>> Announcer: From San Francisco, it's theCUBE, covering Accenture Tech Vision 2020, brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Rick here with theCUBE. We're high atop San Francisco on a beautiful day at the Accenture San Francisco Innovation Hub, 33rd floor of the Salesforce Tower, for the Accenture Tech Vision 2020 reveal. It's where they come up with four or five themes to really look forward to, a little bit innovative, a little bit different than cloud will be big or mobile will be big. And we're excited to have, really, one of the biggest brains here on the 33rd floor. She's Teresa Tung, the managing director of Accenture Labs. Teresa, great to see you. >> Nice to see you again. >> So I have to tease you because the last time we were here, everyone was bragging on all the patents that you've filed over the years, so congratulations on that. It's almost kind of like a who's who roadmap of what's happening in tech. I looked at a couple of them. You've got a ton of stuff around cloud, a ton of stuff around Edge, but now, you're getting excited about robots and AI. >> That's right. >> That's the new passion. >> That's the new passion. >> All right, so robots, one of the five trends was robots in the wild, so what does that mean, robots in the wild, and why is this something that people should be paying attention to? >> Well, robots have been around for decades, right? So if you think about manufacturing, you think about robots. But as your kid probably knows, robots are now programmable, kids can do it, so why not enterprise? And so, now that robots are programmable, you can buy them and apply them. We're going to unlock a whole bunch of new use cases beyond just those really hardcore manufacturing ones that are very strictly designed in a very structured environment, to things in an unstructured and semi-structured environment. >> So does the definition of robot begin to change? We were just talking before we turned on the cameras about, say, Tesla. Is a Tesla a robot in your definition or does that not quite make the grade? >> I think it is, but we're thinking about robots as physical robots. So sometimes people think about robotics process automation, AI, those are robots, but here, I'm really excited about the physical robots; the mobile units, the gantry units, the arms. This is going to allow us to close that sense-analyze-actuate loop. Now the robot can actually do something based off of the analytics. >> Right, so where will we see robots kind of operating in the wild versus, as we said, the classic manufacturing instance, where they're bolted down, they do a step along the process? Where do you see some of the early adoption is going to, I guess, see them on the streets, right, or wherever we will see them? >> Well, you probably do see them on the streets already. You see them for security use cases, maybe mopping up a store after, where the employees can actually focus on the customers, and the robot's maybe restocking. We see them in the airports, so if you pay attention to modern airports, you see robots bringing out the baggage and doing some of the baggage handling. So really, the opportunities for robots are jobs that are dull, dirty, or dangerous. These are things that humans don't want to or shouldn't be doing. >> Right, so what's the breakthrough tech that's enabling the robots to take this next step? >> Well, a lot of it is AI, right? So the fact that you don't have to be a data scientist and you can apply these algorithms that do facial recognition, that can actually help you to find your way around, it's actually the automation that's programmable. As I was saying, kids can program these robots, so they're not hard to do. So if a kid can do it, maybe somebody who knows oil and gas, insurance, security, can actually do the same thing. >> Right, so a lot of the AI stuff that people are familiar with is things like photo recognition and Google Photos, so I can search for my kids, I can search for a beach, I can search for things like that, and it'll come back. What are some of the types of AI and algorithms that you're applying with kind of this robot revolution? >> It's definitely things like the image analytics. It's for the routing. So let me give you an example of how easy it is to apply. So anybody who can play a video game, you have a video game type controller, so when your kid's, again, playing games, they're actually training for on the skilled jobs. Right, so you map a scene by using that controller to drive the robot around a factory, around the airport, and then, the AI algorithm is smart enough to create the map. And then, from that, we can actually use the robot just out of the box to be able to navigate and you have a place to, say, going from Teresa, here, and then, I might be able to go into the go get us a beer, right? >> Right, right. >> Maybe we should have that happen. (laughs) >> They're setting up right over there. >> They are setting up right there. >> That's right. So it's kind of like when you