. It's great to, great to be with you and great, great to be present at reinvent. >>You know, we've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're kind of in this, I call it the systems thinking, revolutions going on now where things have consequences and, and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as, as humans. And so I love the book. Very, very strong content, really. Right on point. What was the motivation for the book? And congratulations. But, you know, I noticed you got the, the structure part one and part two, This book seems to be packing a big punch. What's, what was the motivation and, and what was some of the background in, in putting the book together? >>That's a great question, John, and I'll start, and then, you know, Jim, my co-author and, and part colleague and partner on this, on the book and join in too. You know, the, if you step back from the book itself, we'd written a first book called, you know, Human Plus Machine, which talked about the, you know, focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the Human plus machine pairing. And then, you know, when we started, you know, working on the next book, Covid was, you know, it was kinda the Covid era. Covid came online as, as we were writing the book. And, but that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing, you know, once Covid hit, every company became more dependent on technology. >>Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies ba, you know, and what was different from the first, you know, research we had done around our first book. And what we found, which was super interesting, is that, is that, you know, pre pandemic, the, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of two x. And that was before the pandemic. After the pandemic. We redid the research and the gap widen into five x. And I think that's, and, and that's kind of played a lot into our book. And we talk about that in the opening of our book. And the message message there is exactly what you said is technology is not just the lifeline, you know, from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around, you know, inflation energy, supply chain crisis because of the war in Ukraine, et cetera. >>And companies need the technology more than ever. And that's what we're writing about in, in Radically Human. And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud data and ai and the metaverse that signal out is three trends that are really driving transformative change for companies. And the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are gonna set companies apart as they look to, you know, to implement this technology and transform their companies for the future. >>Jim, weigh in on this. Flipping the script, flipping the assumptions. No, >>You, you, you used a really important word there, and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as kind of a point solution. They don't think of about AI in terms of taking a systems approach. So we were trying to address that, all right, if you're gonna build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the, the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate using your talent, focusing on trust, experiences and sustainability. >>You know, I like this, I like how it reads. It's almost like a masterclass book because you kind of set the table. It's like, cuz people right now are like in the mode of, you know, what's going on around me. I'm been living through three years of covid. But coming out the other side, the world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where I am, where am I today. So I think the first part really to me hits home, like, here's the current situation and then part two is, here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or you know, society. >>Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where, you know, radically human, you know, the title came from. And you know, the, what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot and, and that, you know, the whole hypothesis, you know, or premise of the book I should say, is that the more humanlike the technology is, the more radically human or the more radical the, you know, the, the the, the human potential improvement is the more, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I, you know, talk about, you know, talked about, you know, talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. >>Just a couple examples from the ideas framework, the eye and ideas is each of the, the ideas framework is the first part of the book, The five areas to flip your Assumptions, The eye stands for intelligence. And we're talking about more, more human and less artificial in terms of the intelligence techniques, things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build, using the kind of systems thinking that Jim mentioned. And you know, things like emotional ai, common sense ai, new techniques in addition to machine the big data driven machine learning techniques which are essential to vision and solving big problems like that. So that's, that's just an example of, you know, how you bring it together and enable that human potential. >>I love the, we've been, >>We've >>Go ahead Jim. >>I was gonna say we've been used to adapting to technology, you know, and you know, contorting our fingers to keyboards and and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus. In fact, the human is in the ascended. That's one of the, one of the big ideas that we try to put out there in this book. >>You know, I love the idea of flipping the script, flicking assumptions, but, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, s for strategy, notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution really kind of interesting kind of how you guys put that together. It kind of feels like business is becoming agile and iterative and it's how it's gonna be forming. Can you guys, I mean that's my opinion, but I think, you know, observing how developers becoming much more part of, of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is kind of how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation? If you take it down to a conclusion, strategy is just what you do after you get the outcomes you need. Is that, can you, what's your reaction to that? >>Yeah, yeah, I think, I think one of the most lasting elements of the book might be that chapter on strategy in, in my opinion, because you need to think about it differently. The old, old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to, you know, to lay out with the, the essence ideas, you know, the strategy and the, the, the fun. You know, the, the subtitle that chapter is is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, That's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential world that technology plays and therefore they need to, to master technology, well, you need to think about strategy differently than because of the pace of technology innovation. >>And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really report it's about continuous strategy in all cases. Yet an example is one of the techniques we talk about forever beta, which is, you know, think about a Tesla, you know, companies that, you know, it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along, you know, the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we, we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions, you know, might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days. As Paul was saying, >>It's interesting because that's the kind of the trend you're seeing with more data, more automation. But the human plays a much critical role. And, and just as a side on the Tesla example, you know, is well documented, I think I wrote about in a post just this week that during the model three Elon wanted full automation and had to actually go off script and get to humans back in charge cuz it wasn't working properly. Now they have a balance. But that brings up the, the part two, which I like, which is, you know, this human piece of it, you know, we always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that, that second half, you know, trust, talent experiences, that's the more the person's role, either individually as part of a collective group is talent. The scarce resource now where that's the, that's the goal, that's the, the key because I mean, it all could point to that in a way, you know, skills gap kind of points to, hey, you know, humans are valuable, in fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think, you know, that's something that is not kind of nuance point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >>Yeah, it's, go ahead Jim. I was gonna say it, you know, we're, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book. You know, really zooming in on talent. I think, you know, you might think that for every, you know, a hundred dollars that you put into a technology initiative, you know, you might put 50 or 75 into reskilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw a, a economic analysis recently that pointed out that for every $1 you spend on technology, you are likely gonna need to spend about $9 on intangible human capital. That means, you know, on talent, on, on getting the best talent on reskilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >>That's a huge point. >>I think some of the elements of talent that become really critical that we, we talked about in the book are, are becoming a talent creator. We believe that the successful companies of the future are gonna be able not, not just to post, you know, post a job opening and hire, hire people in because there's not gonna be enough. And a lot of the jobs that companies are creating don't exist, you know, cause the technology changing so fast. So companies that succeed are gonna know how to create talent, bring in people, apprentices and such and, and, and, you know, shape to tail as they go. We're doing a significant amount of that in our own company. They're gonna be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what you know, employees want. And then democratizing access to technology, You know, things like, you know, Amazon's honey code is an example, you know, low code, no code development to spread, you know, development to wider pools of people. Those types of things are really critical, you know, going forward to really unlock the talent potential. And really what you end up with is, yeah, the, the human talent's important, but it's magnified to multiplied by the power of people, you know, giving them in essence superpowers in using technology in new >>Ways. I think you nailed it, That's super important. That point about the force multiplier, when you put things in combination with it's group constructs, two pizza teams, flexing, leveraging the talent. I mean, this is kind of a new configuration. You guys are nailing it there. I love that piece. And I think, you know, groups and collectives, you're gonna start to see a lot more of that. But again, with talent comes trust when you start to have these kind of, you know, ephemeral and or forming groups that are forming production systems or, or, or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously Metaverse is a pretext to the virtual world where we're gonna start to create these group experiences and create new force multipliers. How does the Metaverse play into this new radically human world and and what does it mean for the future of business? >>Yeah, I think the Metaverse is radically, you know, kind of misunderstood to use the word title, word of a, when we're not with the title of our book, you know, and we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So, you know, that that's the potential of the metaverse. And it's about, it's not just about the consumer things, it's about metaverse in the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I, I believe you know that it is, has tremendous potential. We write about that in the book and it really takes radically human to another level. >>And one way to think about this is cloud is really becoming the operating system of business. You, you have to build your enterprise around the cloud as you go forward that's gonna shape the way you do business. AI becomes the insight and intelligence in how you work, you know, in infused with, you know, the human talent and such as we said. And the metaverse then reshapes the experience layers. You have cloud AI building on top of this metaverse providing a new way to, to generate experiences for, for employees, citizens, consumers, et cetera. And that's the way it unfolds. But trust becomes more important because the, just as AI raises new questions around trust, you know, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five part framework or or five, you know, essential, you know, parts of the framework around how you establish trust as you implement these new technologies. >>Yeah, we're seeing that, you know, about three quarters of companies are really trying to figure out trust, you know, certainly with issues like the metaverse more broadly across their it, so they're, you know, they're focusing on security and privacy transparency, especially when you're talking about AI systems. Explainability. One of the, you know, the more surprising things that we learned when doing the book, when we're doing the research is that we saw that increasingly consumers and employees want systems to be informed by kind of a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, the, they're, they're actually training the system by emulating human behavior. So kind of turning the cameras on test drivers to see how they learn and then training the AI kind of using that sense of humanity cuz you know, the other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that that AI system is learning from or some really interesting innovations kind of happening in that trust space. John, >>Jim, I think you bring up a great point that's worth talking more about because you know, you're talking about how human behaviors are being put into the, the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and you know, we've been calling it super cloud, some call it multicloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's gonna happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with Chad and some video, you know, it's, it's group behavior, it's group con groups, convening, talking, getting things done, you know, debating doing things differently. And so this idea of humans informing design decisions or software with low code no code, this completely changes strategy. I mean this is a big point of the book. >>Yeah, no, I go back to, you know, one of the, the, the, the e and the ideas frameworks is expertise. And we talk about, you know, from machine learning to machine teaching, which, which is exactly that, you know, it's, you know, machine learning is, you know, maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with ai? One of the examples we give is one of the, the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to code in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create, you know, amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >>Well you, what's interesting is that I wanna to get your thoughts as we can wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in, in the enterprise of their businesses, as they look at the horizon, they see the, the future, they gotta start thinking about things like generative AI and how they can bring some of these technologies to the table where, you know, we were, we were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are, these are new things you guys are hitting on this in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge, certainly that is an opportunity. How, how do you apply all this stuff for, for business >>Now? I'll go first then Jim Canad. But the, the first thing I think starts with, with recognizing the role that technology does play and investing accordingly in it. So the right, you know, technology, talent, you know, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why, you know, the fact you're at reinvent is so important because companies are, you know, again rebuilding that, that operating system of their business in the cloud. And you need that, you know, as the foundation to go forward, to do, you know, to, to build the other, other types of capabilities. And then I think it's developing those talent systems as well. You know, do you, do you have the right the, do you have the right talent brand? Are you attacking the right, attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward and then you marry the two together and that's what, you know, gives you the radically human formula. >>Yeah. When, you know, when we were developing that first part of the book, Paul and I did quite a bit of, of research, and this was ju and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. You know, one statistic is that 70% of, there was a, there was a of companies that had never tried AI before, went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies are not, or we're not trying to do it themselves and to, you know, to necessarily, you know, build an it, a AI department. They were partnering and it's really important to, to find a partner, often a cloud partner as a way to get started, start small scale and then scale up doing experiments. So that was one of the, that was one of the key insights that we had. You don't need to do it all yourself. >>If you see the transformation of just aws, we're here at reinvent just since we've been covering the events since 2013, every year there's been kind of a thematic thing. It was, you know, startups, enterprise now builders and now, now change your company this year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and, and running a SaaS application on the cloud. People are are changing and refactoring and replatforming, categorical applications in for this new era. And you know, we're calling it super cloud super services, super apps cuz they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools or talent pools in certain ways. So this is real, something's happening here and you know, we've been talking about a lot lately, so I have to ask you guys, how does a company know if they're radical enough? Like when, what is radical? How do, how can I put a pin in that say that could take a temperature or we like radical enough what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening. How do you know if you're, you're you're pushing the envelope radical enough to, to take advantage? >>Yeah, I think one, yeah, I was gonna say one of the, one of the tests is is you know, the impact on your business. You have to start by looking at all this in the context of your business and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. Yeah. That that's still something you need to do. But now we, our focus, you know, with a lot of our customers is on how do you innovate and grow your business in the cloud? What's, what is, you know, how, how, what's the platform you know, that you're using to, you know, for your, the new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test. Whether being radical, you know, radical enough is on the one hand, is this really, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping, you know, people, your human talent with the capabilities they need to perform in very different ways? And those are the the two tests that I would give. Totally agree. >>Yeah. You know, interesting enough, we, you know, we, we love this topic and guys, again, the book is spot on. Very packs a big punch on content, but very relevant in today. And I think, you know, one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like ideas your framework and understand where they are and what's available and what's coming around the corner. They stand out in the, in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean some, you're building clouds on top of clouds or, or something's happening. You can, I think you see it like look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >>Yeah, and that's a good example and it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows the portability of being able to connect and use data across cloud environments and such is, is, is is tremendously powerful. And I think that's why, you know, you talk about companies doing things differently, that's why it's great again that you're at reinvents. If you look at the index of our book, you'll see, you'll see AWS mentioned a number of times cuz we tell a lot of cus of cus customer and company stories about how they're leveraging aws, AWS capabilities in cloud and AI to really do transformative things in your, in their business. And I, I think that's what it's, that's what it's all about. >>Yeah, and one of the things too in the book, it's great cuz it has kind of a, the systems thinking it's got really relevant information but you know, you guys have seen the, seen the movie before. I think one of the wild cards in this era is global. You know, we're global economy, you've got regions, you've got data sovereignty, you're seeing, you know, all kinds of new things, emerging thoughts on the global impact cuz you, you take your book and you overlay that to business. Like you gotta, you gotta operate all over the world as a human issue. It's a geography issue. What's your guys take on the global impact? >>Well that's, that's why the, the, you gotta think about cloud as as one technology, you know, we talked about in the book and cloud is a lot, I think a lot of people think, well clouds it's almost old news. Maybe it's been around for a while. As you said, you've been going to reinvent since 2013. You know, cloud is really just getting, you know, just getting started. And, and it's cuz the reasons you said, when you look at what you need to do around sovereign cloud capability, if you're in Europe for many companies it's about multi-cloud capabilities. You need to deploy, you know, differently in different, in different regions. And they need to, in some cases for good reason, they have hybrid, hybrid cloud, you know, capability that they, they match on their own. And then there's the edge capability which is comes into play in, in different ways. >>And, and so the architecture becomes very complex and we talk the A in and ideas is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and mod and you know, just modularity was kind of the key thing you thought about. It's more the idea of a living system, of living architecture that's, that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the, with the pace of technology advancement. >>You know, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is gonna be a big discussion as these new flipped assumptions start to generate more activity. It's gonna be very interesting to watch. Gentlemen, thank you so much for spending the time here on the queue as we break down your new book, Radically Human and how it, how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at reinvent. Thanks so much for, for sharing and congratulations on a great book. >>You know, Thanks John. And just one point I'd add is that one of the, the things we do talk about in talent is the need to reskill talent. You know, people who need to, you know, be, be relevant to the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those who need to reskilling. And the final point I mentioned is that we mentioned at the end of the book that all proceeds for the book are being donated to not NGOs and nonprofits that are focused on reskilling. Those who need a skill refresh in light of the radically human new, you know, change in technology that's happening >>Great by the book proceeds go to a great cause and it's a very relevant book if you're in the middle of this big way that's coming. This is a great book. There's a guidepost and also give you some great ideas to, to reset re flip the scripts. Refactor, re-platform. Guys, thanks for coming on and sharing, really appreciate it. Again, congratulations. >>Thanks, John. John, great discussion. >>Okay, you're watching the Cube here, covering the executive forum here at AWS Reinvent 22. I'm John Furrier, your host with aen. Thanks for watching.

>> Announcer: From San Francisco, it's theCUBE, covering Accenture Tech Vision 2020. Brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Frick here from theCUBE. We are high atop San Francisco at the Accenture Innovation Hub, 33rd floor of the Salesforce Tower. It's a beautiful night, but we're here for a very special occasion. It's the Tech Vision 2020 reveal, and we are happy to have the guy that runs the whole thing, he's going to reveal on stage a little bit later, but we got him in advance. He's Paul Daugherty, the chief technology and innovation officer for Accenture. Paul, great to see you as always. >> Great to see you, Jeff, too. It is a beautiful evening here, looking out over the Bay. >> If only we could turn the cameras around, but, sorry, we can't do that. >> Yeah. >> All right, so you've been at this now, the Tech Vision's been going on for 20 years, we heard earlier today. >> Yeah. >> You've been involved for almost a decade. How has this thing evolved over that time? >> Yeah, you know, we've been doing the Vision for 20 years, and what we've been trying to do is forecast what's happening with business and technology in a way that's actionable for executives. There's lots of trend forecasts and lists and things, but if you just see a list of cloud, or-- >> Jeff: Mobile's going to be really big. (laughs) >> AI, mobile, it doesn't really help you. We're trying to talk a little bit about the impact on business, impact to the world, and the decisions that you need to make. What's changed over that period of time is just the breadth of the impact that technology's having on people, so we focus a lot of our Visions on the impact on humans, on individuals, what's happening with technology, what the impact on business, we can talk about that a little bit more, but business is certainly not the back office of companies anymore. It's not just the back office and front office, either. In business, it's instrumental in the fabric of how every part of the company operates, their strategy, their operations, their products and services, et cetera, and that's really the trajectory we've seen. As technology advances, we have this accelerating exponential increase in technology, the implications for executives and the stakes just get higher and higher. >> It's weird, there are so many layers to this. One of the things we've talked about a lot is trust, and you guys talk about trust a lot. But what strikes me as kind of this dichotomy is on one hand, do I trust the companies, right? Do I trust Mark Zuckerberg with my data, to pick on him, he gets picked on all the time. That might be a question, but do I trust that Facebook is going to work? Absolutely. And so, our reliance on the technology, our confidence in the technology, our just baseline assumption that this stuff is going to work, is crazy high, up to and including people taking naps in their Teslas, (laughs) which are not autonomous vehicles! >> Not an advisable practice. >> Not autonomous vehicles! So it's this weird kind of split where it's definitely part of our lives, but it seems like kind of the consciousness is coming up as kind of the second order. What does this really mean to me? What does this mean to my data? What are people actually doing with this stuff? And am I making a good value exchange? >> Well, that's the, we talk in the Vision this year about value versus values, and the question you're asking is getting right at that, the crux between value and values. You know, businesses have been using technology to drive value for a long time. That's how applying different types of technology to enterprise, whether it be back to the mainframe days or ERP packages, cloud computing, et cetera, artificial intelligence. So value is what they were talking about in the Vision. How do you drive value using the technology? And one thing we found is there's a big gap. Only 10% of organizations are really getting full value in the way they're applying technology, and those that are are getting twice the revenue growth as companies that aren't, so that's one big gap in value. And this values point is really getting to be important, which is, as technology can be deployed in ways that are more pervasive and impact our experience, they're tracking our health details-- >> Right, right. >> They know where we are, they know what we're doing, they're anticipating what we might do next. How does that impact the values? And how are the values of companies important in other ways? The values you have around sustainability and other things are increasingly important to new generations of consumers and consumers who are thinking in new ways. This value versus values is teeing up what we call a tech-clash, which isn't a tech-lash, just, again, seeing people reacting against tech companies, as you said earlier, it's a tech-clash, which is the values that consumer citizens and people want sometimes clashing with the value of the models that companies have been using to deliver their products and services. >> Right. Well, it seems like it's kind of the "What are you optimizing for?" game, and it seems like it was such an extreme optimization towards profitability and shareholder value, and less, necessarily, employees, less, necessarily, customers, and certainly less in terms of the social impact. So that definitely seems to be changing, but is it changing fast enough? Are people really grasping it? >> Well, I think the data's mixed on that. I think there's a lot of mixed data on "What do people really want?" So people say they want more privacy, they say they want access and control of their data, but they still use a lot of the services that it may be inconsistent with the values that they talk about, and the values that come out in surveys. So, but that's changing. So consumers are getting more educated about how they want their data to be used. But the other thing that's happening is that companies are realizing that it's really a battle for experience. Experience is what, creating broader experiences, better experiences for consumers is what the battleground is. A great experience, whether you're a travel company or a bank or a manufacturing company, or whatever you might be, creating the experience requires data, and to get the data from an individual or another company, it takes trust. So this virtuous circle of experience, data, and trust is something that companies are realizing is essential to their competitive advantage going forward. We say trust is the currency of the digital and post-digital world that we're moving into. >> Right, it's just how explicit is that trust, or how explicit does it need to be? And as you said, that's unclear. People can complain on one hand, but continue to use the services, so it seems to be a little bit kind of squishy. >> It's a sliding scale. It's really a value exchange, and you have to think about it. What's the value exchange and the value that an individual consumer places on their privacy versus free access to a service? That's what's being worked out right now. >> Right, so I'm going to get your take on another thing, which is exponential curves, and you've mentioned time and time again, the pace of change is only accelerating. Well, you've been saying that, probably, for (laughs) 20 years. (Paul laughs) So the curve's just getting steeper. How do you see that kind of playing out over time? Will we eventually catch up? Is it just presumed that this is kind of the new normal? Or how is this going to shake out? 'Cause people aren't great at exponential curves. It's just not really in our DNA. >> Yeah, but I think that's the world we're operating in now, and I think the exponential potential is going to continue. We don't see a slowdown in the exponential growth rates of technology. So artificial intelligence, we're at the early days. Cloud computing, only about 20% enterprise adoption, a lot more to go. New adoptions are on the horizon, things like central bank digital currencies that we've done some research and done some work on recently. Quantum computing and quantum cryptography for networking, et cetera. So the pace of innovation is going to accelerate, and the challenge for organizations is rationalizing that and deciding how to incorporate that into their business, change their business, and change the way that they're leveraging their workforce and change the way that they're interacting with customers. And that's why what we're trying to address in the Vision is provide a little bit of that road map into how you digest it down. Now, there's also technology foundations of this. We talk about something at Accenture called living systems. Living systems is a new way of looking at the architecture of how you build your technology, because you don't have static systems anymore. Your systems have to be living and biological, adapting to the new technology, adapting to the business, adapting to new data over time. So this concept of living systems is going to be really important to organizations' success going forward. >> But the interesting thing is, one of the topics is "AI and Me," and traditional AI was very kind of purpose-built. For instance, Google Photos, can you find the cat? Can I find the kids at the beach? But you're talking about models where the AI can evolve and not necessarily be quite so data-centric around a specific application, but much more evolutionary and adaptable, based on how things change. >> Yeah, I think that's the future of AI that we see. There's been a lot of success in applying AI today, and a lot of it's been based on supervised learning, deep learning techniques that require massive amounts of data. Solving problems like machine vision requires massive amounts of data to do it right. And that'll continue. There'll continue to be problem sets that need large data. But what we're also seeing is a lot of innovation and AI techniques around small data. And we actually did some research recently, and we talk about this a little bit in our Vision, around the future being maybe smaller data sets and more structured data and intelligence around structured data, common-sense AI, and things that allow us to make breakthroughs in different ways. And that's, we used to look at "AI and Me," which is the trend around the workforce and how the workforce changes. It's those kinds of adaptations that we think are going to be really important. >> So another one is robotics, "Robots in the Wild." And you made an interesting comment-- >> Paul: Not "Robots Gone Wild," "Robots in the Wild," "Robots in the Wild." >> Well, maybe they'll go wild once they're in the wild. You never know. Once they get autonomy. Not a lot of autonomy, that's probably why. But it's kind of interesting, 'cause you talk about robots being designed to help people do a better job, as opposed to carving out a specific function for the robot to do without a person, and it seems like that's a much easier route to go, to set up a discrete thing that we can carve out and program the robot to do. Probably early days of manufacturing and doing spot welding in cars, et cetera. >> Right. >> So is it a lot harder to have the robot operate with its human partner, if you will, but are the benefits worth it? How do you kind of see that shaking out, versus, "Ah, I can carve out one more function"? >> Yeah, I think it's going to be a mix. I think there'll be, we see a lot of application of the robots paired with people in different ways, cobots in manufacturing being a great example, and something that's really taking off in manufacturing environments, but also, you have robots of different forms that serve human needs. There's a lot of interesting things going on in healthcare right now. How can you support autistic children or adults better using human-like robots and agents that can interact in different ways? A lot of interesting things around Alzheimer's and dealing with cognitive impairment and such using robots and robotics. So I think the future isn't, there's a lot of robots in the wild in the form of C-3POs and R2-D2s and those types of robots, and we'll see some of those. And those are being used widely in business today, even, in different contexts, but I think the interesting advance will be looking at robots that complement and augment and serve human needs more effectively. >> Right, right, and do people do a good enough job of getting some of the case studies? Like, you just walked through kind of the better use cases, the more humane use cases, the kind of cool medical breakthroughs, versus just continued optimization of getting me my Starbucks coupon when I walk by out front? (Paul laughs) >> Yeah, I'm not sure. >> Doesn't seem like I get the pub, like they just don't get the pub, I don't think. >> Yeah, yeah, yeah, maybe not. A little mixology is another (Jeff laughs) inflection that robots are getting good at. But I think that's what we're trying to do, is through the effort we do with the Vision, as well as our Tech for Good work and other things, is look at how we amplify and highlight some of the great work that is happening in those areas. >> So, you've been doing it for a decade. What struck you this year as being a little bit different, a little bit unexpected, not necessarily something you may have anticipated? >> I think the thing that is maybe a tipping point that I see in this Vision that I didn't anticipate is this idea that every company's really becoming a technology company. We said eight years ago, "Every business "will be a digital business," and that was, while ridiculed by some at the time, that really came true, and every business and every industry really is becoming digital or has already become digital. But I think we might've gotten it slightly wrong. Digital was kind of a step, but every company is deploying technology in the way they serve their customers, in the way they build their products and services. Every product and service is becoming technology-enabled. The ecosystem of technology providers is critical to companies in every industry. So every company's really becoming a technology company. Maybe every company needs to be as good as a digital native company at developing products and services, operating them. So I think that this idea of every company becoming a technology company, every CEO becoming a technology CEO, technology leader, is something that I think will differentiate companies going forward as well. >> Well, really, good work, you, Michael, and the team. It's fun to come here ever year, because you guys do a little twist. Like you said, it's not "Cloud's going to be really big, "mobile's going to be really big," but a little bit more thoughtful, a little bit more deep, a little bit longer kind of thought cycles on these trends. >> Yeah, and I think the, if you read through the Vision, we're trying to present a complete story, too, so it's, as you know, "We, the post-digital people." But if you look at innovation, "The I in Experience" is about serving your customers differently. "The Dilemma of Smart Machines" and "Robots in the Wild" is about your new products and services and the post-digital environment powered by technology. "AI and Me" is about the new workforce, and "Innovation DNA" is about driving continuous innovation in your organization, your culture, as you develop your business into the future. So it really is providing a complete narrative on what we think the future looks like for executives. >> Right, good, still more utopian than dystopian, I like it. >> More utopia than dystopia, but you got to steer around the roadblocks. (Jeff chuckles) >> All right, Paul, well, thanks again, and good luck tonight with the big presentation. >> Thanks, Jeff. >> All right, he's Paul, I'm Jeff. You're watching theCUBE. We're at the Accenture innovation reveal 2020, when we're going to know everything with the benefit of hindsight. Thanks for watching, (laughs) we'll see you next time. (upbeat pop music)

>> From the Salesforce Tower in downtown San Francisco, it's theCUBE covering Accenture TechVision 2019. Brought to you by SiliconANGLE Media. (electronic music) >> Welcome back everybody, Jeff Frick here with theCUBE. We're in downtown San Francisco at the Salesforce Tower, the 33rd floor, brand new Accenture Innovation Hub, five stories here in the building, the ribbon cutting this morning, and we're really excited to have our next guest. He's been on many times, I think the first time in 2013. Fresh off the plane from Davos, Paul Daugherty, great to see you. >> It's great to be here Jeff and thanks for joining us at this event. It's a really big day for us here. >> Absolutely, now I didn't get your title in, I give you Chief Technology and Innovation Officer. You're really at kind of the forefront, so let's jump into the TechVision. This is something you guys do every year. You pick five kind of big trends that we should be taking a look at. There's a lot of detail. People can (laughs) take their time to read through it. But, I just want to touch on some of the highlights. What are some of the big changes from when we sat down a year ago? >> We have five trends this year. The number of trends varies a little bit, but the, you know, I think the one key takeaway and highlight from the Vision this year is this idea, the big idea, that we're entering the post-digital era, and I think many people will be surprised by that. They'll go what do ya mean post-digital? >> When you said that earlier today, I'm like post? We're just right in the meat of it aren't we? >> Right, but just to contextualize that a little bit, last year companies spent 1.1 trillion dollars on digital transformation. 94% of companies are doing some stage of digital transformation. 68% of them said they're pretty well set with their digital transformation. >> They said they're set? >> They're in good shape. Now you can question it. >> Does that surprise you? >> I question it, yes, it surprises me, and we're not sure that that's entirely-- >> Accurate? >> Representative, >> That's okay. >> But nonetheless, what is true is that every organization is adopting digital, and the question we're asking in the Vision is if everybody's doing digital, what's going to differentiate you? And, we believe that that's the characteristics of the post-digital environment where what you did leading up to now isn't going to be enough to differentiate you and lead to success in the future. In the post-digital era, it's about some new business concepts about how you shape your business and new technologies and some new corporate obligations that are going to be instrumental in your success as an organization. >> I want to dig into that a little bit 'cause I think it's a really interesting conversation. At the ribbon cutting this morning, we had representatives from the city and county of San Francisco, a representative from, I think, San Francisco State academic institution, and you said in some earlier remarks today that the responsibility for the company has moved beyond kind of stewardship for their customers, stewardship for their employees and their shareholders, but really they've got to be kind of active contributors to the community. And, that's been kind of called out over the last couple years especially in the tech industry that hey, you can't just do this stuff willy-nilly. You got to kind of take responsibility for what you can do. >> Yeah, well put, and that's one of the key things that we've been talking about in prior Visions, if you'll recall. This year, it's a big theme. The importance of this is, it's not just because it feels good. It's not just because you want to create good headlines. It's instrumental to your business success to be responsible, to create trust with your workers, employees, consumers and citizens and people in the communities you live in, and I'll explain why. What's happening is, we're creating increasingly intimate technology-enabled experiences for consumers. Think about implantable medical devices to prevent epileptic seizures. Think about the monitoring devices we use. Think about the information that's collected on us. People swipe on Tinder 1.1 million times per second, 3.7 million Google searches per second, 178 million emails per second, 266,000 hours of Netflix tracking every pause, play, fast forward, yeah per second, 266,000 hours. There's so much information collected on us out there. Our information is being used in so many different ways, and the technology is enabling companies to create individualized services for you that are great for consumers, but they're only going to be great if companies build the trust with their customers to get that data from them and if they honor the boundaries of responsibility to make sure they can sustain those products and services. >> But Paul, you scare me to death because every day we hear this breach, that breach, this breach, that breach. It's almost now-- >> Three billion identities in 2018 alone stolen. >> That's half the world, right, or almost. So, it's almost like okay, that's going to happen. And now that you're getting all this additional information, now you can tie the information from my phone that I'm takin' eight trips to 7-Eleven a day and spending way too much time on my couch not movin' around and how those things are going to tie together. One, for kind of the ethics of how the information is used when they have it, and two, it is probably going to get breached. An amazing concept you talked about earlier today, a digital twin. We hear about it from GE all the time for a jet engine, but to have a digital twin of me in some data base, that's, uh, you know, it's with everything, right? There's a good side and a scary side. >> There is, but I think this is where the idea of trust becomes very important. We need to think about, companies need to think about these services and their consumers in different ways. A lot of people, including myself, in the past have used phrases like data is the new oil. Data's the gold of artificial intelligence in this digital age we're living. I think that's dead wrong, and we got to change the mindset. Data isn't fuel or gold. Each piece of data is a fragment of a person and represents a part of a person's activity and identity, and I think if you change your thinking that way, and if you take a view that it's not all about optimizing the use of data, but it's about carefully using data in the right way that builds trust and provides value for the consumer, and you get that equitable exchange of value, that's what the future's all about. >> Right, so one of the topics, and again, we don't have time to go through all of 'em here, and you're going to give a presentation later, it's kind of just the whole machine and human interaction and how that's evolving. Specifically, I want to ask in terms of the work world. We hear about RPA, and everybody should have their own bots, and you can have bionic legs, so that you don't hurt your back if you're doing lifting. So, as you guys kind of look at how these things are melding, it's going to be an interesting combination of people with machines that are going to enable this kind of next gen of work. >> Yeah, no it'll be interesting. I think the important thing that we need to really think about is that like anything else, all these technologies are being designed by us, and we're deciding how to use them. We're deciding the principals around it, so this is about how do we design the world we want which gets back to the theme around responsibility and such. If you look at it, we find that workers are actually optimistic about the technology. Two thirds of workers are positive and optimistic about how all this technology's going to improve their job to even increase career prospects, but only half of those workers believe that their companies are going to provide them with the right training and learning. When we're talking about the human plus trend in here, the human plus worker trend is that it's not a nice to have for companies to provide learning platforms and train their employees. It's critical to their success because the jobs are changing so fast, roles are changing so fast, that if you as a company don't invest in a learning platform to continuously advance your people to fill the new jobs as they're being redefined every day, you as a company are going to get left behind, and that's what we're talking about in the human plus trend of the Vision. >> Right, another thing we hear all the time in terms of how technology's advancing on accelerating curves and people aren't so good at accelerating curves, but very specifically how no one person in one particular industry really has visibility as to what's happening in all these tangential. What's happening in health care? What's happening in drugs? What's happening in logistics? I'm in the media business, so I don't know. You guys are really sitting in an interesting catbird seat because you can see the transformation and the impacts of technology across this huge front, and it's that movement across that front which is really accelerating this thing way faster than people realize I think. >> Yeah it is, and it's a great position to be in to be able to look across like that. The thing I would say though is that unlike other eras of technology earlier, we're seeing remarkably broad industry adoption of these concepts. It's a little different in each industry as you just said, but every industry is looking at this. The interesting thing to me is one of the most common requests that I get from CEOs and from the C-Suite is they want to pull together a workshop, and they want to talk about their strategy and where they're going, and very often, more often than not now, they're saying, and I want to hear from people outside my industry. I want to hear what's happening over there. If I'm in insurance, I might want to hear what's happening in retail, or you know, they want to hear about different industries because they understand that the change is happening differently. They want to make sure they're not missing a pattern that they could apply in their own industry. >> Right, so last question before I let you go. You're speaking all the time. You're talkin' to customers. You go to cool shows like Davos and get to hang out with other big-brained people, but you get to participate in all these things, and now you have this facility. What does the Innovation Hub and these resources enable you to do with the clients that you couldn't do as we sit here in this beautiful new facility? >> Yeah, that's a great question. It's something we've worked on really hard over the last four or five years. It's creating what we call our Innovation Architecture, and it's, what we think, a unique way of putting together capability from research and thought leadership to our Accenture Ventures which is our venture capital investing arm to Accenture Labs which is our R and D and inventors to our studios where we co-create with clients to our industry professionals, the 2,000 people here in Northern California that are working with our clients everyday, and we can put all that together to turn the idea, the research, into results very quickly for our clients, and I don't think anybody can do it in the same way we can by co-like-heading all this and by the sheer investment we put into this. We invest over 800 million dollars a year in research and development, over a billion dollars a year in training for our people, and that results in things like 6,500, 6,500 patents that we generate, more than anybody else in our sector, and 1,400 of those come from our people right here in the San Francisco Innovation Hub, so it's an amazing place for innovation right here. >> All right, well Paul, thanks again for taking a few minutes. I know it's a busy day. You're gettin' ready to go present the findings for people. Where should they go to learn more about the TechVision? >> Go to accenture.com dot, uh, accenture.com/techvision. I think at midnight tonight Pacific Time it'll be out there, but by the time they see this, they'll probably have access to it, thanks. >> Paul, thanks for takin' a minute and good luck tonight. >> Always fun, thanks Jeff. >> He's Paul, I'm Jeff, you're watchin' theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco in the Salesforce Tower. Thanks for watchin'. (electronic music)