think of kind of the revolution of drones, which some people might be more familiar with 'cause they're very visible. >> Yes. >> Where when you operate a DJI drone now, you don't actually fly the drone. You're not controlling pitch and yaw and those things. You're just kind of telling it where you want it to go and it's the actual AI under the covers that's making those adjustments to thrust and power and angle. Is that a good analogy? >> That is a great analogy. >> And so, the work that we would do now is much more about how you string it together for the use case. If a robot were to come up to us now, what should it do, right? So if we're here, do we want the robot to even interact with us to get us that beer? So robots don't usually speak. Should speaking be an option for it? Should maybe it's just gesturing and it has a menu? We would know how to interact with it. So a lot of that human-robot interface is some of the work that we're doing. So that was kind of a silly example, but now, imagine that we were surveying an oil pipeline or we were actually as part of a manufacturing line, so in this case it's not getting us a beer, but it might need to do the same sort of thing. What sort of tool does Theresa need to actually finish her job? >> Yeah, and then, the other one is AI and me. And you just said that AI is getting less complicated to program, these machines are getting less complicated to program, but I think most people still are kind of stuck in the realm of we need a data scientist and there are not a lot of data scientists and they got to be super, super smart. You've got to have tons and tons of data and these types of factors, so how is it becoming AI and me, Jeff who's not necessarily a data scientist. I don't have a PhD in molecular physics, how's that going to happen? >> I think we need more of that democratization for the people who are not data scientists. So data scientists, they need the data, and so, a lot of the hard part is getting the data as to how it should interact, right? So in that example, we were saying how does Teresa and Jeff interact with the robot? The data scientist needs tons, right, thousands, tens of thousands of instances of those data types to actually make an insight. So what if, instead, when we think about AI and me, what about we think about, again, the human, not the, well, data scientists are people too. >> Right, right. >> But let's think about democratizing the rest of the humans to saying, how should I interact with the robot? So a lot of the research that we do is around how do you capture this expert knowledge. So we don't actually need to have tens of thousands of that. We can actually pretty much prescribe we don't want the robot to talk to us. We want him to give us the beer. So why don't we just use things like that? We don't have to start with all the data. >> Right, right, so I'm curious because there's a lot of conversation about machines plus people is better than one or the other, but it seems like it's much more complicated to program a robot to do something with a person as opposed to just giving it a simple task, which is probably historically what we've done more. Here, you go do that task. Now, people are not involved in that task. They don't have to worry about the nuance. They don't have to worry about reacting, reading what I'm trying to communicate. So is it a lot harder to get these things to work with people as opposed to kind of independently and carve off a special job? >> It may be harder, but that's where the value is. So if we think about the AI of, let's say, yesterday, there's a lot of dashboards. So it's with the pure data-driven, the pure AI operating on its own, it's going to look at the data. It's going to give us the insight. At the end of the day, the human's going to need to read, let's say, a static report and make a decision. Sometimes, I look at these reports and I have a hard time even understanding what I'm seeing, right? When they show me all these graphs, I'm supposed to be impressed. >> Right, right. >> I don't know what to do versus if you do. I use TurboTax as an example. When you're filing TurboTax, there's a lot of AI behind the scenes, but it's already looked at my data. As I'm filling in my return, it's telling me maybe you should claim this deduction. It's asking me yes or no questions. That's how I imagine AI at scale being in the future, right? It's not just for TurboTax, but everything we do. So in the robot, in the moment that we were describing, maybe it would see that you and I were talking, and it's not going to interrupt our conversation. But in a different context, if Teresa's by herself, maybe it would come up and say, hey, would you like a beer? >> Right, right. >> I think that's the sort of context that, like a TurboTax, but more sexy of course. >> Right, right, so I'm just curious from your perspective as a technologist, again, looking at your patent history, a lot of stuff on cloud, a lot of stuff on edge, but we've always kind of operated in