>> Hey, welcome back everybody. Jeff Frich here with theCUBE. We're at the Accenture Technology Vision 2018 event at the San Francisco mini gallery. Really loud, they got autonomous jazz players in the back, but we're excited to be here with Paul Daugherty. He's the chief technology and innovation officer for Accenture, and he's running this whole thing. Paul great to see you again. >> Great to be here and great to have you here at this event. It's a big event for us to talk about what we see happening with technology and where it's all going, and what it means for individuals and businesses, so it's going to be a fun night. >> So you did the survey last year we were here, really cool event. You did it again in 2018. What are some of the highlights? What are some of the things that jumped out to you a year later? >> I think the highlight and the real core of the vision team that we have this year is around what we the intelligent enterprise unleashed. Intelligent enterprise unleashed, and we're talking about is a fundamental different role that companies need to play as their thinking about the next evolution of the products and services they're offering to their customers. And one thing we talk about is the fact that technology isn't just a peripheral or something people use. Technology is core to the human experience. >> Jeff: Right. >> And how you and I work and how we live our lives and how every person does. And what that means is that companies have to think differently about the way they engage with customers, the way they build their technology. Because the trust you build with the consumers and workers and others using technology is fundamental to getting the right to deliver these profound, intrinsic services that people are demanding and that companies are providing. So it's really pivot point I think in terms of thinking about how companies provide technology. >> It's really interesting. It's bifurcation 'cause on one hand, you want software defined data automation as much as you can. On the other hand, people have an opportunity now through social media and all these channels to have a direct engagement with the company that they never had before. Combine that with the fact that most of your interaction, most of the time is through some type of technology interface whether it's a mobile app or a chat bot or whatever. So it's an interesting polarization of the way people engage with companies. >> Yeah, it really is and if you think about it. You look at it right now, and the average kid spends about eight and a half hours in front of a screen. They're immersed and engaged whether it's their phone or TV. They're immersed to the screen. You and I, you look at the average population. I would say that we touch our phones over 2600 times a day. >> Jeff: 2600? >> 2600. >> Oh that's scary. >> The phone has become part of our life. >> Right. >> The first thing people check when they wake up in the morning, probably. For most people, and that's only with the device that's been around for 10 years. Think about what's going to happen as we have ubiquitous voice communication, natural language understanding, extended reality interfaces to connect people in more rich interfaces. And that's this next generation of experience that we're moving toward. >> Yeah, it's interesting, you said extend the reality, which is one of your five topics for later this evening. >> Right. >> It's funny 'cause everyone's talking about augment reality, mixed reality, artificial reality. >> Right. >> And you've really rolled it up into one that it's a new way to blend data and intelligence. You talk about space with the reality that we're in right now. >> Yeah, exactly. We came up with the term extended reality because we believe it's about extending the experience of the individual and providing access to virtual reality, mixed reality, augmented reality, just your base interface, other types of technologies. And really the power of extended reality is it's the end of distance, is what we call it. The end of distance. So it's the end of distance to people. The end of distance to information. The end of distance to experiences. You can access what you want and the experience you want, when you want to use it. For example, Walmart for Black Friday last year used Oculus and mixed reality to give their store managers a simulation of what could happen on Black Fridays. So that they were better prepared to handle the high volume. The incidents that could happen. The unexpected circumstances. So it brought that experience right to them, and that's that end of experience. And end of access era that we're moving into. >> Right. The other conventional thing is this whole robot and autonomous vehicle thing. Boston dynamics. >> Like a robot Jazz player. >> I was going to say, you got a robot Jazz player and the band is working with the other players in the band. And it's this interesting thing. One one hand, people are afraid of robots. They're going to take my job. They're suppose to do the menial work. On the other hand, there aren't enough people to fill the open Rex, and really again, It's going to be the two working together, that's going to get us to one plus one makes three. >> Yeah, it's exactly our belief is that, we believe that the future is really about human plus machine working together. We talk about this formula. Human plus machine equals super powers. It provides people with super powers so they can do different jobs and do jobs more effectively. And sure point, we don't have a jobs issue right now. We have roughly as many open jobs and the U.S. as we have unemployed. The issue is matching the people with the right skills to fill those jobs. >> Jeff: Right. >> And one thing we haven't talked about enough is the power to use technology to amplify people's capabilities, so that they could fill more of those jobs. We talked about innovation in the new book we're working on is the real power to provide people with those capabilities. >> Right, so you travel a lot. If you need some great travel advice, just watch Paul's Twitter feed. And I want to talk to you. You're were at Davos in the world economic forum. >> Right. >> Right, and there's again, everything's bifurcated. There's doom and gloom about fake news and tech taking over and automated fake news, and what's going to happen in the job thing. On the other hand, there's a whole lot of great, positive opportunities. So I wondered if you can share some of your thoughts and your insights that you brought back from Davos, which is not a tech conference. It's a much bigger, higher level thinking about what's happening with this technological evolution. >> Yeah, the take a way from Davos is that there's tremendous power to use technology to address some of the fundamental issues that we have in society and in the world today. So a great example was what we just talked about with human plus machine. We believe that rather than the fear of machines taking over the world, and machines putting everybody out of work. We don't believe that's the future. There's tremendous opportunity and there's industries we don't yet know of that are being created right now, that are creating new jobs, in addition to real jobs are being created today that we can point to. And the discussion Davos says how do we use the art of the technology to both help the people who need access to new skills and technology, and prepare people for those new jobs. We also talked a lot in Davos about how to use technology to solve some of the big problems we have in the world toady. One of the really exciting discussions we have was on this idea of innovation with purpose. Not just innovation but innovating to solve a problem with purpose and a great example of that was an announcement that Accenture made with Microsoft, along with an organization called ID2020. To use blockchain technology powered by the cloud with artificial intelligence to provide identity and credentials to a billion people in the world that lack identity today. So it's refugees and others who don't have documented identity and can't access the services they need. And that's an example of a multi-stakeholder community coming together at Davos. Governments, tech companies and NGO's working together to solve a real problem using innovative technology. That's what we call innovation with purpose. >> Yeah, it's still so much opportunity. There's still so many fundamental problem. The fundamental job thing, I saw some treat the other day. Said go back 1860. How many jobs do you think they're qualified to do back then? So if the job changes right, the market changes. >> Yeah and the real issue we'd have to deal with 'cause I don't want to sound like Pollyanna in this. Is that there are real issues we need to deal with in terms of jobs that would be eliminated more quickly than in previous technology revolutions 'cause the pace of this is so fast. >> Right. >> But it really comes down to us getting a grip around how do we prepare people with the right skills. And that's one of the things we're very focused on in our tech vision, and in the other work we're doing at Accenture is the idea of how do you prepare the future work force. And we just put out a report on this recently as well. And one of the things we found is that over half of executives believe that a lot of their employees lack the skills that need for the AI that's coming. Over half of the executives. Only 3% of executives are increasing their investment in training, and that's a problem. If you believe the workforce isn't prepared. There's an obligation to begin investing to prepare the work force. It's something we take very seriously at Accenture. Investing a billion dollars a year in trading to continually rotate our people to the next thing that's ahead. We think that, that's the mindset around responsible investment in technology and in people >> Right. >> And the skills that gets us this human plus machine future. >> Takes a much bigger conversation around just the structure of our education system, which is so front loaded to the young age. And it just really doesn't match this continuous learning that people are going to have to do at a faster rate than ever before. >> Yeah, I think that's exactly right. We need to create lifelong learning platforms for people in our society, but also in the companies that we create. And it's something we're very focused on, and we do have to do a lot with K through 12 education. We do have to do a lot with higher ed. We need to do a lot more with apprenticeships in other alternative routes into the workforce as well. And you put all that together and tie it to new learning platforms for many career professionals. And that's I think what the future work force and education of the future workforce looks like. >> Right, alright Paul. Well you're the master of ceremonies. You got a big presentation to do and 200 something odd people here waiting for you. So I appreciate you taking a minute. But before I let you go, I got something new that's coming up. >> Oh yeah. >> That is coming out in a month or so. You got to get it out here. >> The very first copy. I don't know if they can see this. >> The very first copy. Hold it steady, they'll zoom in on it. >> This is the very first copy of the-- >> Is this your first? This is not your first book? >> It is my first book. >> It is your first book, congratulations. >> It's by Carl and Jill Wilson. Jim Wilson and I partnered together on this. This is Jim's second book, and it's Human + Machine: Re-imagining Work in the age of Artificial Intelligence. We're talking about precisely about the issues we just talked about. It's a leader's guide to how you deploy AI in a responsible fashion to read to your work force, and equip them with super powers, and really reconfigure your enterprise for what's coming with artificial intelligence. >> Paul, it's always great to catch up. Always love to see you here at the cutting edge. You go to so many cool events and this is one of them, so break a leg up there in an hour, and we'll see you after it's over. >> Not literally, but okay thank you. >> Yeah, yeah the theatrical way. >> Good to see you Jeff, bye. >> He's Paul Daugherty. I'm Jeff Frick. You're watching theCUBE. Thanks for watching. (uptempo techno music)

>> Narrator: From the Computer History Museum in Mountain View, California, it's The Cube, on the ground with Accenture Labs' 30th anniversary celebration. >> Hello, everyone, welcome to the special coverage of The Cube, on the ground here at the Computer History Museum in Mountain View, California, the heart of Silicon Valley. It's The Cube's coverage of Accenture Labs' 30th year celebration. I'm here with Paul Dougherty, the chief technology and innovation officer at Accenture Labs. Welcome to The Cube conversation. Thanks for joining me. >> It's great to be here. >> So first I want to toast you guys to 30 years from turning to an accounting firm, Arthur Anderson, to Accenture Labs Consulting. Guys are really changed. Congratulations to all your success. Thanks for having us. >> Yeah, thanks, it's been an incredible journey. If you think back in the 30 years, it's the 30th anniversary of Accenture Labs, and the transformation of our company to now be an innovation-led company, leading in IT services and IT innovation, and with the amazing innovations that are happening in technology, it's a great time to be doing what we're doing. >> So the theme here at the party is magic. There's a magic show going on. We can't get coverage. It's a little private event, probably some G-rated, probably ... >> Lots of magic. >> A lot of magic. But there's magic right now. We were commenting earlier, before you came on, about, you know at my age, I love this innovation cycle, but if I was 20 years old, I'd really be excited. There's so much going on. It's really magical. You've got the convergence of infrastructure, cloud, software. You guys have been on all sides of innovation, from the mini-computer boom, all the way now through now, where AI and software and now data science is coming together. What's the exciting thing for you right now? Because it's beyond software eating the world, it's beyond data eating software. This is real applications. >> Yeah, this is ... We're at an era where technology is the driving force behind every business. There was a survey recently of CEOs, and they asked CEOs how do they view their business, and 81% of CEOs, 81%, said their company's a technology company. And that was a cross-industry survey. And that's why it's an exciting time, because the option we have as Accenture is to work with any company, and every company, and help them transform, change their business, and lead them through the transformation to deliver technology-enabled digital products and services. And that's why it's an exciting time. >> What I find exciting about these global system integrators, as they're now called, is that you guys have always been a consultative organization to customers, helping them through their journey of that generational shift. Now it's interesting, with cloud computing, you guys are not only just advising, you're delivering services. A mindset transformation as well as talent, technology, process, and people. How are you doing it? What's the secret formula? >> Yeah, absolutely. I mean, what we found, the reason we've driven our business model in that direction, is our clients need help throughout the cycle. So we help with Accenture strategy, with advising our clients. We help with Accenture consulting, on helping our clients transform. Accenture digital, bring the digital capabilities in. Accenture technology, building the solutions in. Accenture operations, providing business process, infrastructure, and cloud operations. So, we've found that our clients, they need help with it all. They want to understand where to take their business, they want to understand how to get there, and they want somebody to help them manage their business as they do. And that's why we've taken the business in that direction. >> Not to give you guys a lot of props, but I do want to give you guys kudos, Accenture, Accenture Labs, is that all of folks might not know, or some, you guys probably do know, you've accumulated a lot of data scientists over the years. You've got thousands of data scientists, a lot of talent coming in. Accenture Labs is a booming operation, it's not just a throwaway lip-service kind of operation for customers, to say "Hey, we got some smart people." You guys have actually have a real organization. What are some of the cool things that you guys are doing? Can you give some examples? >> Yeah, let's just step back and talk about Labs a bit, and then I'll give some examples. We've been at Labs now for 30 years, hence the celebration we're talking about, and it's thousands of patents, it's billions of dollars of impact on the revenue of our business. And really, you're driving innovation that sets us ahead in the marketplace. And it's a fabric of a global organizations. We have labs here in Silicon Valley. We have labs in Washington, DC, that focus on security and other things. We have labs in Dublin, Ireland, in Tel Aviv, in Bangalore, India, in Beijing, in Sophia Antipolis in France. And it's that global infrastructure that allows us to tap into the innovation, I think in the key hot spots where it's happening. The kinds of innovation that we've driven are, think back to the early days of the cloud, we were doing R&D in patents and research in the cloud before the term "cloud" existed. And once the cloud phenomena took off, we had assets and architectures that we turned into the Accenture cloud platform, which has made us a leader in the multi-billion dollar ... Built a multi-billion dollar business in the cloud market. So that's an example of research and idea in early patents going to scale business for Accenture. That's the research to results that we talk about and what makes a difference in our business. >> So, talk about AI. AI's a hot trend, it's a great buzzword. I love AI because it gets young people excited about software. IOT is a little bit more boring than AI. But AI is augmented intelligence, also a little bit of artificial intelligence. Look no further than a test load, look no further than some of these cool things. How's AI impacting your world? >> AI's massive. I would say AI is the biggest single innovation and the most disruptive innovation of the information age to date. And probably, the biggest impact on how we work and live since the industrial revolution a couple hundred years ago. That started a couple hundred years ago. So AI is a big impact, and we're just at the start of it. That's kind of a paradox, though, because AI has been around for 60 years. The term was coined 60 years ago in 1956 at Dartmouth. And it just did it kind of slowly, but now we're at the inflection point where we have the computing hardware and the data and the processing power to make it really happen. So for the next five to 10 and 20 years, it's all about applying intelligence to augment the way we as people work and live and really create new opportunities to improve the productivity and creativity of humans. That's why we're excited. >> It's a perfect innovation storm. You've got great compute capability, almost unlimited capacity, software, new developer, open source is booming, and now you have STEM. >> Well, before you get to STEM, let me just make one comment on that. I think the other exciting thing about AI is we've been working with dumb technology up until this point. Think about the way we interact with our thumbs on a mobile phone. Think about the way you use traditional software in an enterprise on your PC or your screen. We're slaves to dumb technology, and the power and potential of AI is to make technology smarter, more human-like, and really enhance our ability as humans to use it. And that's why it's an exciting era. >> That's a great perspective from someone who has been in the process business. The classic example is, does the process work for you? Do you work for the process? >> Dougherty: Yeah. That's what technology ... >> And technology, we don't work for technology. They should work for us. >> And that's what's changing. That's the inflection point. >> So now, 30 years now, a lot's changed, certainly in Silicon Valley lately. Women and the role of women in the industry is certainly important. We're going to be at Grace Hopper for the fourth year this year as part of our women in tech celebration, in California this year covering women in tech. STEM is huge, but also, the gender gap is still there. You guys have a pledge to be 50% by 2025, Accenture as an organization. Labs, in particular, getting STEM in the technical roles is also a challenge. What are you guys doing to address that, and what's your personal philosophy? What's your comment about STEM and women in tech? >> Well, look, the technology industry in general has a gender diversity problem, and we believe at Accenture, we can really set the standard for how to really get to gender equality in the workforce. And that's the commitment we've got with our 50/50 gender diversity pledge by 2025. We're well along the path to getting there, right about 36% or so. Now, with the actions we're taking, the formula we've got, I'm confident that we'll get to the 50/50 pledge that we set out there. And it's an imperative for the technology industry, not just for Accenture, because we won't innovate to the potential of the industry, and we won't create the right opportunity if we don't have the right gender balance in the workforce. That's what will lead to the right innovations. In this new era where the humanity of how we apply technology, as you were saying earlier, flipping the lens on a people-centric view, we need all the perspectives and an equal representation of the population going into the way we develop solutions. That's why it's a priority for us. And we think we can really set a standard for how to apply to the technology industry. >> It's certainly a topic near and dear to my heart and our company's heart. I want to ask one more question on that as a follow-up. Computer science was always kind of narrow, I'm not saying super narrow, but now it's broadened, with analytics, the tech science side is opening up, for all the reasons you were just talking about, the AI stuff. It's a broad landscape now for many diverse roles. Can you share your thoughts on where the entry points could be for women, where it's not a man-led culture or new opportunities or new areas, new opportunities to engage, learn? Certainly digital will help that, in terms of acquiring knowledge. But in terms of getting into the business, what is the surface area of opportunities? >> The surface, it's the whole surface area. I think the wrong approach is to think that there are certain roles that are better for women or better for any group to do. There's equal opportunity in all the roles. One stat that's striking to me is the fact that, when I graduated from college in 1986, 35% of the graduates were women. 35% in 1986. Today that number is about 18%. We've gone backwards in the percentage of women graduates from computer science programs. That's a problem that we need to address. We need to get more women into technology careers. It's about sponsorship, it's about mentorship, it's about having the right role models, and it's about painting the right picture of the opportunity in technology. One of the organizations I'm involved with is Girls Who Code, where I'm on the board of directors because of our Accenture involvement because I believe that we need that kind of early involvement with girls to get them on the right paths and make them aware of the right opportunities that we can get them into the pipeline earlier. >> Congratulations. Thanks for doing that; it's great stuff. Personal question. 30 years, you've been in Accenture for a long time, 30 years of labs now, celebrating. What's the coolest thing you've done? >> You know, the coolest thing, the coolest thing is building the fabric of innovation of the company, so what we've done with the labs, creating Accenture Ventures, which is our tool for investing in companies, formalizing our Accenture research capabilities, that we now have an innovation fabric that goes from research to our ventures into our labs and the rest of Accenture's business. So we can take innovations like quantum computing and scale it and ramp it right into our business like we're doing today. So that's what's exciting to me, is to have created a funnel that we can use to take the early-stage innovations and pump them into real impact on our business. >> Awesome, and quick, what's happening here tonight? We're here at the 30th, labs here in Silicon Valley, Computer History Museum, historic event, magic. What's the show about today? >> Yeah, it's all about the past, the present, and the future. The past is how we got here with tremendous leaders of Accenture Labs, who built the organization to where it is today. The present is what I was just talking about, all the opportunity we have. And the future is more exciting that it's ever been. The next 30 years ... My only regret is that I'm not 20 years old right now. So the next 30 years are going to be even more exciting than the 30 years that I've lived through. And we're in a great place. Computer History Museum isn't just about the past. It's about the future. I'm on the board of trustees here at the Computer History Museum, and I love the mission of the museum in the way it brings the stories of innovation to light and sets us on the course for the future as well. >> Well, since you have so much influence, we're going to have to get our genes edited for sequencing so we can actually live longer because that's coming around the corner, too. >> I think that's the right idea. >> Cheers. Congratulations. >> Paul: Cheers. >> We'll be back with more coverage here live in The Cube. Accenture Labs' 30-year anniversary. I'm John Furrier with Paul Daugherty, chief technology and information officer, great work, innovation officer, great work. Congratulations. More coverage after this short break. Thanks for watching.

(upbeat music) >> Hello, everyone. Welcome to theCUBE's coverage here at AWS re:Invent 2022. This is the Executive Summit with Accenture. I'm John Furrier, your host of theCUBE with two great guests coming on today, really talking about the future, the role of humans. Radically human is going to be the topic. Paul Daugherty, the group Chief Executive Technology and CTO at Accenture. And Jim Wilson, Global Managing Director of Thought Leadership and Technology Research, Accenture. Gentlemen, thank you for coming on theCUBE for this conversation around your new hit book, "Radically Human." >> Thanks, John. It's great to be with you and great to be present at re:Invent. >> We've been following you guys for many, many years now, over a decade. You always have the finger on the pulse. I mean, and as these waves come in, it's really important to understand impact. And more than ever, we're in this, I call it the systems thinking, revolution is going on now where things have consequences and machines are now accelerating their role. Developers are becoming the front lines of running companies, seeing a massive shift. This new technology is transforming the business and shaping our future as as humans. And so I love the book, very, very strong content, really right on point. What was the motivation for the book? And congratulations, but I noticed you got the structure, part one and part two, this book seems to be packing a big punch. What was the motivation, and what was some of the background in putting the book together? >> That's a great question, John. And I'll start, and then, Jim, my co-author and colleague and partner on the book can join in too. If you step back from the book itself, we'd written a first book called "Human + Machine", which focused a lot on artificial intelligence and talked about the potential and future of artificial intelligence to create a more human future for us with the human plus machine pairing. And then when we started working on the next book, it was the COVID era. COVID came on line as we were writing the book. And that was causing really an interesting time in technology for a lot of companies. I mean, think back to what you were doing. Once COVID hit, every company became more dependent on technology. Technology was the lifeline. And so Jim and I got interested in what the impacts of that were on companies, and what was different from the first research we had done around our first book. And what we found, which was super interesting, is that pre-pandemic, the leading companies, the digital leaders that were applying cloud data, AI, and related technologies faster, we're outperforming others by a factor of 2x. And that was before the pandemic. After the pandemic, we redid the research and the gap widened into 5x. And I think that's played a lot into our book. And we talk about that in the opening of our book. And the message there is exactly what you said is technology is not just the lifeline from the pandemic, but now technology is the heart and soul of how companies are driving innovation, how they're responding to global crises around inflation, energy, supply chain crisis because of the war in Ukraine, et cetera. And companies need the technology more than ever. And that's what we're writing about in "Radically Human." And we're taking a step beyond our previous book to talk about what we believe is next. And it's really cloud, data and AI, and the metaverse that signal out as three trends that are really driving transformative change for companies. In the first part of the book, to your question on the structure, talks about the roadmap to that. We talked about the ideas framework, five areas where you need to change your thinking, flip your assumptions on how to apply technology. And then the second part of the book talks about the differentiators that we believe are going to set companies apart as they look to implement this technology and transform their companies for the future. >> Jim, weigh in on this flipping the script, flipping the assumptions. >> You used a really important word there and that is systems. I think when we think about artificial intelligence, and when Paul and I have now talking to companies, a lot of executives think of AI as a point solution. They don't think about AI in terms of taking a systems approach. So we were trying to address that. All right, if you're going to build a roadmap, a technology roadmap for applying intelligent technologies like artificial intelligence, how do you take a holistic systematic view? And that's really the focus of the first section of the book. And then as Paul mentioned, how do you take those systems and really differentiate it using your talent, focusing on trust, experiences and sustainability? >> I like how it reads. It's almost like a masterclass book because you set the table. It's like, 'cause people right now are like in the mode of what's going on around me? I've been living through three years of COVID. We're coming out the other side. The world looks radically different. Humans are much more important. Automation's great, but people are finding out that the human's key, but people are trying to figure out where am I today. So I think the first part really to me hits home. Like, here's the current situation and then part two is here's how you can get better. And it's not just about machines, machines, machines and automation, automation, automation. We're seeing examples where the role of the human, the person in society, whether it's individually or as part of a group, are really now key assets in that kind of this new workforce or this new production system or society. >> Yeah. And just to take a couple examples from the book and highlight that, I think you're exactly right. And that's where "Radically Human", the title came from. And what's happening with technology is that technology itself is becoming more human like in its capability. When you think about the power of the transformer technologies and other things that we're reading about a lot. And the whole hypothesis or premise of the book I should say, is that the more human like the technology is, the more radically human or the more radical the human potential improvement is, the bigger the opportunity. It's pairing the two together rather than, as you said, just looking at the automation or the machine side of it. That's really the radical leap. And one thing Jim and I talked about in context of the book is companies really often haven't been radical enough in applying technology to really get to dramatic gains that they can get. Just a couple examples from the ideas framework, the I in IDEAS. The ideas framework is the first part of the book. The five areas to flip your assumptions. The I stands for intelligence and we're talking about more human and less artificial in terms of the intelligence techniques. Things like common sense learning and other techniques that allow you to develop more powerful ways of engaging people, engaging humans in the systems that we build using the kind of systems thinking that Jim mentioned. And things like emotional AI, common sense AI, new techniques in addition to machine, the big data driven machine learning techniques, which are essential to vision and solving big problems like that. So that's just an example of how you bring it together and enable that human potential. >> I love the idea, go ahead Jim. >> I was going to say we've been used to adapting to technology, and contorting our fingers to keyboards and so on for a long time. And now we're starting to see that technology is in fact beginning to adapt to us and become more natural in many instances. One point that we make is now in the human technology nexus, in fact, the human is in the ascended. That's one of the big ideas that we try to put out there in this book. >> I love the idea of flipping the script, flipping the assumptions, but ideas framework is interesting. I for intelligence, D for data, E for expertise, A for architecture, S for strategy. Notice the strategies last. Normally in the old school days, it's like, hey, strategy first and execution. Really interesting how you guys put that together. It feels like business is becoming agile and iterative and how it's going to be forming. Can you guys, I mean that's my opinion, but I think observing how developers becoming much more part of the app. I mean, if you take digital transformation to its conclusion, the application is the company, It's not a department serving the business, it is the business, therefore developers are running the business, so to speak. This is really radical. I mean, this is how I'm seeing it. What's your reaction to that? Do you see similar parallels to this transformation if you take it down to a conclusion and strategy is just what you do after you get the outcomes you need? What's your reaction to that? >> Yeah, I think one of the most lasting elements of the book might be that chapter on strategy in my opinion, because you need to think about it differently. The old way of doing strategy is dead. You can't do it the way you used to do it. And that's what we tried to lay out with the S in IDEAS, the strategy. The subtitle that chapter is we're all technology companies now. And if you're a technology driven company, the way you need to think about and every company is becoming, that's what I hear when I talk to these suites and CEOs and boards, is everybody's recognizing the essential role that technology plays and therefore they need to master technology. Well, you need to think about strategy differently then because of the pace of technology innovation. And so you need to throw out the old way of doing it. We suggest three new archetypes of how to do strategy that I think are really important. It's about continuous strategy in all cases. An example is one of the techniques we talk about, forever beta, which is, think about a Tesla or companies that it's never quite done. They're always improving and the product is designed to be connected and improving. So it changes along the product and the strategy along how you deploy it to consumers changes as you go. And that's an example of a very different approach to strategy that we believe is essential to consider as you look at the future. Yeah, those multi-month strategy sessions might play out over two or three quarters of going away. And strategy and execution are becoming almost simultaneous these days as Paul was saying. >> It's interesting because that's the trend you're seeing with more data, more automation, but the human plays a much critical role. And just aside on the Tesla example, is well documented. I think I wrote about in a post just this week that during the model three, Elon wanted full automation and had to actually go off scripts and get to humans back in charge 'cause it wasn't working properly. Now they have a balance. But that brings up to part two, which I like, which is this human piece of it. We always talk about skills gaps, there's not enough people to do this, that and the other thing. And talent was a big part of that second half, trust, talent, experiences. That's more of the person's role, either individually as part of a collective group. Is talent the scarce resource now where that's the goal, that's the key 'cause it all could point to that in a way. Skills gap points to, hey, humans are valuable. In fact the value's going up if it's properly architected. What's your reaction to that, guys? Because I think that's something that is not, kind of nuanced point, but it's a feature, not a bug maybe, I don't know. What's your thoughts? >> Yeah, go ahead Jim. >> I was going to say it, we're dramatically underestimating the amount of focus we need to put on talent. That's why we start off that second part of the book, really zooming in on talent. I think you might think that for every hundred dollars that you put into a technology initiative, you might put 50 or 75 into re-skilling initiatives to really compliment that. But what we're seeing is companies need to be much more revolutionary in their focus on talent. We saw economic analysis recently that pointed out that for every $1 you spend on technology, you are likely going to need to spend about $9 on intangible human capital. That means on talent, on getting the best talent, on re-skilling and on changing processes and work tasks. So there's a lot of work that needs to be done. Really that's human focus. It's not just about adopting the technology. Certainly the technology's critical, but we're underestimating the amount of focus that needs to go into the talent factors. >> That's a huge point. >> And I think some of the elements of talent that become really critical that we talked about in the book are becoming a talent creator. We believe the successful companies of the future are going to be able not just to post a job opening and hire people in because there's not going to be enough. And a lot of the jobs that companies are creating don't exist 'cause the technology changing so fast. So the companies that succeed are going to know how to create talent, bring in people, apprentices and such, and shape to tale as they go. We're doing a significant amount of that in our own company. They're going to be learning based organizations where you'll differentiate, you'll get the best employees if you provide better learning environments because that's what employees want. And then democratizing access to technology. Things like Amazon's Honeycode is an example, low-code/no-code development to spread development to wider pools of people. Those types of things are really critical going forward to really unlock the talent potential. And really what you end up with is, yeah, the human talent's important, but it's magnified and multiplied by the power of people, giving them in essence superpowers in using technology in new ways. >> I think you nailed it, that's super important. That point about the force multiplier when you put things in combination, whether it's group constructs, two pizza teams flexing, leveraging the talent. I mean, this is a new configuration. You guys are nailing it there. I love that piece. And I think groups and collectives you're going to start to see a lot more of that. But again, with talent comes trust when you start to have these ephemeral and or forming groups that are forming production systems or experiences. So trust comes up a lot. You guys see the metaverse as an important part there. Obviously metaverse is a pretext to the virtual world where we're going to start to create these group experiences and create new force multipliers. How does the metaverse play into this new radically human world, and what does it mean for the future of business? >> Yeah, I think the metaverse is radically misunderstood to use the word title when we're not with the title of our book. And we believe that the metaverse does have real big potential, massive potential, and I think it'll transform the way we think about digital more so than we've changed our thinking on digital in the last 10 years. So that's the potential of the metaverse. And it's not just about the consumer things, it's about metaverse and the enterprise. It's about the new products you create using distributed ledger and other technologies. And it's about the industrial metaverse of how you bring digital twins and augmented workers online in different ways. And so I believe that it has tremendous potential. We write about that in the book and it really takes radically human to another level. And one way to think about this is cloud is really becoming the operating system of business. You have to build your enterprise around the cloud as you go forward. That's going to shape the way you do business. AI becomes the insight and intelligence in how you work, infused with the human talent and such as we said. And the metaverse then reshapes the experience layers. So you have cloud, AI building on top of this metaverse providing a new way to generate experiences for employees, citizens, consumers, et cetera. And that's the way it unfolds, but trust becomes more important because just as AI raises new questions around trust, every technology raises new questions around trust. The metaverse raises a whole new set of questions. And in the book we outline a five-part framework or five essential parts of the framework around how you establish trust as you implement these new technologies. >> Yeah, we're seeing that about three quarters of companies are really trying to figure out trust, certainly with issues like the metaverse more broadly across their IT so they're focusing on security and privacy, transparency, especially when you're talking about AI systems, explainability. One of the more surprising things that we learned when doing the book, when we were doing the research is that we saw that increasingly consumers and employees want systems to be informed by a sense of humanity. So one company that we've been looking at that's been developing autonomous vehicles, self-driving car systems, they're actually training the system by emulating human behavior. So turning the cameras on test drivers to see how they learn and then training the AI using that sense of humanity 'cause other drivers on the road find human behavior more trustworthy. And similarly, that system is also using explainable AI to actually show which human behaviors that AI system is learning from. Some really interesting innovations happening in that trust space. John. >> Jim, I think you bring up a great point that's worth talking more about. Because you're talking about how human behaviors are being put into the design of new things like machines or software. And we're living in this era of cloud scale, which is compressing this transformation timeline and we've been calling it supercloud, some call it multi-cloud, but it's really a new thing happening where you're seeing an acceleration of the transformation. We think it's going to happen much faster in the next five to 10 years. And so that means these new things are emerging, not just, hey, I'm running a virtual event with chat and some video. It's group behavior, it's groups convening, talking, getting things done, debating, doing things differently. And so this idea of humans informing design decisions or software with low-code/no-code, this completely changes strategy. I mean this is a big point of the book. >> Yeah, no, I go back to one of the, the E in the IDEAS framework is expertise. And we talk about from machine learning to machine teaching, which is exactly that. Machine learning is maybe humans tag data and stuff and feed into algorithms. Machine teaching is how do you really leverage the human expertise in the systems that you develop with AI. One of the examples we give is one of the large consumer platforms that uses human designers to give the system a sense of aesthetic design and product design. A very difficult thing, especially with changing fashion interest and everything else to encode in algorithms and to even have AI do, even if you have fast amounts of data, but with the right human insight and human expertise injected in, you can create amazing new capability that responds to consumers in a much more powerful way. And that's an example of what you just said, John, bringing the two together. >> Well, yeah, it's interesting. I want to to get your thoughts as we get wrap up here soon. How do you apply all these human-centric technologies to the future of business? As you guys talk to leaders in the enterprise of their businesses, as they look at the horizon, they see the the future. They got to start thinking about things like generative AI and how they can bring some of these technologies to the table. We were talking about if open source continues to grow the way it's going, there might not be any code to write, it just writes itself at some point. So you got supply chain issues with security. These are new things you guys are hitting in the book where these are new dynamics, new power dynamics in how things get built. So if you're a business owner and leader, this is a new opportunity, a challenge certainly that is an opportunity. How do you apply all this stuff for business? >> I'll go first then Jim can add in. But the first thing I think starts with recognizing the role that technology does play and investing accordingly in it. So the right technology talent, rethinking the way you do strategy as we talked about earlier and recognizing how you need to build a foundation. That's why the fact you're at re:Invent is so important because companies are, again, rebuilding that operating system of their business in the cloud. And you need that as the foundation to go forward, to do, to build the other types of capabilities. And then I think it's developing those talent systems as well. Do you have the right talent brand? Are you attracting the right employees? Are you developing them in the right way so that you have the right future talent going forward? And then you marry the two together and that's what gives you the radically human formula. >> Yeah. When we were developing that first part of the book, Paul and I did quite a bit of research, and Paul kind of alluded to that research earlier, but one of the things that we saw in really the first year of the pandemic was that there was a lot of first time adoption of intelligent technologies like artificial intelligence. One statistic is that 70% of companies that had never tried AI before went ahead and tried it during the pandemic. So first time adoption rates were way up, but the thing is companies were not trying to do it themselves and to necessarily build an AI department. They were partnering and it's really important to find a partner, often a cloud partner as a way to get started, start small scale, and then scale up doing experiments. So that was one of the key insights that we had. You don't need to do it all yourself. >> If you see the transformation of just AWS, we're here at re:Invent, since we've been covering the events since 2013, every year there's been a thematic thing. It was startups, enterprise, now builders, and now change your company. This year it's continuing that same thing where you're starting to see new things happen. It's not just lift and shift and running a SaaS application on the cloud. People are are changing and refactoring and replatforming categorical applications in for this new era. And we're calling it supercloud, superservices, superapps, 'cause they're different. They're doing different things in leveraging large scale CapEx, large scale talent pools, or talent pools in certain ways. So this is real, something's happening here and we've been talking about it a lot lately. So I have to ask you guys, how does a company know if they're radical enough? Like what is radical? How can I put a pin in that? It's like take a temperature or we like radical enough, what some tell signs can you guys share for companies that are really leaning into this new next inflection point because there are new things happening? How do you know if you're you're pushing the envelope radical enough to take advantage? >> Yeah, I think one. >> You can go ahead, Paul. >> Yeah, I was going to say one of the tests is the impact on your business. You have to start by looking at all this in the context of your business, and is it really taking you to another level? You said it perfectly, John, it used to be we used to talk about migration and workloads to the cloud and things like that. That's still something you need to do. But now our focus with a lot of our customers is on how do you innovate and grow your business in the cloud? What's the platform that you're using for your new digital products and services you're offering to your consumers. I mean it is the business and I think that's the test whether you're being radical enough is on the one hand, are you really using the technology to drive differentiation and real growth and change in your business? And are you equipping people, your human talent with the capabilities they need to perform in very different ways? And those are the two tests that I would give. >> Totally agree. >> Interesting enough, we love this topic and you guys, again, the book is spot on. Very packs of big punch on content, but very relevant in today. And I think one of the things we're looking at is that people who do things differently take advantage of some of these radical approaches like IDEAS, your framework, and understand where they are and what's available and what's coming around the corner. They stand out in the pack or create new business opportunities because the CapEx is taken care of. Now you got your cloud, I mean you're building clouds on top of clouds or something's happening. I think you see it, look at like companies like Snowflake, it's a data warehouse on the cloud. What does that mean? They didn't build a cloud, they used Amazon. So you're starting to see these new things pop up. >> Yeah and that's a good example. And it sounds like a simple thing, data warehouse in the cloud, but the new business capability that a technology like that allows and the portability of being able to connect and use data across cloud environments and such is tremendously powerful. And I think that's why, you talk about companies doing things differently, that's why it's great, again, that you're at re:Invent. If you look at the index of our book, you'll see AWS mentioned a number of times 'cause we tell a lot of customer company stories about how they're leveraging AWS capabilities in cloud and AI to really do transformative things in their business. And I think that's what it's all about. >> Yeah, and one of the things too in the book, it's great 'cause it has the systems thinking, it's got really relevant information, but you guys have seen the movie before. I think one of the wild cards in this era is global. We're global economy, you've got regions, you've got data sovereignty, you're seeing all kinds of new things emerging. Thoughts on the global impact 'cause you take your book and you overlay that to business, like you got to operate all over the world as a human issue, as a geography issue. What's your guys take on the global impact? >> Well that's why you got to think about cloud as one technology. We talked about in the book and cloud is, I think a lot of people think, well, clouds, it's almost old news. Maybe it's been around for a while. As you said, you've been going to re:Invent since 2013. Cloud is really just getting started. And it's 'cause the reasons you said, when you look at what you need to do around sovereign cloud capability if you're in Europe. For many companies it's about multi-cloud capabilities that you need to deploy differently in different regions. And they need to, in some cases for good reason, they have hybrid cloud capability that they match on their own. And then there's the edge capability which comes into play in different ways. And so the architecture becomes very complex and we talk the A in IDEAS is architecture. We talk about all this and how you need to move from the old conception of architecture, which was more static and just modularity was the key thing you thought about. It's more the idea of a living system, of living architecture that's expanding and is what's much more dynamic. And I think that's the way you need to think about it as you manage in a global environment today with the pace of technology advancement. >> Yeah, the innovation is here. It's not stopping. How do you create some defacto standards while not stunting the innovation is going to be a big discussion as these new flipped assumptions start to generate more activity. It's going to be very interesting to watch. Gentlemen, thank you so much for spending the time here on theCUBE as we break down your new book, "Radically Human" and how business leads can flip the script on their business assumptions and put ideas and access to work. This is a big part of the cloud show at re:Invent. Thanks so much for sharing and congratulations on a great book. >> Thanks, John. And just one point I'd add is that one of the things we do talk about in talent is the need to reskill talent. People who need to be relevant in the rapidly changing future. And that's one area where I think we all as institutions, as communities and individuals need to do more is to help those that need to reskilling. And the final point I mentioned is that we've mentioned at the end of the book that all proceeds from the book are being donated to NGOs and nonprofits that are focused on reskilling those who need a skill refresh in light of the radically human change in technology that's happening. >> Great. Buy the book. Proceeds go to a great cause and it's a very relevant book. If you're in the middle of this big wave that's coming. this is a great book. There's a guidepost and also give you some great ideas to reset, reflip the scripts, refactor, replatform. Guys, thanks for coming on and sharing. I really appreciate it. Again, congratulations. >> Thanks, John. >> Thanks, John. Great discussion. >> You're watching theCUBE here covering the executive forum here at AWS re:Invent '22. I'm John Furrier, you're host with Accenture. Thanks for watching. (gentle music)