this kind of new world, which is, if you had infinite compute, infinite storage, and infinite bandwidth, which was taking another. >> Yes. >> Big giant step with 5G, kind of what would you build and how could you build it? You got to just be thrilled as all three of those vectors are just accelerating and giving you, basically, infinite power in terms of tooling to work with. >> It is, I mean, it feels like magic. If you think about, I watch things like "Harry Potter", and you think about they know these spells and they can get things to happen. I think that's exactly where we are now. I get to do all these things that are magic. >> And are people ready for it? What's the biggest challenge on the people side in terms of getting them to think about what they could do, as opposed to what they know today? 'Cause the future could be so different. >> That is the challenge, right, because I think people, even with processes, they think about the process that existed today, where you're going to take AI and even robotics, and just make that process step faster. >> Right. >> But with AI and automation, what if we jumped that whole step, right? If as humans, if I can see everything 'cause I had all the data and then, I had AI telling me these are the important pieces, wouldn't you jump towards the answer? A lot of the processes that we have today are meant so that we actually explore all the conditions that need to be explored, that we do look at all the data that needs to be looked at. So you're still going to look at those things, right? Regulations, rules, that still happens, but what if AI and automation check those for you and all you're doing is actually checking the exceptions? So it's going to really change the way we do work. >> Very cool, well, Teresa, great to catch up and you're sitting right in the catbird seat, so exciting to see what your next patents will be, probably all about robotics as you continue to move this train forward. So thanks for the time. >> Thank you. >> All right, she's Teresa, I'm Jeff. You're watching theCUBE. We're at the Accenture Tech Vision 2020 Release Party on the 33rd floor of the Salesforce Tower. Thanks for watching. We'll see you next time. (upbeat music)

>> 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)

(upbeat music) >> Man: From San Francisco it's theCUBE covering Accenture Tech Vision 2020 (upbeat music) brought to you by Accenture. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We are high atop San Francisco. It is absolutely beautiful outside. Sun is going down, we're here for a really special event, It's the Accenture Tech Vision, kind of unveiling of the five things that we should be paying attention to as we look to 2020 the year that we're going to know everything with the benefit of hindsight. So it's pretty exciting, it's pretty exciting time. And we have a new guest, Mike Redding, he's the managing director of Accenture Ventures telling us where the Accenture Ventures plays in all this stuff, so Mike, well, welcome. >> Well, thanks for having me, I'm really excited to be here. It's a big day here at Accenture with the launch of the 2020 tech vision. You know, and one of the key trends is about innovation DNA, which is really saying, how does an organization connect to the external ecosystems to systematically and scalably and sustainably innovate? And that's part of the role of Accenture Ventures. >> Well, it's an interesting play, right? Because unfortunately Clayton Christensen just passed away, my favorite business writer ever. And the whole innovator's dilemma is that smart people working at big companies making sound business decisions based on revenue and their customers will always miss this continuous change. So really you need some other things to help motivate that. And that's really piece that you guys play. >> Right, exactly cause what, you know, we're a bridge builder between those highly successful large enterprises, which are big, they're slow and they're risk adverse, and the startups, which are small, fast and nothing but risk. And so for us, the role of Accenture and Accenture ventures as being part of that innovation DNA is to say, let's make a bridge, let's figure out how the elephant can dance. And as a result, not get caught up in those disruptions, but in fact leverage them to propel those big enterprises forward. >> Right, now you guys invest in all types of areas, Ais, looking through the portfolio, security, big data, I love this Industry X Dot O, what is Industry X Dot O? >> Well, so, you know, a lot of places talk about industry 4.0 but we're like, why put it, you know, X dot O, is make it a variable? five point O, six point O, which makes it evergreen. Which says, every industry on the planet is going through a transformation, you know, powered by AI, powered by all those areas you mentioned. And as a result, we want to make sure that whatever the future of any industry is, Accenture is part of it and we're bringing in the startups and of course the big technology