(upbeat music) >> Hey everyone. Welcome back to theCUBE's coverage of Coupa Inspire 2022. We are in Las Vegas at the beautiful Cosmopolitan hotel. I'm your host, Lisa Martin. Brian McKillips joins me next, a managing director at Accenture. Brian, it's great to have you on the program. >> Thanks for having me, I'm glad to be here. >> So you have an interesting, you lead a lot of stuff at Accenture and I want to read this off, so I get it right. You lead the intelligent platform services strategy and the industry and functions platform group. Talk to me about those responsibilities. >> Yeah, so the intelligent platform services is the place in the business where we have kind of our large software partners, SAP, Oracle, Microsoft, Workday, Salesforce and Adobe. And we kind of think of ourselves as kind of the engine that powers industry and functional solutions, right? And the way Accenture's gone to market over the last couple of years has been kind of bringing together our breadth of experience all the way from strategy, all the way through operations and these big technology transformations are at the core of that. So that's what we do in intelligent platform services. And we recently launched this what we call the industry and functions platforms group because we realized there's a lot of strategic partners that are critical for us to be have a strong practice around, COUPA being one of them, you know in the supply chain and sourcing and procurement space so that we could create a home to be able to deliver these solutions globally and at scale. So I lead both kind of the strategy across all of IPS and then the new industry and functions platform group. >> Got it. All right. So you're here to talk to me about composable technology. First of all, define that for the audience so they understand what you're talking about. >> Yeah, you bet. So, you know, at Accenture, we're talking a lot about this is the age of compressed transformation, meaning, you know, change is only going to speed up and the need to change and so our clients are really struggling with not only kind of moving fast but that pressure around having to change as dynamics around the world change. So in the age of compressed transformation, we were really talking about how our clients should be kind of reorienting the way they think about their tech stack. And because, you know, historically a lot of us grew up in kind of monolithic implementations with, you know one software provider. But today it's really about composing technology to create new industry, new ways to solve industry problems, functional processes, customer experiences, right? And so composable technology we think about it in three parts. One is a cloud foundation that is, you know, the hyperscalers are a critical part of that. Secondly, our digital core and these are the kind of the historic software packages at the center of a lot of the industry and functional business processes. So you think about SAP and Oracle and Salesforce and things like that. But then around that digital core you have composable elements to be able to plug in. And that could be things like other software packages but it's also kind of industry IP or you know, edge devices, you know think IOT, think smart appliances, think and when you put, pull all those things together you need to be able to not only configure it once but configure and reconfigure as the dynamics of the marketplace change. >> So composable technology isn't necessarily new but has the pandemic been an accelerator of some of the things that you're seeing now in terms of why it's important, what's different about it now as being a foundation for competitive differentiation? >> Yeah, for sure. And it's, you know, I, anybody who's in technology say, you know, you tell them about this idea, they're like, well this isn't new, we've had service oriented architectures for 20 years. >> Right. >> You know, we've been talking about integrating things forever, but the you know, much like we all five to seven years ago we knew that we'd be using our phones to pay for pretty much everything but the tech hadn't caught up, right. Not every restaurant or store that you went to had the point of sale set up, right. So we all kind of knew that was coming. And the same thing has kind of happened around this idea of about composable technology and the three things that are new are one is that the cloud foundation is here, right. >> Yes. >> Where, you know, you now have not only kind of hyperscale high speed compute in at the core you actually have at the edge as well. And the same thing with high speed network, you know you have Starlink, you have 5G rolling out. So you have that cloud foundation that really wasn't there before. The second thing that's happening is the posture of a lot of the ecosystem, major ecosystem players has changed, right. And this started, you know when Satya Nadella took over Microsoft where Microsoft was very much a kind of a closed environment. >> Right. >> Where Satya under his leadership has really kind of changed the posture of being able to integrate into that. And we've seen that really pretty much across the entire landscape. And then lastly, it's become, you know, cheaper and, you know, quicker to be able to integrate with platforms like MuleSoft and others where there's kind of full scale integration platforms. So those are, those are the kind of the things that are new that allows for composable technology to be here in the real world. >> So it's something that's tangible, it's real organizations need to be on this bandwagon I imagine or they're going to be left behind. Gartner had some interesting stats that your team sent over and they were talking about these stats that were very compelling in terms of a seismic shift which always, you hear seismic living in California I think earthquakes, but something substantial. And they said, this seismic shift is going to happen by 2023. And I thought, hang on, that's less than a year away. >> Yeah. >> And they talked about by 2023, organizations that have adopted an intelligent composable approach will outpace competition 80% in the speed of new feature implementation. So if an organization hasn't started on that now is it too late? >> I would say not necessarily too late but they need to look for ways to change their disposition, right. And one of the ways that we've been helping clients do this is through pre-integrated solutions, right. So you know, in the past, the motion would be we would work with a client, they would work with our kind of strategists and consultants and say, what does the the future of supply chain look like for example. And if the client liked it, they would say, okay, I love it, what do I do next? Right. Then there would be another consulting engagement, another consulting engagement and then there would be a blueprint and architecture and at some point there was an implementation and a run. We've actually said we're investing heavily with our ecosystem partners to be able to pre-integrate solutions. So when that supply chain strategist says this is what the post COVID supply chain should look like and the client says, I love it what do I do next, that strategist can turn around and say, well, we've got a pre-integrated solution with SAP at the core sitting on a Microsoft Azure stack integrated with Coupa, wrapped with AI and machine learning and we can drop that and configure it for an environment. So that's how we're working with clients who are in that position that really need to kind of change their disposition is to bring these pre-integrated solutions and drop them in. >> Where are your conversations at the C- Suite level? Because this is, I hear many things in what you just said. Part of it is change management, which is very challenging. There's, people are very resistant to that. >> Brian: Yeah. >> One of the things that we've learned in the last two years is if it's going to come it's going to come but where are your conversations within that executive suite in terms of getting buy-in and going this is the direction we have to go in. >> Brian: Yeah. >> Because our business needs to be not just survive but thrive. >> Yeah. Yeah. These are, I mean, there are certainly of course in kind of traditional channels of tech whether it's, you know, the CIO or the CTO, but increasingly we're seeing this is a CEO discussion and, you know, our CEO Julie Sweet, is very, very market pacing and is having top to top conversations talking about compressed transformation, talking about composable technology because it's no longer just a, you know, a back office function as you know, right. I mean, this is really core to how companies you know, are, change their business models, make money, right. And it's a constant evolution. And that's why we talk about that kind of configuring and reconfiguring, it's not just coming in, implementing once, run it for five years and then when it's time to upgrade, we come back. >> No. >> We really want to be the partner with our clients to basically move in and, you know, across the patch whether it's specific industry processes, specific functional processes, specific customer experiences, we want to be the partner that is constantly tuning and configuring and reconfiguring and composing these solutions from across the ecosystem. >> And helping those businesses in any industry evolve as you talked about this compressed timeline, compressed transformation, such an interesting way of describing it but it's really true, it's what we've been living the last couple of years. >> Brian: Yeah. And so I want to get into Accenture's technology vision. You touched on this a little bit but there was some stats that your team provided that I thought were really, really interesting, a survey that Accenture did, 77% of executives, and we were just talking about the C-suite, state that their tech architecture is becoming critical to the overall success of the organization. So that awareness is there for sure en masse. Another thing that, stat that was interesting was 90% of business and IT execs agree that to be agile we always talk about agility, right, be resilient, organizations need to fast forward this digital transformation at the core. There's that compressed transformation. >> Brian: Yeah. >> Those are very high numbers. >> Brian: Yeah. >> In terms of where organizations say we see where we need to be. What's the vision at Accenture to help organizations get there fast? >> Yeah. Well, I think it's, you know, the thing that came to mind as you were talking is that we have, you know, major clients that have had this had in the, you know consumer packaged goods and apparel space that have had one way that they've done business is directly through retailers, you know, for pretty much their whole existence. Suddenly they need to shift to a direct to consumer model both in terms of marketing, in terms of commerce and that's not, you know, you don't just flip a switch in the back office and, you know, call IT and say hey, hey, can you change around a few things? It's actually shifting the entire core, it touches everything, it touches point of sale, it touches the customer experience, it touches supply chain, it touches employee experience even, right. >> Yeah. >> And so that's why I think it's so important for, you know technology leaders and business leaders to continue to kind of integrate themselves more tightly. >> Yes. >> To be able to make these business model transformations not just, you know, the tech that supports things. >> It's essential. >> Yeah. >> You know, we often in so many shows, Brian, we talk about alignment of business and technology, but it's not trivial. >> Yeah, yeah. >> It's absolutely fundamental to the success of every organization. And they've got to do so and as you said, I'm going to use your, your word, the compressed transformation. >> Yeah. >> A compressed timeframe. So talk to me about some customer examples where you really feel that Accenture and Coupa have helped this organization transform its supply chain to be able to be, use composable technology. >> Brian: Yeah. >> To be a leader in its industry. >> Yeah. Well, one example of that is a major industrial client that we have that has global operations across the world. And they're on a journey to kind of upgrade their digital core ERP that they've been on for a long time. And that's a multi-year journey. But at, you know, today they have needs for sourcing and procurement solutions in specific geographies around the world like Japan, for example. So what we've been able to do and it's a relatively simple example but quickly work with the client and Coupa to identify the right Coupa solution that's born in the cloud that has a great kind of user experience and implement that quickly as well as integrated it into the digital core, right. So they're not separate things. And it becomes part of that architecture, right. It just starts to kind of show the flexibility of when you have, when you come with a kind of composable technology point of view, the way we can help our clients do that. And in some other cases it's even more, you know, more cutting edge. So think about a utilities client, for example that has IOT sensors on their wires and when the, when that wire swings too far they say something's wrong. Automatically it goes back to the digital core cuts a ticket and finds the closest worker. >> Lisa: Okay. >> To then dispatch. The worker then can put on their hollow lens, for example and climb the pole and get directions on how to solve the problem right then and there, right? That's another example of you know, multiple systems, edge devices things coming together in order to create that. And it's only going to get faster, you know, with the metaverse. >> Lisa: Right. >> You know, with web 3.0 coming, with blockchain becoming more and more mainstream, companies need to be thinking about in this age of compressed transformation how to do that composable technology that you can figure and reconfigure. >> Do you think that we're in an age of compressed transformation or is that how it's going to be going forward given the global climate the last two years? >> Yeah. It's definitely going to be that way going forward over the next, you know, probably for the large part of the, the remainder of our career. I mean, we're, our CTO, Paul Daugherty, talks about us being an mega cycle, right? There's so many things changing. And even without these externalities of, you know, political issues and pandemics, you know, the introduction of AI and machine learning, a lot of these technologies I just mentioned, it's, the change is happening in every industry, in every, you know kind of area of the marketplace and in a way that's, you know, that's really exciting, right. And we get to help our clients be able to kind of solve those things not just once, but continually >> There's a tremendous amount of opportunity that's come from compressed transformation, right. A lot of opportunity, a lot of potential. What are some of the things that you're looking forward to say in the next year, as we talked about some of those business and lines of business and IT folks understand we've got to move in this direction. What excites you about the potential that you have to help these organizations really transform? >> Yeah, well, I think, I mean, the, we just came out with our new tech vision which is about the metaverse. And I think that the things that excite me are there's brand new ways like we've lived in a world where transactions take place in a very predictable way with local currencies through a single channel. And that was, that's been sort of fixed for a long time. The fundamentals of the economy or actually in the marketplace are starting to change in terms of how do we transact with things like cryptocurrencies, things like non fungible tokens, you know, all these things that we didn't, you know, they weren't, even the metaverse these were not main line words, even six you know, months ago, 12 months ago. >> Lisa: Right, right. >> Now these things, you know, every it seems like every month there's something new that is, you know, seismic to use your word that is shifting the fundamentals of the marketplace. And I think that's what's really exciting. I mean, that's where, I mean, it's probably one of the most exciting times to be in business, be in the marketplace. It certainly has a lot of challenges. >> Lisa: Yes. >> But, you know, I think we're really about using, you know, the promise of technology to unlock human ingenuity and this is a great time to be able to unlock that human ingenuity. >> And that's such a great alignment with Coupa. I was just in the keynote and there was an Accenture video, Julie Sweet was talking to some other folks about that. Great alignment in the partnership. Brian, thank you for joining me talking about composable technology, what's new, why and the potential that organizations and every business have to use it to unlock competitive advantages. >> Brian: Yeah. >> We appreciate your insights and your time. >> You bet. Pleasure to be here. >> All right. With Brian McKillips, I'm Lisa Martin. You're watching theCUBEe from Coupa Inspire 2022. (upbeat music)

>> Narrator: Live from San Francisco, it's theCUBE, covering RSA Conference 2020 San Francisco. Brought to you by SiliconANGLE Media. >> Welcome back everyone. This is theCUBE's coverage from RSA Conference on Moscone South. I'm John Furrier, host of theCUBE. You know, cybersecurity is changing, and the next technology is right around the corner, and it's got to be invented somewhere, and of course Accenture Labs is part of it. Our next guest is Lisa O'Connor, Global Security R&D Lead for Accenture Labs. Lisa's working on some of those hard problems all around the world. Thank you for joining me today. Thanks for coming on. >> Thank you for having me. >> So, we always get the good scoop from Accenture, because you have a lot of smart people in that company. You know, they know their stuff. I know you got a huge analytics team. I've talked to Jean-Luc Chatelain before, and I know you got a massive amount of, deep bench of talent. But as you have to go do the applied R&D, and maybe some of the crazy ideas, you got to start thinking about where the puck is going to be. >> Absolutely. >> You got to understand that. Well, it's pretty clear to us that Cloud is certainly there. Palo Alto Networks had a disappointing earnings yesterday, because their on-premises business is shifting to the Cloud. You're seeing hybrid operating model and multicloud for the enterprise, but now you got global challenges. >> We absolutely do. >> Huge, so what are you guys working on that's coming? Tell us. >> So we're working on lots of exciting things, and Cloud is one of them. But, some of the things I'm so passionate about in labs, and I have the best job at Accenture. Don't tell anyone. (laughs) I do. So, we are working on, like Jean-Luc is working on applied intelligence, we are working on robust AI. So, when we think about AI in the future, how do we feel that, and know that it's okay? How do we put it out there and know it's safe in production, we've done the right training, we've made our model resilient to what's out there? One of the things we see happening, and I love AI, love it. It has great potential, and we get great insights out of it, but a lot of times we stop, we get the insights, and we say, "Okay, it's in the box, we got a couple hits there, "we're good, it's good." No, maybe not. And so really, it's learning and creating the actually applied attacks on AI, and then figuring out what the right defenses are. And, depending on what type of machine learning you're using, those defenses change. And so, we're having a great time in our lab in Washington D.C., working on basically defending AI and building those techniques, so that what we put out as Accenture is robust. >> You know, it's interesting, AI, you watch some of the hardcore, you know, social justice warriors out there going after Amazon, Google, you know, because they're doing some pretty progressive things. Oh, facial recognition, you got AI, you got Alexa. You know, a lot of people are like, "Oh, I'm scared." But, at the end of the day, they also have some challenges like network security, so you have all this AI up and down the stack. And, one thing I like about what's being talked about in the industry is the shared responsibility model. So, I got to ask you, as AI becomes exciting, but also, balancing, frightening to people, how do you get that shared responsibility model, so we get it right, do the experimentation, without people freaking out? (laughs) So, it's kind of like this weird mode we're in now, where I want to do more AI, because I think it benefits society, but everyone's freaking out. >> Yeah, so, in our tech vision that we just launched, The Tech Vision 2020, there's a lot of talk about value and values, which is really important when we think about AI because we can get great value out of it, but there's a values piece of it and it's how we're using it, how we're getting those insights. Because, the one thing, we have this circle, and it's between customer experience, because the companies that do customer experience well are going to excel, they're going to keep their clients, they're going to do amazing things, they're going to become sticky. But, to do that well, you have to be a good custodian of their data and their information, and curated experiences that they want, and not the creepy ones, not the ones they don't want. And so, we really look at that trust is necessary in that ecosystem, in building that, and keeping that with clients. So, that's something that came out of our technology vision. And, in fact, we're going to be talking at the Executive Women's Forum, this is tomorrow, and we're going to be having a panel on AI, and defending it, which will be very interesting. >> Make sure your people film that conference. We'd like to get a view of it on YouTube after. We love those conferences, really insightful. But, I want to get back to what you were talking about, the fun side. >> Yeah. >> You got a lot of new things on, your guys are kicking the tires on, scratching the surface on. You have two operating labs, one in Washington D.C., and one in Israel. What city in Israel? Is it in Tel Aviv or-- >> Herzliya. >> Okay, did not know. >> Yeah, the tech district, just north of Tel Aviv. It's the hotspot. >> So, Silicon Valley, D.C., and Israel, hotbeds of technology now. >> Yes. >> What's coming out of those labs, what's hot? >> Oh, there's so much exciting stuff coming out of our lab in Herzliya. One of the things that we have, and it's something that's been long and coming, it's been brewing for a while, but it's really looking at creating a model of the enterprise security posture. And, when I say a model of it, I'm talking about a cyber digital twin. Because, so much we can't do in our production networks, we don't have the capabilities. We can look around the room, but we don't have the capabilities on the SOCs team side, to ingest all this stuff. We need a playground where we can ask the what-ifs, where we can run high performance analytics, and we do that through a temporal knowledge graph. And, that's a hard thing to achieve, and it's a hard thing to do analytics at scale. So, that's one of the big projects that we're doing out of our Israel lab. >> Are you saying digital twins is a framework for that? >> Yeah. >> Does it really work well with that? >> So the knowledge graph, we can create digital twins around many things, because a digital twin is a model of processes, people, technologies, the statefulness of things, and configurations, whatever you want to pull in there. So, when we start thinking about, what would we take in to create the perfect enterprise security posture? What would give us all the insights? And, then we can ask the questions about, okay, how would an adversary do lateral movement through this? I can't fix everything that's a 10, but I could fix the right ones to reduce the risk impactfully. And, those are the kind of what-ifs that you can do. >> That's real sci-fi stuff, that's right around the corner. >> Yeah, it is. >> That simulation environment. >> It is. >> What-ifs. Oh my god, the company just got hacked, we're out of business. That's your simulation. You could get to, that's the goal, right? >> It absolutely is, to ask those good business questions about the data, and then to report on the risk of it. And, the other thing, as we move to 5G, this problem's getting bigger and bigger, and we're now bringing in very disparate kinds of compute platforms, computing-at-the-edge. And, what does that do to our nice little network model that we had, that our traditional systems are used to defending against? >> I mean, just the segmentation of the network, and the edge opens up so much more aperture-- >> Yes, it does (laughs). >> to the digital twin, or a knowledge graph. You brought up knowledge graph, I want to get your thoughts on this. I was just having dinner last night with an amazing woman out of New York. She's a Ph.D. in computer science. So, we're talking about graphs, and I love riffing on graph databases. But, the topic came up about databases in general, because with the cloud, it's horizontally scalable, you've got all kinds of simulation, a lot of elasticity going on, there's a lot of software being written on this. You got time series database, you got relational database, you got unstructured, and you got graphs. You got to make them all work together. This is kind of the unique challenge. And, with security, leveraging the right database, and the right construct is a super important thing. How do you guys look at that in the labs? Because, is it something that you guys think about, or is it going to be invisible someday? >> Oh, we think about it a lot. In fact, we've had a number of research projects over the last five years now, actually six years, where we've really pivoted hard in cyber security to graph databases. And, the reason for that is, the many-to-many relationships, and what we can do in terms of navigating, asking the questions, pulling on a thread, because in cyber hunting, that's what we're doing. In many of these use cases that we're trying to defend an enterprise, we're following the next new path based on the newest information of now what the challenge is, or what the current configuration is. So, that's really important. So, graph databases enable that so well. Now, there's still the architecture challenge of, okay, when I ask a query, what am I doing? Am I disrupting the whole apple cart? Do I have to process everything over, or is there a way to do that elegantly, where I can ask my query, and because of how I've structured it in storage, I can do it much better, and I can do it much more efficiently. And that, I think, is where the opportunities are. >> I got to tell you, I'm getting exited now on this whole database discussion, because you think about the logic around what you just said. A graph database with that kind of complexity, when you factor in contextually different things happening at any given time, the database needs to be parsed and managed differently. >> Yes. >> That's a huge challenge. >> It is a great research challenge, which is why we're doing it. >> What is that, how far along are we going to be able to have this dynamic, self-evolving, self-governing, self-healing data modeling? Is that coming soon, or... >> Yeah, I hope so. We wrote about it a couple of years ago. >> You did? >> The self-healing enterprise, aspirational. But I think, I mean, we try to get to real time, right? And, we try to get to real time, and again, refactoring. As we talk about what an adversary is going to do, or lateral movement through a business process, we're talking about a lot of computational horsepower to recalculate all that, process it again, update it, and then again present that back. So the number of things we're asking, how we're asking it becomes also very important to the structure. >> Just, it goes zooming up a little bit, high level, what we're really talking about here is value >> of the data. >> Absolutely. >> And, when you get into the valuation of the nodes, and the arcs, and all that graphs, and other databases, you got to know what to pay attention to. It's kind of like going into the hospital and hearing all these alarms going off. At some point you don't know what's, until they hear a flat line, or whatever. >> Right. That's a bad one. >> I mean, well that's obvious. But, now sometimes there's so many alerts, there's so many alarms. How do you understand at any given time what to pay attention to, because obviously when someone's having a problem you want to pay attention to it. If it's a security alert, that's prioritized. >> And the devil is in the analytics, right? What's the question we're asking, and the analytics that give us that prioritization? And that's non-trivial, because there are a lot of other folks that are doing prioritization in a different manner. To do it at scale, and to do it, not just one hop out, but I want to go all the way to the crown jewels, I want that whole path navigated, and I want to know where to cut along that path. That's a hard thing to do. And so, we've actually developed, and we've submitted patents for them, but we've developed new analytics that'll support that. >> Awesome. Well Lisa, I want to ask you kind of a, I'll give you a plug here, just going to get it out, because I think it's important. Skills gap's a big thing, so I want to give you a minute to explain, or share what you're looking for in your hiring. Who are you looking for? What kind of, the make-up of individual, obviously? Maybe, do you use straight, more academic paper kind of people, or practitioners? I mean, when you look to hire, what are some of the priorities that you look for, and who would thrive in an Accenture Lab's environment? >> Oh, my goodness. >> Take a minute to share what you're looking for. >> Yeah, so we love people that think out of the box, and those kinds of people come from very different backgrounds. And so, part of that is, some of them we look for Ph.D.'s, that have wonderful applied skills, and applied is a key word there. White papers are great, I need to be able to prove something, I need to be able to demo something that has value. So, having the applied skills to a business challenge is really important. So, that sort of ground, understanding the business, very important too. But, our talent comes from many different areas. I mean, I kind of joke, my lab looks like the UN, it's wonderful. I have people from across the globe that are in our cyber security lab. I have, in our Washington D.C. lab, we're 50% women, which is also exciting, because we want different experiences, and we shoot for cognitive diversity, right? So, we're looking for people that think differently about solving problems, and are not encumbered by what they've seen in the past, because we're trying to be tip of spear. And, I'm sure you know that from Paul Daugherty. >> Yeah. >> We are trying to be three to five years over the horizon. >> You guys got a good narrative. I always love talking to Accenture, they have a good vision. So, I got to ask you, the next logical question is, obviously, in the news, you see everyone talking about breaches, and ya know, it's not a breach if the door's open, you just walk in. They're really walking in, nothing was really breached, you're just giving it to them. >> Yeah. It's a passive invitation. >> (laughs) Hey come on in. Human error is a big part of it, but then, breach is obviously targeted, phishing, and all that good stuff. But, as those stories get told, there's a whole nother set of stories that aren't being told that are super important. So, I'd love to get your thoughts on, what are the most important stories that we should be talking about that aren't being talked about? >> Yeah, so I have two that are front-of-mind for me. One theme we come back to, and it's not sexy, it's hygiene. It is IT hygiene, and so many of the large companies, and even medium, small companies, we have legacy technology, and keeping that adds complexity, it adds to the whole breadth and depth of what we have to manage and defend. Keeping that attack surface simple and small, cloud-enabled, all those good things, is a real asset and it makes it much easier to defend. So, that's kind of the first non-sexy one, hygiene. The other one I'll say that I think is a challenge that we are not dealing with yet, quantum computing, right? And so, we're on the way to getting our post quantum cryptography in place, but there's another dimension to it, and it's our histories. So, all of the things that have passed on the wire, all the communications with the key exchanges, all that brilliant stuff, is sitting somewhere. Once we get to that point where this becomes very routine, and it's coming fast, we predicted eight years, two years ago. >> So, all that exhaust is somewhere, pent up. >> It's somewhere that, we have to think about how much data we're keeping as custodians, how we're managing it, and then we have to think about the exposure from our past, and say, "Okay, what does that mean that, that was out there?" "Is it aged enough that it doesn't have value?" And, I think there's a real triage that needs to be done, and certainly data management. >> I think, you know, the hygiene brings up a good point. It reminds me of the story Andy Jassy was telling about the mainframe customer that they couldn't find who had the password. They had to find their person, who was retired 10 years earlier to get the password. You don't forget things, but also, there's a human component in all this. Humans and machines are working together. >> Absolutely. >> And. that's a huge part of it. It's not just machines dominating it all, there's going to be a human component, there's a societal impact that we're seeing with information. And, whether that's out in the open, or behind closed doors, there's all kinds of things looming. >> There are, and I think one of the things in the companies that we're seeing who are embracing innovation well, are doing a lot of retraining. Because, the things that people are excellent at, AI is not good at, and the things that AI is good at, are not at all what people are good at. So, the good news is there is a beautiful teaming there, if we retool the skills, or if we re-envision those roles, so that people can get into those roles, and I think that's really important, because I'd rather see AI do all the heavy lifting well, and be trustworthy, and robust and all those great things, and the people be doing the much smarter things that require a human. >> Does the process serve the purpose? Does the purpose serve the process? Same kind of question, right? >> Exactly. >> AI, you can't have great AI that does nothing. >> That's right. >> (laughs) So, it has to be relevant. >> It absolutely does. >> Relevance is kind of a big thing. >> And we own that context, right? Humans own that context. >> Yeah. Yeah. Yeah. Well, thanks for coming in, and sharing the insight. Really appreciate it. Final question, it's always tough to pick your favorite child, but what is your most coolest thing you're working on right now? >> I'll tell you, the cyber digital twin stuff is so cool. >> The what? >> The cyber digital twin stuff is so cool. When you see the power of what that picture, and the analytics can do, we'll show ya. >> Do you have a demo of that now? >> We absolutely do. >> You do. Is it online, or is it more in person you got to see it? >> More in person. >> Okay. >> Folks can reach out, yeah. >> We'll have to get the exclusive on that. >> We do. >> I love those simulations. I think it's very beneficial. >> It is. >> A lot of learning. I mean, who doesn't want practice? >> Well, and a picture, you know that is worth a million dollars. It's just incredible to look at it, and it clicks. It clicks of all the potential things you could ask or do. And, that's the exciting part now, as we show this with customers' and we co-innovate with customers', they're coming up with a laundry list of questions. >> And, this is the beautiful thing about cloud, is that new capabilities are emerging every day, and you could use the good ones. Lisa O'Connor is here. Thank you very much for sharing your insights. Global Security R&D Lead for Accenture Labs. TheCUBE coverage, getting all the signal here on the show floor, extracting that from all the noise. I'm John Furrier, thanks for watching. (upbeat music)