players that are going to be the fundamental players making that transformation possible. >> Right, there's so much synergy, right? Because for the little guys, right? They've got all the juice behind the innovation and the really smart people and they're kind of breaking things and moving fast, but the challenges there are scale and a sales force and marketing and reach and distribution and all these things that are not too hard for the big guys. >> Right, and so that's why it's a marriage made heaven, right? Again, if you can bring, I always like to say the analogy of you've got the aircraft carrier and then you have all the battleships and the PT boats circling around it, that's a battle group. And so that's what we really see as the opportunity is to bring what each strength, the strength of that disruption and passion and energy and capital to marry to market scale and data and customer base, right? Put those things together, unstoppable force? >> How do the enterprises, you know, kind of view it, do they, obviously they see the value, you wouldn't be doing what you're doing, but is that something that's attracted to them? Is it too disruptive to them? How do they try to work these little startups? Cause (laughs) the other thing, right? Is always vendor viability when you're a little startup doing business with a big company and they can kill you with meetings and there's all kinds of, you know, kind of interesting things that can happen to screw that up. >> Well you're right on and so that's part of where, you know, Accenture comes in as that broker, that bridge maker, because we help each other find how to match up, how not to crush the little guy with infinite meetings, you know, in an enterprise, you know, six months is quick, in a startup, that's a funding cycle, right? And so we've got to find a way to meet each other in the middle and as a result, get the strength of each, but pointed in the same direction and really, you know, become really good dance partners. And that's what we really think any organization, cause they know they need to do it, they know they want to do it, they just don't know how. And that's the gap we help fill. >> And then how do you find your investments? Are you partnering with other venture firms? How are you kind of out prospecting for new opportunities? >> Well, so for us, since we're a corporate strategic, we're really focused on the future of our client's business, the future of the marketplace. And so for us, it's a network game. It's, you know, it's everything from what the corporate venture units at our clients are up to where they're seeing strategic bets. Of course, we're the VC, you know, of Sand Hill Road, of Tel Aviv, of Shenzhen and Shanghai, you know, Bangalore, you know, there's so many great venture capital communities. We love the syndicate, we love friends because we, you know, a financial VC will bring their discipline and we'll bring Accenture's discipline and that's a combo pack that one plus one is three. >> Right, so I want to get your take, you've been in this for a while -- >> Oh, yeah. and one of the themes that we hear over and over, right, is the acceleration of accelerating pace of technology innovation, right? And this exponential curve and people have a hard time with exponential curves, we like linear curves. But it's getting steeper and steeper and steeper. So you know, from your kind of cap bird seed, as you've watched the evolution, do you see, you know, kind of, is this the only way for the enterprises to keep ahead of these things? Is it just an augment? Is it more important than it used to be? How has the landscape kind of changing as this acceleration just keeps going and going and going? >> Well, I think that the era of build it all yourself vertically integrate it So, you know, start to finish, soup to nuts yourself, you can't do it, right? If you're a large incumbent and, but also if you think about this way, and I would talk to audience especially, you know, business audience and say, "Who's got enough budget?" Nobody, there's no such thing as enough budget, the government doesn't have enough budget, right? Nobody does, but if you partner, you can leverage other people's money, their investment cycles, and as a result, for every dollar you have, you can get multiple dollars of leverage. And as a result, no matter how fast it's going, because of the Public Clouds, because of the big software players, you can get so much further. So even though things are moving faster, what you can leverage to adapt to that change is more powerful than ever before. So the good news is the rate of change is fast, but you're not starting from dead stop. You're jumping on a moving train and going where it's going and putting your own business spin on it. >> Right, the other piece is kind of the disruptive speeds. It's funny you mentioned Amazon just, you know, watch a lot of great interviews with Bezos. One of them, he talks about AWS having, you know, a seven-year uninterrupted headstart