>> From the Salesforce Tower in downtown San Francisco, it's theCube, covering Accenture Tech Vision 2019, brought to you by SiliconANGLE Media. >> Hey welcome back everybody, Jeff Frick here with theCube. We're in downtown San Francisco with the Salesforce Tower. We're in the 33rd floor with the grand opening of the Accenture Innovation hub. It's five stories inside of the Salesforce Tower. It's pretty amazing, couple of work floors and then all kinds of labs and cool things. Tonight they introduce the technology vision. We've been coming for a couple of years. Paul Daugherty and team. Introduce that later, but we're excited to have a couple of the core team from the innovation hub. And we're joined by Mary Hamilton She's a managing director of Accenture Labs. Great to see you Mary. >> Nice to see you too. >> And Teresa Tung also managing director of Accenture Labs. Welcome. >> Thank you. >> So it's been quite a day. Starting with the ribbon cutting and the tours. This is quite a facility. So, what does it mean having this type of an asset at your disposal in your client engagements, training your own people, it's a pretty cool spot. >> Yeah, I think it's actually something that's, these innovation hubs are something that we're growing in the U.S. and around the world, but I think here in San Francisco, we have a really unique space and really unique team and opportunity where we're actually bringing together all of our innovation capabilities. We have all of them centered here and with the staircase that connects everyone, we can now serve clients by bringing the best of the best to put together the best solutions that have open innovation and research and co-creation and innovation all in one. >> Right and you had a soft opening how many months ago? So you've actually been running clients through here for a number of months, right? >> We have. So, we've been working here probably about six months in the workspaces. We've been bringing clients through, kind of breaking in the space, but just over the holidays we opened sort of all of the specialty spaces. So, the Igloo, the Immersive Experience, we've got a Makeshop, and those all started to open up so our employees can take advantage and our clients can come in. >> Right, right. >> Yeah. >> So one of the things that comes up over and over I think in every other interview that we've had today is the rock stars that are available here to help your clients. And Teresa I got to brag on you. >> Got one here. >> You're one of the rock stars, all you hear about is most patents of any services for most patents from this office of all the other offices in Accenture. >> All of Accenture >> You're probably the person. (laughs) So congratulations. Talk about your work. It's funny, doing some research, you have an interview from a long time ago, you didn't even think you wanted to get in tech. >> Yeah. >> Now you're kicking out more patents than anybody in Accenture which has like 600,000 people. Pretty great accomplishment. >> I think it's a great story how a lot about people think about technology as a geek sort of thing and they don't actually picture themselves in that role but really, technology is about imagining the future and then being able to make it happen. You can imagine an idea, and you think Cloud, and AI, VR, it's all so accessible today. You could buy a 3D printer and just print your own idea. >> Right. >> And that's so much different than I think it was even ten, twenty years ago. And so when you think about tech, it's much more about making something happen instead of, just again, coding and math. Those are enablers but that's not the outcome. >> Right, right. So what type is your specialty in terms of the type of patent work that you've done? >> I've done them all. So I start with cloud computing, doing a lot of APIs and AI. Most recently doing a lot of work on robotics and that's the next generation. >> Right. so one of the cool things here is, software is obvious, right? You get to do software development, but there's a lot of stuff. There's a lot of tangible stuff. You talked about robotics, there's a robotics lab. Fancy 3D printing lab. >> There's like this, >> Yep. >> I don't know, the maker lab, I guess you call it? >> That's right. >> So, I don't know that most people would think of Accenture maybe as being so engaged in co-creation of physical things beyond software innovation. So, has that been going on for a long time? Is that relatively new? And how is it playing in the marketplace? >> Yeah, so, there's a few things we've been doing. Some of it is the acquisitions we've made, so Mindtribe, Pillar, Matter, that really have that expertise in industrial design and physical products. So we're getting to that space. And then, I'm also, as a researcher's standpoint, I'm really excited about some of the area that you'd never think Accenture would play in around material science. So if you start to combine material science plus artificial intelligence, you start to have smart materials for smart products and that's where we see the future going is what are all the kinds of products and services that we might provide with new material? And new ways to use those materials And, >> Right. >> My original background, my degree is in material science so I feel like I've kind of come full circle and exactly what Teresa was saying is how can you design things and come up with new things? But now we're bringing it from a technology perspective. >> Right, got to get that graphene water filtration system so we can solve the water problem in California. That's another topic for another day. But I think one of the cool things is really the integration of the physical and the software. I think a really kind of underreported impact of what we're seeing today are connected devices. Not that they're just connected to do things, but they phone home at the end of the day and really enable the people that developed the products, to actually know how they're being used. And then the other thing I think is so powerful is you can get shared learning. I think that's one of the cool thing about autonomous cars and Waymo, right? If there's an accident, it's not just the people involved in the accident and the insurance adjuster that learn what not to do but you can actually integrate that learning now into the broader system. Everyone learns from one incident and that is so, so-- >> Right. >> different than what it was before. >> Yeah I mean, it really points to type of shared pursuits of larger business outcomes. By yourself, a company might see their customer and impact their business and their product, but if you think about the outcome for the customer, it's around taking an ecosystem approach. It might be your car, your insurance company, you as an individual, and maybe you might be a hobbyist with the car, you're mechanic. Like this ecosystem that I just described here. It's the same across all of the different types of verticals. People need to come together to share data to pursue these bigger outcomes. >> Right, you need to say? >> I was just going to say, and along those lines, if you're sharing data, those insights go across the legal system. But then they can get plugged back in to thinking about the design, and we're looking at something called generative design where if you have that data, you can start to actually give the designer new creative solutions that they may not have thought about. >> Right. >> So you can kind of say, hey based on these parameters of the data we've received back about this product, here are all the permutations of design that you might want to consider, and here's all the levers you can pull and then the designer can go in and then say, okay, this makes sense, this doesn't. But it gives them the set of here are all of the options based on the data. >> Right. >> And I think that's incredibly brilliant. It's kind of the human plus machine coming together to be more intelligent. >> So, human plus machine, great Segway, right? What we just got out of the presentation and one of the guys said there's three shortages coming up. There's food, water and people. And that the whole kind of automation and machines taking jobs is not the right conversation at all, that we desperately need machines and technology to take many of the tasks away because there aren't enough people to do all the tasks that are required. >> I mean think about it as a good thing. As a human, the human plus workers really enabling your job to be easier, more efficient, more effective, safer. So any task that's dull dirty, dangerous, those are things that we don't want to do as humans. We shouldn't be doing those as humans. That's a great place for the robotics and the machines to really pair with us. Or AI, AI can do a lot of those jobs at scale that again, as a human we shouldn't be doing. It's boring. Now you could have human plus machine whether it's robotics or AI to actually make the human a higher level worker. >> Right, I love the three Ds there. You got to add the fourth D, drudgery. Talking about automation, right, it's like drudgery. Nobody wants to do drudgery work. But unfortunately we still do. I mean, I'm ready for some more automation in my daily tasks for sure. Okay, so before we wrap up. What are you looking forward to? We got through the ribbon cutting. Are there some things coming in the short term that people should know about, that you're excited that you're either doing here, or some of your, kind of research directives now that we got the big five from Paul and team. What are you doing in the next little while that you can share? >> Well, I'm excited to have clients coming in, so >> Yeah. >> Al lot of the innovations that we have like Quantum Computing. This is a big bet for Accenture. At the moment, at the time we started Quantum Computing, our clients weren't begging for it yet. We made that market. We went out and took a bet. We saw how the technology was changing. We saw the investments in Quantum. We made the relationships with 1QBit, with IBM and through that, now we're able to find this client opportunity with Biogen and that's the story that we published a drug discovery method that is actually much better than what would happen before. >> Right. >> Yeah. >> Mary? >> For me it's about, it's also the clients and it's thinking about it from a co-research and co-innovation standpoint. So, how do we establish strategic, multiyear, long-term relationships with our clients where we're doing joint research together and we're leveraging everything that's in this amazing center, to bring the best and to kind of have this ongoing cycle of what's the next thing. How are we going to innovate together, and how are we going to transform them, talk about approximately from building physical products to building a set of services. >> Right, right. >> And I think that's just taking advantage of this to make that transformation with our clients is so exciting to me. >> Well, what a great space with great energy and clearly you guys look like you're ready to go. >> Hey, we are. >> So congrats again on the event, and thanks for taking a few minutes and sharing this terrific space with us. >> Thank you. >> Thank you. >> All right. She's Teresa, she's Mary, I'm Jeff. You're watching theCube, from San Francisco the Accenture Innovation Hub. Thanks for watching, we'll see you next time. (upbeat music)

(upbeat music) >> Hello everyone. I'm John Furrier here in Palo Alto at our CUBE headquarters. We're here with John Del Santo, Senior Managing Director at Accenture for a Cube Conversation. John, welcome to theCUBE. Good to see you. >> Thanks, John. Great to be here. >> So we just talked before we came on camera about Accenture and all the stuff you guys are doing. You guys are in the cloud heavily. We've been following, you guys have probably one of the most comprehensive analytics teams out there. And global SI market and just, the world's changing. So it's pretty fun. I'm looking forward to this conversation. So I got to ask you first, before we get started. I want to jump in with a ton of questions. What is your role at Accenture? You're in the Bay Area. Take a minute to explain what you do for Accenture and what's your territory. >> I've got the best job at Accenture. So, Accenture's got close to half a million people right now and my job is, I'm responsible for our business on the West Coast, across all of our industries, et cetera. I've been here 32 years, so I've seen a lot of things happen in the Bay Area. And I now have the responsibility of making sure that we're doing great work for our clients. And we're doing great work in the community. And then we're providing great opportunities to the thousands of people that work for us here in the Bay Area and across the West Coast. So it's a lot of fun. >> Obviously, West Coast is booming. And for tech it's been a hotbed. And obviously the industry's across the board now is global. I got to ask you because, you know, you've been around multiple waves of innovation. And Accenture's been, had their hands in enabling a lot of value creation for clients. You guys have a great reputation. There's a lot of smart people. But the waves are always kind of different in their own way, but sometimes it's the same. What's different about the way we're living now? Because you can almost look back and see the major inflection points. Obviously the PC revolution, client server, interoperability, networking stacks went standard. Then you saw the Internet come. Now you've got Web 2.0. And now you got the whole global, you got things like cryptocurrency and blockchain. You have multiple clouds. You have a whole new game-changing dynamic going on with IT infrastructure combined with opensource at a whole 'nother level. So how is this wave different? Is it like the, how would you compare? >> Well, I think all the technologies that have waved through my career, at least, have been real enablers for the business model that the companies had at the time, and that they evolved. What we see now is epic disruption, right? So, the waves now are, we have digital native companies that are just disrupting the heck out of the industry or the company that we're trying to help. And so it's now about pulling all of those technologies together, and really figuring out a new business model for a client. Figuring out a new distribution channel, a new product that's maybe natively digital. And so it's very, very different, I feel, then it was five, 10, 15, 20 years ago, through some of the other waves. >> Talk about the things going on in the Bay Area before we get more in the global themes, because I think the Bay Area is always kind of a leading indicator. I call it a bellwether. Some cool things happened. You've got things like the Golden State Warriors got a stadium that's being built. I'm watching the World Series with the Red Sox, and you see Amazon stat cast, you're seeing overlays, you're seeing rosserial. All these things are changing the work and play. The Bay Area's got a lot of leading indicators. What are some of the projects that you've been involved in? What's happening now that you think is worth noting, that's exciting, that piques your interest? >> Yeah, I mean, we work across every industry, and we do a ton of work in tech, but I actually find some of the more interesting projects are the ones we're doing for healthcare companies in the Bay Area, some of the utilities in the Bay Area, some of the big resource companies, some of the financial services institutions, 'cause, like I said before, all of those industries have disruption coming or have been disrupted, and so we're doing some work right now around patient services in healthcare and in pharma that is really interesting. It's meant to change the experience that a patient has, that you and I have when we interact with our healthcare providers or, you know, the whole industry. And so those kinds of projects are real interesting cause a lot of these industries are old and sort of have a big legacy estate and model that they need to transform from. So they need to move fast, and we kind of describe it as a wise pivot. They sort of need to move, but they need to make sure they're moving at the right time. They can't hurt their existing business, but they got to pivot to the next business model, and that's happening in lots of places. And you're right, I think it is happening a lot in the Bay Area and the West Coast as sort of a bellwether. >> I want to get your thoughts on some of the moments that are going on in tech. You mentioned prior, before we came on camera, you worked for Apple in the old days. Tim Cook was just recently tweeting yesterday, and that tweet's going around, privacy. He was at this big GDPR conference. The role of regulatory now is changing some of the West Coast dynamics. Used to be kind of fast and loose West Coast, innovate, and then it gets operationalized globally with tech, tech trends. What's the tech enablers now that you see that are involved that actually have to deal with regulatory, and is regulatory an opportunity? You're mentioning utilities, finance, those are two areas you can jump out and say okay, we see something there. Privacy is another one. So you have a perfect storm with tech and regulatory frameworks. How has that impacted your job in the West Coast? >> Well, I mean, GDBR, we live with everyday. And clearly we're doing a ton of work in Europe. And I think that's one of the advantages Accenture has of being a big global company, and being able to take lessons learned from other parts of the world that are likely to come to the United States, et cetera, so, but I think the combination of tech and regulatory are going to be merging together here pretty quickly, especially when you talk about AI and data privacy, and that sort of thing. But it's definitely been an evolution. Great to hear Tim's point of view on what Apple thinks. And it's been really fun in my life to see Apple in the 80s when I worked there. They were a client of mine in the 80s. I worked with NEXT Computing in the 90s. And then obviously they're a big partner of ours now, so it's been a really interesting evolution. >> What are some of the growth accomplishments you guys have in the Bay Area? Obviously there's been growth here for you guys. Obviously, we've been seeing it. >> Well, I think the amount of tech-driven disruption, or digital transformation, we call it, is growing like crazy. So, you know, 20 years ago we were doing a lot of eCommerce work. We kind of shied away from doing Y2K work and a lot of our competitors saw that as a big opportunity. We didn't think it was a lot of value for our clients, fixing the old systems. And so we pivoted to eCommerce in a very aggressive way. And I would say now that's evolved even further, where more than close to 2/3 of our business here on the West Coast is what we call the new, which is clouds, security, digital analytics. And I really think it gets down to, we were talking a little bit earlier, about the data. And so we have more data scientists than we've ever had. We're probably hiring one or two every day out here on the West Coast. And it's about the data. Data is driving our consulting business. It's driving our technology business. It's driving what we're doing with AI, obviously, and things like that, so. The transformation's been pretty tremendous. >> So take a minute to explain the difference (mumbles), data, you mentioned a lot of things, you got data in there, you got cloud, and you mentioned earlier you got kind of cloud first companies, got born in the cloud, born in AI, AI first, data first, these new companies that are essentially disrupting incumbents, also your clients, that are kind of born before the cloud. And they got to transform. Is digital transformation one of those things or both of those things? How does digital transformation translate to the clients that you guys work with? >> Well, every client has a unique set of needs depending on where they came from. We do a lot of work with the digital natives. We do a lot of work with the unicorns out here on the West Coast. And their needs are different. You know, they need to learn how to scale globally. They need help in the back office. They need help sort of maturing their business model. We do a lot of work with legacy financial services companies, healthcare companies, that sort of thing. They need to figure out how to sort of, you know, pivot to digital products or digital interactions with their customers. We have a very large business now in Accenture Interactive around helping to find customer experiences for clients. And we think our mission is sort of help our clients really redefine that relationship with their customer, their supplier, their supply chain, and the experience is a key part of that. Given expectations means a lot. >> We have a lot of CUBE Conversations around IT transformation as well. And I had a CIO, big time firm, we won't say the name cause it'll out em, but he said, "We've been outsourcing IT for so many years, but now we got to build the core competency internally because now it's a competitive advantage." And they have to ramp up pretty quickly. Cloud helps them there, and they need partners that can help them move the needle on the top line. That this is not just cost control and operational scale or whether it's horizontally scalable scale-out or whatnot. Top line revenue. This is where the bread and butter of the companies are. >> Right. >> So how are you guys engaging with the clients? Give some examples of how you're helping them with the digital transition to drive their business, how do you engage them? Do you do the standard sales calls engagements? You bring them to a technology center? As the world starts to change, how do you guys help those clients meet those top lines? >> Well, a perfect client for us, you know, we're really good at helping clients cut costs and get really efficient and be good with their peers on cost structure. We love a client where they want us to help em with that and they want to pivot the savings to the new part. The way, one of the things that triggered a thought when you mentioned that was we like to bring our clients into our innovation hubs, so we've had labs here on the West Coast for a long time. We now have 10 innovation hubs in the U.S. We have a very large one in San Francisco now, and so we'll bring a client into our innovation hub and really roll up our sleeves with the client and over a week or two weeks or three period of time, we really brainstorm on envisioning their future for their company, build a minimal viable product if we have to out of our rapid prototyping capability and really envision what the target and state of their business could be, of their product could be or their customer interaction and we'll model it. Rather than sort of do a study, do another study, do a PowerPoint presentation, it's let's roll up our sleeves and figure out how to really pivot your business to the new and then take it from there. >> And they come to your location Absolutely. >> For an extended period of time? >> Yeah, so we'll have, any given day we'll have at least two different clients in our location doing either a couple a day workshop, a multi-week workshop, and it's co-creation. It's us collaborating with our client to figure out a solution. A good example is we had one of our large clients from the West Coast in there recently and we were trying to figure out how to use drone technology to drive analytics in, you know, over a geography to provide better data for them to minimize risk. And we've got a number of co-creation projects now going on with them to figure out how do we take that into a solution that not only helps their business but maybe it is a commercially available system. >> Yeah, our Wikibon research team brings us all the time with IOT and security you're starting to see companies leverage their existing assets, which is physical as well as digital and then figure out a model that makes them work together because these new use cases are springing up. So what if some of those use cases that you guys see happening, because you mentioned drones, cause that's an IOT device, right, essentially. There's all these new scenarios that are emerging and the speed is critical. It's not like, you can't do a study. There's no time to do a study. There's no time to do these things. You got to get some feet on the ground. You got to have product in market, you got to iterate. This is devops culture. >> Right. >> What is an example? >> So we did a project for a big ag company and not actually a West Coast based company but they came to our labs to look at it. And basically what we did was, we covered an area that's basically the size of Delaware in terms of drone video and we were able to drive analytics from that and ten times faster figure out for them where the forest was weak and where it wasn't. where they ought to worry about vegetation, where they might have disease issues or other risks that were facing them. And those analytics we were able to drive a lot faster and so rather than manually going around this huge square mile set of geography, they were able to sort of do it through technology a lot faster. >> Yeah, just a side note. I was talking to Paul Daugherty and interviewed him. We were celebrating, covering the celebration, your 30th anniversary of your labs. And one of the interviews I did was a wacky idea which made total sense, was during like a car accident or scene where there's been a car accident, they send drones in first and they map out the forensics- >> Sure. >> First. And you think, okay, who would have thought of that? I mean, these are new things that are happening