because no one down the road in Redwood shores or Philadelphia or Waldorf was really paying attention to the little bookseller up in Seattle as a competitor for enterprise infrastructure. So you know that which is going to get you is often not the competitors that you're benchmarking against. It's not the same people that you've been competing with but can completely come out of left field. >> Well, and so that again, is why we really believe passionately that with this future, the next few years, those enterprises that have an innovation DNA that get out of their foxhole and don't just look at your bank, don't just look at FinTech, look at all tech and thanks to this thing called the internet. It's really possible, and language translation, even if you don't speak Chinese, you can get a sense of what's happening in China, where you can call a friend like Accenture and we can hook you up. And regardless of the fact is you can now, if you cast that wide net, if you challenge yourself to get out of that Foxhole and look around, well then suddenly you can't be surprised. You can see it coming and you can then use your superpowers, which is incumbency, scale, balance sheet, customer base, you know, loyalty, all those things that you brand, all the things that make you strong, you can now append that disruption to it and basically, not get disrupted. So I think that's, that's the formula for going forward. >> Yeah, well, I love the one plus one makes three formula cause it really is kind of a match made in heaven really bringing together two sets of strengths that the other person or the other party doesn't really have. So you guys been at it for awhile and continued success. >> Well, thank you very much. All right. Well, Mike, thanks for taking a minute. He's Mike, I'm Jeff, you're watching theCUBE. With the Accenture Tech Vision launch 2020. Thanks for watching, we'll see you next time. (upbeat music)

>> Announcer: From San Francisco, It's theCUBE Covering Accenture Tech Vision 2020. Brought to you by Accenture. >> Hey welcome back, everybody. Jeff Frick here with theCUBE. We are high atop San Francisco, the 33rd floor of the Salesforce building. This is the San Francisco Accenture innovation hub, and we're really excited to have our next guest. She runs all the innovation hubs in all the Americas. It's Mary Hamilton, the managing director of Accenture Labs for Accenture. Mary, great to see you. We saw you last year. >> Great to see you, yes. >> Great to be back. >> But now you've had this place open for a year. Last year was the grand opening I think. >> It was, it was, and now we're doing all kinds of crazy new things here in our labs and in the hub. >> Yeah, that's great. So we've talked before that, you know, Paul and Mike and the team, they've put together this great vision document. It's very provocative and forward-looking and I think it is actually really thought-provoking. That's great, and we're going to have a nice party here and they're going to present, but how do we get this from this pretty piece of paper into my company or into your clients' companies? How do you and the innovation hub help them execute? >> Yeah, it is my job to bring this to life, all right? So it's all about, how do I do applied research, and how do I do that for our clients in a real way with new and emerging technologies? >> Jeff: Right. >> And so we take all of this vision and say, you know, what are the next round of technologies, and how do we think about it in new and different ways, and how do we do that in kind of a sustained, ongoing innovation direction? >> Right, right. So, you guys work with giant companies. They have millions, if not billions of R&D budgets. Where do you fit and how do you augment that? What's kind of the value add that your special asset brings to this huge investment that they're already making? >> Absolutely, so I think what we bring is the combination of everything that's here in this hub. So we've got business research. You know, what are the paradigms and the trends that we're seeing that are shifting society, politics, economics, and technology? We've got the technologists that are partnering with universities, partnering with startups. You know, think about how we view open innovation. And then, how do we actually build that for real, and how do we do it with that industry lens. We're so fortunate that, you know, out of the 500 thousand people we have here, we have deep, deep, industry expertise. So it's really about bringing all those pieces together and then working with those clients to say, how do we augment? How do we shape your future? How do we figure out what direction to go in, create that roadmap, and then together start to turn the crank on innovation from ideation all the way up through scale, and I think that's something pretty unique that we do really well. >> Right, and is it driven kind of top down from the CEO who says I have innovation kind of prerogative, go forth and innovate? Or do you see it more kind of with product groups that are trying to potentially go a slightly different direction, or incorporate some new technology? How does that actually work, or what are some of the models that you see that are successful, I guess? >> Yeah, and I would say yes, uh, all of those. >> Of course. >> You know, we do some big strategic things that are, you know, our CEO, you know, our client CEO coming together and say, you know, we're rethinking mobility. We're rethinking, you know, how we're going to shape our future, what are extended businesses that we've never thought of before? How do we go from a products to a services company? So there's, you know, the big CEO visions that trickle down, you know. We help them through strategy, through innovation, through the technology pieces to deliver that, and then there's also sort of that grassroots. You know, lab to lab pairing up and saying, okay. Let's create a partnership that, you know, you bring kind of the industry lab piece and we'll bring, you know, our technology labs and the work that we do, and come together to create that relationship. >> Right. >> So we've done both. (laughs) >> They're getting ready to start the program as you can tell. >> Mary: I know. (laughs) >> But I got to get a couple more questions. So there's a lot of different types of technology labs that you guys have in here. You've got a really cool quantum computing thing upstairs. You've got VR and AR and all these different things, but I know your passion, you talk about it every time I see you, is material science, >> Mary: It is. and, you know, I don't think if people, cause it's kind of under the covers, if you will, really appreciate the science advancements that are happening with materials, so when you think of kind of material science, how it's moving, and the opportunities that that's opening up just in the technology of the materials themselves, what gets you excited? What are some of the things that people should know about that maybe they're not paying attention to? >> Yeah, well, so first of all, I'm excited about it because that was my degree in college, and I never thought I would use it here at Accenture. (laughs) >> Jeff: Good lesson for those watching at home. >> Yeah, so I used to you know, work in a wet lab and build hydro gels and all kinds of cool, um... So this has been a journey for me, but what I'm really excited is this is a space that you wouldn't think of Accenture playing in normally, right? You wouldn't think of us having this expertise, but when you think about the proliferation of sensors that we think about today, material science allows you to start to do some of the same things that we see with sensors, and even actuators, but at the molecular level, and we can start to do it at a different scale than what's available today, whether it's at a really small scale, or really big scale with coatings, right, or even paint, that start to create really, truly interactive, connected spaces. You know, we all talk about IOT and connected spaces and connected buildings, and that's great, but imagine if everything's connective, like the walls, the floor, your clothing, and you can start to almost in a way have a conversation with the space, right? >> Jeff: Right, right. >> Have an interaction that's super personalized based on everything that's happening. You know, the environment understands everything that's going on, and ideally if we start to apply our research with AI, can start to understand well, what's your intent? What's the context? And then, how do you actually shape and create a super, super personalized experience? >> So just so people understand what you just said, well, let me make sure I understand. Now, you're talking about like in a coating, so instead of a sensor or many sensors, the actual coating, say inside of a pipe that you're trying to keep track of, the whole coating becomes one big sensor? >> Mary: That's right, exactly. >> Yeah, that's a pretty big game changer. (laughs) >> Yeah, yeah. >> And are you seeing the implementation? I mean, what are some of the ones that are actually out in the field today that people probably, you know, are rolling over, walking by, touching, and have no clue that they're really interacting with material science as opposed to electronics, for instance? >> It's still pretty early days, so this is why it's in our incubation stage, and we're playing with things like skin tattoos, right? You've probably, I dunno if you've seen Beyonce's. You know, have those gold leaf tattoos? Well we can do those same cool tattoos but make them controllers for your space, or you know the Levi's jacket that has the jacquard, we actually now have in house one of the teams that worked on that, and so, you know, we're starting to see, you know, in actual clothing, the ability to use that material science, conductive thread to create a whole new way of interacting. (laughs) >> Wow. >> Which is really, really cool, and then, you know, we're thinking about, you know, how do you create those advances? If