that are changing the game on the road because they'll open up faster. They get the data that they need. They don't have to spend all that physical time laying things out. This is not just a one-off, this is like in every industry. Is there an industry that's hotter than another for you guys? (mumbles) oil and gas, utilities, financial services is kind of the big ones. What are some of the hot areas that you guys see the most activity on, on this kind of new way of taking existing industries and transforming them? >> I don't know if I could pinpoint an industry, I really don't. I mean, because I see what we're trying to do with anti-money laundering and banking is really moving the ball forward. What we're doing with patient services and pharma in health care is pretty aggressive. Even some of the things that we're doing for some of the states and governments around citizen services to make sure that ... Cause all of us have expectations now on how we want to interact with government and our expectations are not being met in just about every department, right? So we're doing a lot of work with states around how to provide a better experience to citizens. So I don't know if I could pinpoint an actual industry. One of the fun ones that we just, that we're involved with our here in our patch is one of the big gaming companies in Vegas. We are doing a lot of video analytics and technology and again, it's something like 20 times faster being able to detect fraud, being able to figure out what's going on on a gaming table and how to provide rewards quicker to their customers, keep em at the table faster or longer- >> He's got to nice stack of chips. Oh, he's going down. (laughs) Give him a comp through, he's feeling down. Look at his facial expression. I can (mumbles) imagine, I mean, this is the thing. I would agree. I think this every vertical we see is being disrupted. Just mentioned public sectors. Interesting. We were riffing at an Amazon event one time around who decides with the self-driving cars? These towns and cities don't have the budget or the bandwidth to figure out and reimagine the public services that they have, they're offering the citizens. The consumerization of IT hits the public sector. >> For sure. >> And they need help. So again every industry is going on. Okay, well I want to step back and get some time in for analytics because you guys have been investing as a company heavily in analytics in the past 10 years. Past, I think, seven years, you guys have been really, really ramping up the investment on data science, analytics. Give us an update on that. How is that going? How's that changed? And what's the update today? >> Yeah, and it's a good point. I mean, and again, you mentioned those labs being here for 30 years. A lot of our data scientists and big machine learning and big data folks frankly started at the labs here years and years ago and so, we've now got one of the largest analytics capabilities, I think, of any services company globally. We called it applied intelligence. It's a combination of our analytics capability and artificial intelligence, and we basically have an analytics capability that's built into all the different services that we provide. So we think it's, everything's about analytics just about. I mean, clearly you can't do a consulting project unless you've really got a unique analytical point of view and unique data around assessing a client's problem. You really can't really do a project or implement a system without a heavy data influence. So we are adding, frankly, I think every day I'm approving more analytics head count into our team on the West Coast in lots of different practices. And so it disbands industries, it spans all the platform sets, that sort of thing, but we're the largest of most of the big data players. >> I think one of the consistent trends with AI, which is now being the word artificial intelligence, AI, is kind of encapsulated the whole big data world because big data's now AI is the implementation of it. You're seeing everything from fraud. You mentioned anti-money laundering, know your customer, these kind of dynamics. But you get the whole dark web phenomenon going out there with fraud. All kinds of underground economies going on. So AI is a real value driver across all industries around one, understanding what's happening, >> Sure. >> And then how to figure out how to applications development could be smarter. >> Right. >> This is kind of relatively new concept for these scale out applications, which is what businesses do. So how is that going? Any color commentary on the impact of AI specifically around how companies are operationally changing and re-imagining their businesses? >> Well, I think it's very early days for most of our clients, most big companies. I think, we've done some recent surveys that say something like 78% of our clients believe that AI's really, really important and they're not at all prepared to deal with or apply it to their business. So I think it's relatively early days. There's a huge fight for skills, so we're building our team and that sort of thing. We're also classic Accenture. We grow skills pretty well too through both on-the-job training and real training. And so I think we're seeing sort of baby steps with AI. There's a lot of great vended solutions out there that we're able to apply to business problems as well. But I think we're in relatively early days. >> It's almost as if, you know, the old black-box garbage in, garbage out. You have good data, >> Exactly. >> and you got to understand data differently, and I think what I'm seeing is a lot of data architects going on, figuring out how do we take the role of data and put it in a position to be successful. It's kind of like, cause then you use AI and you go, that's great, but what about, oh, we missed this data set. >> Right. >> You'll have fully exposed data sets, so this is all new dynamics. >> So you have to iterate through it and you'll have to (mumble) solutions that'll start and restart. >> All right, so final question for you. Talk about this technology hubs again. So you have the labs, get that. So how many hubs do you have, technology hubs? >> Well, in the U.S., there's 10. But I would say in the West Coast it's really San Francisco and Seattle right now, with San Francisco being our flagship and frankly it's a flagship in the U.S. We've had the 30 year presence of our labs here on the West Coast and we've had design studios on the West Coast. We've had our what we call liquid studios, which is a big rapid prototyping sort of capability. We've had our research, et cetera. We've pulled all of those locations, so our lab started in Palo Alto, went to San Jose and is now in San Francisco. We've pulled all those locations together into what we're calling the innovation hub for the West Coast and it's a five-story marquee building in San Francisco and it's where we bring our clients and we expect to have literally, I think last year we had 200 and something client workshops and co-creation sessions there. This year we think the number's going to go to 400 and so it's really becoming a fabric of all our practices. >> How important is the co-creation, because you have a physical presence here and it's the flagship for the innovation hub and it's an accumulation of a lot of work you guys have done across multiple things you've done. Labs, liquid labs, all that stuff coming together. How important is the co-creation part as a mechanism for fostering collaboration with your clients? Co-creation's certainly hot. Your thoughts on co-creation. >> Great question, and I would tell you Accenture's kind of gone through waves as technology's gone through waves and so we were always an enabler for a client's projects and we did a lot of project work. I think we're in a wave now where we're going to be the innovation partner. We continue to sort of be named the innovation partner or the digital partner for certain clients. And we're going to do that through co-creating with them, and it's not just at their site, et cetera. It's going to be co-creation in our labs where we're taking advantage of the hundreds of data scientists and computer researchers and technical architects that we have in our labs to create something that's new and fresh and purpose-built for their particular business model. So we think co-creation is a huge part of the formula for us being successful with our clients over the next 10 years. And so that's why we've put this infrastructure in place, expect it to expand and to be sold out and that sort of thing. But it's a good way for us to build capability and really, really viable solutions for our clients going forward. >> So it's not just a sales development initiative. It's an operationalized engagement and delivery mechanism for you guys. >> Exactly, exactly. It's not, I mean it has, it self markets but it's not about marketing. It's about, we'll have tours and we'll have a little tourism through our center and so clients'll say, Wait, look at that maker lab. Look what you're doing with that client. I want one of those, right? I need to do that in my business, even though I'm in a different industry. So it's not really a marketing tool per se, it's a way for us to interact and engage with our clients. >> Well, it's a showcase in the sense of where you can showcase what you have and if clients see value, they can go to the next step. It's an accelerated path to outcomes re-imagining businesses. Okay, final question. What have you learned from all this? Because now you guys have a state of the art engagement model, delivery model, around cloud, all these things coming together, perfect storm for what you guys do. As you guys look back and see what you've built and where it's going to go, what are the key learnings that you guys came out of the West Coast team around pulling it all together over the years? What's the key learnings? >> Well, I think that our clientele is just thirsty for innovation and innovation now. It's now about sort of let's envision the future and we'll get to it some other day. It's what can we do right now and what journey, what glide path are we on to change our business? So the pace is just radically different than it used to be. And so it's about changing, rapidly changing, putting real innovation on it, and collaborating with clients in a pace that we've never seen before. I mean, I've been here 32 years and I've just never the pace of change. >> That's great, John. So (mumbles), really appreciate it. We'll get a quick plug in. What's coming up for you guys? What's going on in the West Coast? What's happening? >> Well, we're in event season right now, so we just finished all the ... We're wrapping up Oracle Open World. We just won five awards at Oracle Open World. We just did an acquisition on the West Coast to beef up our Oracle capabilities. We've got ReInvent and we have all kinds of events coming up but it's a, it's been a pretty busy season. >> So cloud and data have certainly helped rise the tide for your business. >> 100%. I mean, cloud is taking Accenture from kind of in the back of the office and put us into the front office over the last 10 years. >> Well, certainly it's awesome, (mumbles), leveling the playing field, allowing companies to scale out very rapidly, bringing a devops culture, new kinds of modern application developments, real value being created, super exciting time. Thanks for coming in and sharing your time. John Del Santo here in theCube for Cube Conversation, senior managing director at Accenture. I'm John Furrier here in theCube studios for Cube Conversation. Thanks for watching. (upbeat music)

>> Announcer: Live, from Las Vegas, it's theCUBE! Covering Informatica World 2018. Brought to you by Informatica. >> Hello everyone welcome back, this is theCUBE's exclusive coverage at Informatica World 2018 here live, in Las Vegas at The Venetian Ballroom. I'm John Furrier, your host of theCUBE, with Peter Burris, my co-host this week, Analyist at Wikibon, Chief Analyst at SiliconANGLE and theCUBE. Our next guest is Sanjeev Vohra, Group Technology Officer at Accenture, in charge of incubating new businesses, growing new businesses, handling the talent. Great to have you on thanks for spending the time coming on. >> Pleasure, it's my pleasure to be here. >> So we have a lot of Accenture interviews, go to thecube.net, type in Accenture, you'll see all the experts. And one of the things we love about talking with Accenture, is you guys are in the front lines of all the action. You have all the customer deployments, global system integrator, but you've got to be on top of the new technology, you've got really smart people, so thanks for spending the time. So I got to ask you, looking at the landscape, of the timing of Informatica's opportunity, you've got data, which is not a surprise for some people, but you've got GDPR happening on, this Friday, you've got cloud scale on the horizon, a lot of interesting things are going on right now around data and the impact of customers, which is now pretty much front and center. What're you guys doing with Informatica, what are some of the things that you guys are engaging with them on, and what's important to you? >> We have a very deep relationship with Informatica for many years and, we have many, many, joint clients in the market, and we are helping them sustain their businesses, and also grow their businesses future. Right? In future. And I think, I think there's a lot going on, there's a lot going on sustaining the core of the business, and improving it on a continuous basis, by using new technologies, and, you know, like today's keynote went on a little, talked about the new stuff and it's, there's a lot of things, actually, clients require, or our customers require for, just sustaining their core. But then I caught something in the middle, which is basically: how are you building your new business models, how are you disrupting the market your industry, what's new around that? And, in that piece, I think that's where, we are now starting working with Informatica to see what other pieces we need to bring together to the market, so we can generate, so we can help clients or customers to really leverage the power of technology. And I'll tell you, there are four areas of discussion priorities, that are, you know, you get a sense, and we get a deep dive depending on what you want to see. The first one is, I think the customers now have data warehouses, which are Data 2.0, as is what's told in the morning, so these are still 15 years old data warehouses, they are not in the new. So a lot of customers, and a lot of organizations, large organizations, including some organizations like ours, they're investing right now to make sure that they get to Data 3.0, which is what Anil was saying in the morning, which is around the new data supply chain, because without that, you cannot actually get real data analytics. Right? So you can't generate insight on analytics unless you actually work on your data's infrastructure layer below, so that's one area where we are working with them, that's where the cloud comes in, that's where the flexibility of cloud comes in. The second piece is around, around data compliance and governance because, guess what, there're regulations which are coming up now, which are towards data privacy and data protection. And the data infrastructures which were built 15 years back, actually do not handle that so effectively. >> In being polite, yeah. I mean, it wasn't built for it, they didn't have to think about it. >> Sanjeev: It was not built for that, exactly. So now, now, the point there is that, now there is a regulation coming in, one of them is GDPR, Global Data Protection Regulation, it impacts all the global companies who deal with your EU residents. And now they are looking at how they can address that regulation, and be compliant with that regulation. And we believe that's a great opportunity for them to actually invest. And see how, not only comply with regulation, but actually make this a benefit for them. And make the next leap towards building a next level of infrastructure for them, their data, right? >> And that is doing a lot of the data engineering, actually getting data right. >> And that's the third piece. So the first two are this: one is infrastructure, second is compliance, and the third reason, they're all interrelated finally, but I'm just saying, it depends on, from where do you want to begin your journey, right? And the third piece is around, I think you got it right, is about quality of data, but actually it is not quality, we call it data voracity, it's much beyond quality. We talk about more completeness, and also things like provenance, integrity, and security along with it, so if we, and it's very much business contextual element, because what's happening is, you may have heard the story is that, clients have invested in data lakes, for years now, it's been there for like, eight, nine years, data lake concepts, and everybody talks about it-- >> John: Throw everything into the lake. >> And everybody says throw everything into the lake, and then they become a data swamp. (John laughing) - That was last years theme. >> That was last years theme, and the reason is because, because it's not IT's failure, IT is actually pretty advanced, the technology is very advanced. If the business is not as involved as it should be, and is not able to trust the data, and that's where your point comes in, whether you have the right data, and trusted data with you. >> Though, well we had Toyota on earlier and they said, one of the customers said, we had this 2008 post crisis thing and then, they had all this stuff channeled, they had product in channel, and they had the data! They actually had the data, they didn't have access to it! So again, this is like the new data center, data first, get it right, and so with GDPR we're seeing people saying okay, we've got to get this right. So that's, investing engineering involved, governance, application integration, this is all, now, a new thing. How do you guys advise you clients? 'Cause this is super important and you guys are, again, on the front edge. As a CTO group, you got to look at the new tech and say, okay, that's baked, that's not baked, that's new, that's old, throw a container around it, you know. (laughing) How are you sorting through the tools, the platforms? 'Cause there's a lot of, there's a lot of stuff out there. >> Oh yes, absolutely, and there's a lot of stuff, and there's a lot of unproven things as well, in the market. So, the first and foremost thing is that, we should understand what the context in the market right now is. The first question is, mine is, is everybody ready for GDPR? The answer is no. (John laughs) Are they, have they started into the journey, have they started getting on the racetrack, right, on the road? >> Yes? Yeah? It depends on a majority of that organization, some people have just started building a small strategy around GDPR, some people have actually started doing assessments to understand how complex is this beast, and regulation, and some people have just moved further in the journey of doing assessment, but they're now putting up changes in their infrastructure to handle remediation, right? Things like, for example, consent management, thinks about things like dilation, like, it's going to be a very big deal to do, right? And so they are making advantageous changes to the infrastructure that they have, or the IT systems to manage it effectively. But I don't think there's any company which properly can claim that have got it right fully, from end-to-end, right? So I think that's happening. Now, how are we addressing? I think the first and foremost thing, first of all we need to assess the majority of the customers, or the organization. Like BHD, because we talk to them first and understand, we understand, right? Usually we have various ways of doing it, we can have a chit-chat, and meet the person responsible in that company, it could be a Chief Data Officer of a company, it could be a CIO of a company, it could Chief Operating Officer of a company, it could be a CSO of a company, depending on who has a baton in the sea of suites, to kind of handle this problem. >> So it's different per company, right, so every company has their own hierarchy or need, or entry point? >> Data companies have different entry points, but we are seeing more of the CSOs and CIOs playing a role in many of the large organizations, and our, you know our clientele is very large companies, as you know. But we see most of these players playing that role, and asking for help, and asking for having a meeting, and starting with that. In some cases, they have not invested initially, we talked to them, we assess them very quickly, very easy, quick as it's in, you know, probably in a couple of days or day, and tell them that, let's get into a, what we call is, assessment as step one, and that takes four to six weeks, or eight weeks, depending on the size of their application suite, and the organization. And we do it quite fast, I mean initially, we were also learning. If you were to have asked me this question 12 months back, we had an approach. We've changed that approach and evolved that approach now. We invested hugely in that approach itself, by using a lot of machine learning to do assessment itself. So we have now a concept called data discovery, another concept called knowledge graph. >> And that's software driven, both with, it's all machine learning or? >> Sanjeev: It's largely computer driven. But obviously human and computer work together, but it's not only human. A traditional approach would happen to do only with humans. >> John: Yeah, and that've been takin' a long time. >> And that has changed, that has changed with the new era, and technology advancement, that even for, things which are like assessment, could now be done by machines as well, machines are smart enough to do that work, so we are using that right now. But that's a step one, and after that, once we get there, we build a roadmap for them, we ensure that they're stakeholders are agreeing with the roadmap, they actually embrace the roadmap! (laughing) And once that's done, then we talk about remediation to their systems. >> So, you mention voracity, one of the, and you also mentioned, for example, the idea of the, because of GDPR, deletion, which is in itself a voracity thing, so you, it's also having a verifiable actions on data. So, the challenge that you face, I think, when you talk to large customers, John mentioned Toyota, is, the data's there, but sometimes it's not organized for new classes of problems, so, and that's an executive issue 'cause, a lot of executives don't think in terms of new problem, new data, new organization. You guys are speaking to the top executives, CSOs, CIOs often but, how are you encouraging your clients, your customers, to think differently, so that they become data-first? Which is, kind of a predicate for digital business transformation anyway. >> So I think it's a great question. I think it depends again on, who you're talking to in the organization. I have a very strong perspective, my personal view is that data is an intersection of business and technology, it is not a technology, it's not a business, right? It's an intersection of both, especially this topic, it has to be done in collaboration within business and technology. Very closely in terms of how, what is the, how you can drive metadata out of your data, how can you drive advantage out of your data? And, having said that, I think the important thing to note down is that: for every, when you talk about data voracity, the single comment I will make that it is very, very, very contextual to business. Data voracity is very, very contextual to the business that you're running. >> Well, but problems, right? Because, for example, going to Toyota, so, when the Toyota gentleman came on, and this is really important, >> Absolutely. >> the manufacturing people are doing a great job of using data, lean is very data-driven. The marketing people were doing a great job of using data, the sales people were making a great job of using data, the problem was, the problems that Toyota faced in 2008, when the credit crunch hit, were not limited. They were not manufacturing problems, or marketing problems, or sales problems, they were a wholistic set of problems. And he discovered, Toyota discovered, they needed to say, what's the problem, recast the problem, and what can we do to get the data necessary to answer some of these crucial questions that we have? >> So, I think you hit the nail, I can tell, I mean, I think you're spot on, and the one way we are doing right now, addressing that is through, what we call our liquid studios, >> John: I'm just going to-- >> Peter: I'm sorry what? >> Liquid studios. >> Peter: Liquid studios. >> We have this concept called liquid studios. >> John: Yeah, yeah. >> And actually, this concept we started, I don't know if you heard about this from Accenture before? we started this thing couple of years back-- >> John: Well take a minute to explain that, that's important, explain liquid studios. >> Okay, so liquid studios, so what, when we were thinking about these things where, we talked to multiple clients, they called us, exactly the point, they may be working in silence, and they may be doing a great job in their department, or their function, but they are talking across enterprise. As to how they can, if you are doing great work, can I use your work for my advantage, and vice versa, right, because it's all sharing data, even inside enterprise, forget outside enterprise, and you will be amazed to know how much sharing happens today, within enterprise, right? And you're smiling, right, so? So what we did was, we came to this concept, and the technologies are very new and very advanced, and many of the technologies we are not using beyond experimentation, we are still in the COE concept, well that's different than enterprise ready deployment. Like, if we talk about ERP today, that's not a COE, that's an enterprise ready deployment, in most of the companies, it's all there, like, you run your finance on ERPs right, most of the companies, big companies. So we felt that, technology's advancing, the business and technology IOs, they all have to still agree on a concept, and define a problem together. And that's where the studio comes in, so what we do is, it's actually a central facility, very innovative and creative space, it's unlike an office, it's very much like, new, new thing, it's like very, differently organized structure to generate creativity and good discussion. And we bring in core customers there, we have a workshop with them, we talk about the problem for one or two days, we use design thinking for that, a very effective way. Because one thing we've learned, the one thing that brings our table to agreement on a problem. (laughing) (John and Peter laugh) In a very nice manner, without confronting, in a very subtle manner. So we, through this timeframe, we get to a good problem situation, a good problem definition and then, the studio can actually help you do the POC itself. Because many times people say, well I understand the problem, I think I kind of get your solution, or what your proposing, my people also tell me something else, they have a different option to propose. Can we do it together? Can I get the confidence that, I don't want to go in enterprise ready deployment and put my money, unless I see some proof of pudding, but proof of pudding is not a power point. It's the actual working mark. >> Peter: It's not?! >> It's not! (all laughing) and that's where the studio comes in picture because, you wouldn't believe that we do these two days of workshop without any Powerpoint, like we aren't on a single slide. >> So it's creative, it's very agile, very? >> It's more white boarding, come and talk, it's more visitation, more visitation now, more human interaction, and that's where you open up everybody saying: what is your view, what is your view? We use a lot of post-it stickies to kind of get the-- >> I think the business angle's super important, I want to get your thoughts. 'Cause there's a lot of problems that can be solved once you identify them. But we're hearing terms like competitive advantage, 'cause when you solve some of these problems, these wholistic problems, that have a lot of interplay, where data's shared, or where there's internal, and or external with APIs and cloud-native, you start thinking about competitive advantages, being the data-first company, we've heard these terms. What does that mean to you guys? When you walk into an executive briefing, and they say look, you know, we've done all this work, we've done this engineering, here's where we're at, we need help, but ultimately we want to drive top-line results, be more competitive, really kind of move with the shift. This is a, this is more of a business discussion, what do you guys talk about when you have those conversations? >> I think we, so first of all, data was always a technical topic, do you agree? Like if you just go back, 10 years back, data was always a CIO discussion. >> Well, >> Unless you're in a regulated industry like financial services or, >> Or I guess I'd say this, that the, that the notion of getting data out of a system, or getting data into a system, was a technical discussion. But there was, you know, we've always used data, from market share growth, etc. But that was relatively simple, straight-forward data, and what you're talking about, I think, is, getting into considerably greater detail about how the business is really operating, how the business is really working. Am I right? >> You're right, considering data as an asset, in a discussion in terms of, how can you leverage it effectively, that's what I was saying and, so it is, it's definitely gone up one more level upstaged or into the discussion that is, into the companies and organizations. And what we're saying is, that's where the business comes in effectively and say that, helping them understand, and by the way, the reason I was making that comment is because, if you have ever seen people expending data 10 years back, it is very complex explanation. >> Schemas, this, that, and the other thing. >> You got it, yeah. And it's very hard for a business guy to understand that, like if I'm a supply action lead, I don't get it, it's too complex for me. So what we did, I'm just letting you know how we started the discussion. The first and foremost thing is, we tell them, we're going to solve the business problem, to your point, that's what we think, right? And, every company now-a-days, they want to lead in their industry, and the leadership position is to be more intelligent. >> Yeah, and it's got to hit the mark, I mean, we had Graeme Thompson on, who's the CIO, here at Informatica, and he was saying that if you go to a CFO and ask them hey where's the money, they'll go oh, it's over here, they get your stuff, they know where it's stored, at risk management, they say, where's they data? You mentioned asset, this is now becoming a conversation, where it's like, certainly GDPR is one shot across the bow that people are standing up, taking notice, it's happening now. This data as a asset is a very interesting concept. When I'm a customer of yours, say, and I say hey Sanjeer, I have a need, I got to move my organization to be data-first but, I got to do some more work. What's my journey? I know it's different per customer, depending on whether it's top-down, or bottom-up, we see that a lot but. How do you guys take them through the journey? Is it the workshop, as you mentioned, the assessment, take us through the journey of how you help customers, because I'm sure a lot of them are sittin' out there goin' now, they're going to be exposed with GDPR, saying wow, were we really setup for this? >> Yeah, so I think in the journey, it's a very good question that you asked. The journey can start depending on the real, the biggest pain they have, and the pains could be different on the majority of that particular organization, right? But I can tell you what client position we are having, in a very simplified manner, so that you understand the journey, but yes, when we engage with them, there's a process we follow, we have a discovery process, we have a studio process, together have a workshop, get into a POC, get into a large-scale deployment solution en route. That's a simple thing, that's more sequential in nature, but the condition is around four areas. The first and foremost area is, many companies actually don't have any particular data strategy. They have a very well articulated IT strategy, and when you go to a section of IT strategy, there's a data component in that, but that's all technology. About how do you load, how do you extract those things. It talks about data architectures, and talks about data integration, but it doesn't talk about data as a business, right? That's where it's not there, right? In some companies they do have, to your point, yes, some companies were always there in data, because of regulatory concerns and requirements, so they always had a data organization, a function, which thought of data as different from other industries. And those industries have more better strategy documents or, or they're more organized in that space. But, guess what, now companies are actually investing. They're actually asking for doing help in data strategies, that's one entry point which happens, which means, hey, I understand this, I understand governance is required, I understand privacy's required, and I understand this is required, I also understand that I need to move to new infrastructure, but I can't just make an investment in one or two areas, can you help my build my strategy and road map as to what should be my journey from now til next three years, right, how does it look like? How much money is required, how much investment is required, how do I save from something and invest here, help me save internal wealth, right? That's a new concept. Right, because I don't have so much that you're asking for, so help me gain some savings somewhere else. That's where cloud comes in. (laughs) So, that's one entry point, the second entry point is totally on, where the customers are very clear, they actually have thought through the process, in terms of where they want to go, they actually are asking, very specifically saying, I do have a problem in our infrastructure, help me move to cloud. Help me, that's a big decision right, help me move to cloud, right? But that's one, which I call is, new data supply chain, that's my language. Which means that-- >> John: I like that word actually. >> Yeah? I'm making your supply chain and my supply chain in business terms, if I have to explain business, it's different, technically it's different. Technology, I can explain all the things that you just mentioned, in business I explain that there are three Cs to a supply chain, capture it, curate it, consume it, and they so, oh I get it now, that's easy! >> Well, the data supply chain is interesting too, when you think about new data coming in, the system has to be reactive and handle new data, so you have to have this catalog thing. And that was something that we saw a lot of buzz here at the show, this enterprise catalog. What's your take on that, what's your assessment of the catalog, impact to customers, purpose at this point in time? >> I think it's very important, especially with the customers and large companies, who actually have data all over the place. I can share, as an example, we were talking to one of the customers who had 2600 applications, and they want to go for GDPR, we had a chat with them, and we said look, they were more comfortable saying, no, no, let's no use any machine. Because when you talk about machine, then you have to expose yourself a bit, right? And I said look, the machine is not going to be in my place, it's going to be in yours, your boundaries of firewall. But they were a little more concerned, they said let's go with a manual approach, let's do that, I said fair enough, it's your call, we can do that as well. But guess what? 2600 applications, you can't discover manually, it's just not possible. >> John: Yeah, you need help. A lot of data streaming and-- >> I guess I'm just letting you know it's very, I'm just answering your question. The data catalog is extremely important, if you really want to get a sense of where the data is residing, because data is not in one or two applications, it's all over the place. >> Well I'm impressed by the data catalog positioning, but then also, when you look at the Azure announcement they had, that Informatica had. You're essentially seeing hybrid cloud playing out as a real product. So that's an easy migration, of bringing in some of those BI tools, bringing some democratization into the data discovery. Rajeev, thanks for coming on theCUBE, really appreciate it, love the work you do, and I just want you to take a minute, just to end the segment out. Explain the work that you do, you have two roles, real quick, explain your two primary roles. You've got the, you incubate new stuff, which is hard to do, but, I'm an entrepreneur, I love the hard problems, but also you're doing talent. Take a minute to kind of explain, real quickly, those two roles, for, super important. >> well, the first one is basically that I, my role, I look at any ideas that are, that we can incubate as a business, and we can work within Accenture, different entities within Accenture to make sure that we go to clients in a much more quiescent manner, and see how we can have an impact to our top line. And that's a big thing, because our, we are a service as a business and, we have to be very innovative to come to know how do we increase our business. >> Any examples that you can share, of that stuff that you worked on? >> So, one is, right now, I'm spending a lot of my time in, on fueling our data business itself. We just recently launched our data business group, right? We have our market way in this position, is called applied intendance, which you may be aware, which includes data, analytics, advanced analytics, and then artificial intelligence, all put together, then we can solve these problems. >> And you guys got a zillion data scientists, I know that, you guys have been hiring really, really strong people. >> It's a very strong team. But on that, what I feel is that, the data is a critical foundation, really critical foundation for an intelligent enterprise. You can become and intelligent enterprise unless you have right data, to your point. And right data means curated data, in the set, in the fashion that can help you become, draw more insights from your enterprise. And that's possible if you invest in data strongly, and selection of data so strongly, but that's why we are fueling that, so I'm just letting you know that I'm spending most of my time right now to enhance our capability, you know, enhance our power in on that, and go to market with that. The second thing which I am investing right now, which is, there is a few more ideas, but one more, which could be very useful for you to know, is, while companies are moving to the new, they have to also, they have to rely on their people. Ultimately the companies are made of people. Like us, right? And if you can, if you are not retooling yourself, you cannot reimagine the future of your organization as well. >> You're talking about the peoples, their own skills, their job functions, okay-- >> So I'm working on a concept called workforce of the future right, how can 44 companies, large companies, how can they transform their talent, and their, even leadership as well, so that they are ready for the future and they can be more relevant. >> Yeah, and this is the argument we always see on theCUBE, oh, automation's going to take jobs away, well, I mean certainly automating repetitive tasks, no one wants to do those, (laughing) but the value is going to shift, that's where the opportunities are, is that how you see that future workforce? >> Absolutely, it's one of the complimentary, we have Paul Daugherty, whom you know, who's the Chief Technology Officer of Accenture Technology. Accenture, Accenture as a firm, he, he's a Chief Technology and Innovation Officer for Accenture He has recently written a book called Human + Machine, exactly talked about the same concept that, we actually all believe, very, very strongly that, the future is all about augmenting humans together. So there are tasks which machines should be doing, and there are tasks where humans should be doing, and there are tasks which both of them do collaboratively, and that's what we are trying to boast. >> Cloud world, we're doing it here in theCUBE, here at Informatica World. Rajeev, thanks so much for spending time-- >> Sajeev. (laughing) Sajeev, I mean, thanks for coming on. Sorry my bad, a little late in the day. But we're bringing it out here at Informatica World, this is theCUBE, I'm John Furrier with Peter Burris, here with Accenture inside theCUBE, here at Informatica World in Las Vegas. Be right back with more coverage, after this short break. Thank you. (bubbly music)

>> Hey welcome back, everybody. Jeff Frick here with the CUBE. We're at the Accenture Technology Vision 2018, actually, the preview event, 'about 200 people. The actual report comes out in a couple of days. A lot of interesting conversations about what are the big trends in 2018 in Accenture. Surveyed Paul Daugherty and team and really excited. Just was a panel discussion to get into a little bit of the not exactly a technology, but really the trust and ethics conversations. We're joined by Dr. Shannon Vallor. She's a professor at Santa Clara University. Dr. Vallor, great to see you. >> Great to be here, thank you! >> So you were just on the panel, and of course there was a car guy on the panel. So everybody loves this talk about cars and autonomous vehicles. You didn't get enough time. (chuckles) So we've got a little more time, which is great. >> Great! >> But one of the things that you brought up that I think was pretty interesting is really, kind of a higher-level view of what role technology plays in our life before. And you said before it was ancillary, it was a toy, it was a gimmick. It was a cool new car, a status symbol, or whatever. But now technology is really defining who we are, what we do, how we interact, not only with the technology of other people. It's really taken such a much more fundamental role with a bunch more new challenges. >> Yeah, and fundamentally that means that these new technologies are helping to determine how our lives go, not just whether we have the latest gadget or status symbol. Previously, as I said, we tended to take on technologies as ornaments to our life, as luxuries to enrich our life. Increasingly, they are the medium through which we live our lives, right? They're the ways that we find the people we want to marry. They're the ways that we access resources, capital, healthcare, knowledge. They're the ways that we participate as citizens in a democracy. They are entering our bodies. They're entering our homes. And the level of trust that's required to really welcome technology in this way without ambivalence or fear, it's a kind of trust that many technology companies weren't prepared to earn. >> Jeff: Right, Right. >> Because it goes much deeper than simply having to behave in a lawful manner, or satisfy your shareholders, right? It means actually having to think about whether your technologies are helping people live better lives, and whether you're earning the trust that your marketing department, your engineers, your salespeople are out there trying to get from your customers. >> Right. And it's this really interesting. When you talked about a refrigerator, I just love that example 'cause most people would never let their next door neighbor look into their refrigerator. >> Shannon: Or their medicine cabinet, right? >> Or their medicine cabinet, right. And now you want to open that up to automatic replenishment. And it's interesting 'cause I don't think a lot of companies that came into the business with the idea that they were going to have this intimate relationship with their customers to a degree, and a personal responsibility to that data. They just want to sell them some good stuff and move on >> Sure. >> to the next customer. >> Yes. >> So it's a very different mindset. Are they adjusting? How are the legacy folks dealing with this? >> Well, the good news is, is that there are a lot more conversations happening about technology and ethics within industry circles. And you even see large organizations coming together to try to lead in an effort to develop more ethical approaches to technology design and development. So, for example, the big five leaders in AI have come together to form the partnership for AI and social good. And this is a really groundbreaking movement that could potentially lead other industry participants to say, "Hey we need to get on board with this, "and we have to start thinking >> Right. >> "about what ethical leadership looks like for us," as opposed to just a sort of PR kind of thing. Yeah, we throw the word "ethics" on a few websites or slides and then we're good, right? >> Right. >> It has to go much deeper than that. And that's going to be a challenge. But it has to be at a level where rank and file workers and project managers have procedures that they know how to go through that involve ethical analysis, prediction, and preparing ethical responses to failures or conflicts that might arise. >> Right, there's just so many layers to this that we could go on for a long time. >> Sure. >> But the autonomous band has kicked up. >> Yes, yes! >> But one of the things is when you're collecting the data for a specific purpose, and you put all the efficacy in as to why and how, and what you're going to treat, what you don't know is how that data might be used by someone else next week, >> Yes. >> next year, >> Yes. >> ten years from now. >> Absolutely. >> And you can't really know because there's maybe things that you aren't aware of. So a very difficult challenge. >> And I think we have to just start thinking in terms of different kinds of metaphors. So data up until now has been seen as something that had value and very little risk associated with it. Now our attitudes are starting to shift, and we're starting to understand that data carries not just value, not just the ability to monetized, but immense power. And that power can be both constructive or destructive. Data is like jet fuel, right? It can do great things. >> Right. >> But you've got to store it carefully. You have to make sure that the people handling it are properly trained. That they know what can go wrong. >> Right. >> Right? That they've got safety regimes in place. No one who handles jet fuel treats it the way that some companies treat data today. But today, data can cause disasters on a scale similar to a chemical explosion. People can die, lives can be ruined, and people can lose their life savings over a breach or a misuse of data that causes someone to be unjustly accused of fraud or a crime. So we have to start thinking about data as something much more powerful than we have in the past. >> Jeff: Right. >> And you have the responsibility to handle it appropriately. >> Right, but we're still so far away, right? We're still sending money to the Nigerian prince who needs help getting out of the airport at Newark Airport. I mean, even just the social, >> Yes. >> the social factors still haven't caught up. And then you've got this kind of whole API economy where so many apps are connected to so many apps. >> Right. >> So even, where is the data? >> Yeah. >> And that's before you even get into a plane flying over international borders while you send an email, I mean. >> Right, yes. >> The complexity is crazy! >> Yep, and we're never going to get a handle on all of it. So one of the things I like to tell people is, it's important not to let the perfect become the enemy of the good, right? >> Jeff: Right. >> So the idea is, yes, the problem is massive. Yes, it's incredibly complex. Can we address every possible risk? Can we forestall every possible disaster? No. Can we do much better than we're doing now? Absolutely. So, I think, the important thing is not to focus on how massive the problem or the complexities are, but think about how can we move forward from here to get ourselves in a better and more responsible position. And there's lots of ways to do that. Lots of companies are already leading the way in that direction. So I think that there's so much progress to be made that we don't have to worry too much about the progress that we might never get around to making. >> Right, right. But then there's this other interesting thing that's going on that we've seen with kind of the whole "fake news," right? Which is algorithms are determining what we see. >> Shannon: Yes. >> And if you look at the ad tech model as kind of where the market has taken over the way that that operates, >> Shannon: Yep. >> there's no people involved. So then you have things happen like what happened with YouTube, where advertisers' stuff is getting put into places where they don't want it. >> Yeah. >> But there's really no people, there's no monitoring. >> Yes. >> So how do you see that kind of evolving? 'Cause on one hand, you want more social responsibility and keeping track of things. On the other hand, so much is moving to software, automation, and giving people more of what they want, not necessarily what they need. >> Well, and that means that we have to do a much better job of investing in human intelligence. We have to, for every new form of artificial intelligence, we need an even more powerful provision of human intelligence to guide it, to provide oversight. So what I like to say is, AI is not ready for solo flight, right? And a lot of people would like that to be the case because, of course, you can save money if you can put an automated adjudication system in there and take the people out. But we've seen over and over again that that leads again and again to disaster and to huge reputational losses to companies, often huge legal liabilities, right? So we have to be able to get companies to understand that they are really protecting themselves and their long-term health if they invest in human expertise and human intelligence to support AI, to support data, to support all of the technologies that are giving these companies greater competitive advantage and profitability. >> But does the delta in the machine scale versus human scale just become unbearable? Or can we use the machine scale to filter out the relatively small number of things that need a person to get involved. I mean. >> Yeah, and the-- >> How do you see some kind of some best practices? >> Yeah, so the answer depends on the industry, depends upon the application. So there's no one size fits all solution. But what we can often do is recognize that typically human and AI function best together, right? So we can figure out the ways in which the AI can amplify the human expertise and wisdom, and the human expertise can fill in some of the gaps that still exist in artificial intelligence. Some of the things that AIs just don't see, just don't recognize, just aren't able to value or predict. And so when we figure out the ways that human and artificial intelligence can compliment each other in a particular stetting, then we can get the most reliable results, and often the fairest and safest results. They might not always be the most efficient from the narrow standpoint of speed and profit, right? >> Jeff: Right, right. >> So they have able to step back and say at the end of the day, quality matters, trust matters. And just as if we put together a shoddy project on the cheap and put it out there, it's going to come back to bite us. If we put shoddy AI in place of important human decisions that affect human lives, it's going to come back to bite us. So we need to invest in the human expertise and the human wisdom, which has that ethical insight to round out what AI still lacks. >> So do you think the execution of that trust building becomes the next great competitive advance? I mean, >> Yeah. >> nobody talks about that right? Data's the new oil, >> Sure! And blah, blah, blah, blah, blah. And software defined, AI driven automation, but that's not necessarily only to the goal in road, right? There's issues. >> Right. >> So is trust, you think? >> Absolutely. >> The next great competitive differentiator? >> Absolutely. I think in the long run it will be. If you look at, for example, the way that companies like Facebook and Equifax have really damaged, in pretty profound ways, the public perception of them as trustworthy actors in, not just the corporate space, right? But in the political space for Facebook, in the economic space for Equifax. And we have to be able to recognize that those associations of a major company with that level of failure are really lasting, right? Those things don't get forgotten in one news cycle. So I think we have to recognize that today people don't know who to trust, right? It used to be that you could trust the big names, the big Fortune 500 companies. >> The blue chips, right. >> The blue chips, right. >> Right. >> And then it was the little fly by night companies that you didn't really know whether you could trust, and maybe you'd be more cautious in dealing with them. Now the public has no way of understanding which companies will genuinely fulfill the trust in the relationship >> Right. >> that the customer gives them. And so there's a huge opportunity from a competitive standpoint for companies to step up and actually earn that trust and say, in a way that can be backed up by action and results, "Your data's safe with us," right? "Your property's safe with us. "Your bank account is safe with us. "Your personal privacy is safe with us. "Your votes are safe with us. "Your news is safe with us." >> Right. >> Right? And that's the next step. >> But everyone is so cynical that, unfortunately Walter Cronkite is dead, right? >> Sure. >> We don't trust politicians anymore. We don't trust news anymore. We don't trust, now more and more, the companies. So it's a really kind of rough world in the trust space. >> Yeah! >> So do you see any kind of (chuckles) silver lining? I mean, how do we execute in this kind of crazy world where you just don't know? >> Well, what I like to say is that you have to be cautiously optimistic about this because society simply doesn't keep going without some level of trust, right? Markets depend on trust. Democracy depends on trust. Neighborhoods depend on trust, right? >> Jeff: Right. >> So either trust comes back into our lives at some deep level or everything falls apart. Frankly, those are the only choices. So if nature abhors a vacuum, and right now we have a vacuum of trust, then there's a huge opportunity for people to start stepping into that space and filling that void. So I'd like to focus on the positive potential here rather than the worst case scenario, right? The worst case scenario is, we keep going as things have been going and trust in our most important institutions continues to crumble. Well, that just ends in societal collapse >> Right, right. >> one way or the other. If we don't want to do that, and I presume that if there's anything we can all agree on, it's that that's not where we want to go. >> Right. >> Then now is the time for companies, if need be, to come together and say, "We have to step into this space "and create new trusted institutions and practices "that will help stabilize society and drive progress "in ways that aren't just reflected in GDP "but are reflected in human wellbeing, "happiness, a sense of security, a sense of hope. "A sense that technology actually does gives us a future "that we want to to be happy about moving into." >> Right, right. >> Right? >> So I'll give you the last word. >> Sure. >> We'll end on a positive note. What are some examples of companies or practices that you see out there as kind of shining lights that other people should be either aware of, emulate. Let's talk about the positive before we >> Sure. cut you lose. >> Well, one thing that I mentioned already is the AI partnership that has come together with companies that are really leading the conversation along with a lot of other organizations like AI Now, which is an organization on the East Coast that's doing a lot of fantastic work. There are a lot of companies supporting research into ethical development, design, and implementation of new technologies. That's something we haven't seen before, right? This is something that's only happened in the last two or three years. It's an incredibly positive development. Now we just have to make sure that the recommendations that are developed by these groups are actually taken onboard and implemented. And it'll be up to many of the industry leaders to set an example of how that can be done because they have the resources >> Right. >> and the ability to lead in that way. I think one of the other things that we can look at is that people are starting to become less naive about technology. Perhaps the silver lining of the loss of trust is the ability of consumers to be a little wiser, a little more appropriately critical and skeptical, and to figure out ways that they can, in fact, protect their interests. That they can actually seek out and determine who earns their trust. >> Right. >> Where their data is safest. And so I'm optimistic that there will be a sort of meeting, if you will, of the public interest and the interests of technology developers who really need the public to be on board, right? >> Jeff: Right. >> You can't make a better world if society doesn't want to come along with you. >> Jeff: Right, right. >> So my hope is, and I'm cautiously optimistic about that, that these forces will come together and create a future for us that we actually want to move into. >> All right, good. I don't want to leave on a sad note! >> Great, yes. >> Dr. Shannon Vallor, she's positive about the future. It's all about trust. Thanks for taking a few minutes. >> Thank you. >> I'm Jeff Frick, she's Dr. Shannon. Thanks for watching. We'll catch you next time. (upbeat techno music)