you can use a stretchy polymer that understands when it's being stretched, you can start to apply that to, you know, maybe an armband or an elbow brace that for physical therapy understands how much you're bending your arm, and are you doing your physical therapy in the right way, so instead of, you know, once or twice going in your doctor and checking, you know, how are things going? >> Jeff: Right, right. >> They can have real time constant updates in a pretty lo-fi way, but it's through these new smart materials. >> Right, such cool stuff. >> Yeah. >> It's like, look at the smile. You love this stuff. >> (laughs) I do. >> All right, well we got to let you go, cause they're getting ready to kick off the big thing. >> I'm getting left behind! (laughs) >> And I don't want to get you the kick, so thank you for taking a few minutes, and thanks for having us back, and congrats to you and the team. >> Thank you, super fun and thanks for having me. >> All right, she's Mary, I'm Jeff. You're watching theCUBE with the Accenture Tech Innovation 2020 launch. Check it out online. They'll have all the stuff. It'll make you think, and thanks for watching. We'll see you next time. (energetic theme music)

>> Announcer: From San Francisco, it's theCUBE covering Accenture Tech Vision 2020, brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Rick here with theCUBE. We are high atop San Francisco, at the Accenture Innovation Hub, 33rd floor of the Salesforce Tower at the Accenture Technology Vision 2020 party. The party's getting started. Paul, and Mike, and the team are going to present the findings, and we're excited to have, actually, the hostess of this great facility. She's Ashley Miller, managing director of the San Francisco Innovation Hub. Ashley, great to see you. >> Great to see you again. >> So, congratulations once again. We were here last year. It was the grand opening of this facility. >> Ashley: Yes, sure was. >> You've had it open for a year now. >> We sure have. It's been a year. We also have a soft launch in September, so a little more than a year under our belt, and as you can see, the place is busy. >> Right, so you had the hard job, right? So Mike, and Paul, and all the big brains, they put together pretty pictures, and great statements. You're the one that actually has to help customers implement this stuff, so tell us a little bit about how you use the Tech Vision because it's pretty insightful. It's a lot deeper than cloud's going to be big, or mobile's going to be big, but to take some of these things to help you with your customers drive this innovation. >> Yeah, well, I don't know about having the hard job against theirs. They certainly have the hard job understanding what these technology trends are that are going to have an impact on business three to five years out, but I certainly do have the fun job, and the exciting job. I get to work with our clients every day here in the hub, and work with our 250 dedicated innovation teammates here in the hub to think about the impact of these trends to their business, so clients come in for a day, two days, a week, and we'll sit with technologists. We'll get our hands on some of these emerging technologies, on quantum computing, on artificial intelligence, machine vision, machine learning, natural language processing. You name it, we have it here. We have a smart materials showcase going on upstairs that a lot of these clients have checked out, so they can come here, they can get their hands on these technologies that are driving these trends, and then, they can sit and work with strategists, and others who can think about, what are the application of these technologies to their business? And then, what's really exciting is we have engineers here who can then help build prototypes to actually test these technologies to see what their impacts are for the business, and then, finally, support the rollout of pilots that prove successful, so it's, again, it's a fun job. I love it. >> And how does it actually work in terms of best practices? Is it starting out as some strategy conversation with the top-level people about trying to integrate say, more AI into their products, or is it maybe more of within a product group, where they're trying to be a little bit more innovative, and it really challenges on the product development path? You talked about the material science that they want to go down, what are some of the ways that people actually work with you, and work with your teams, and leverage this asset here at the hub? >> Yeah, so ultimately, it's both, and it's at all ends of the spectrum. We are here in the Silicon Valley, where clients are coming from all over the globe to understand what the trends are that are going to shape their business operations in the future, so we have clients that are coming through. Some people call them digital safaris, or innovation safaris. Some people may say that's not valuable. I think it is valuable to come and get firsthand experience, knowledge, touch and feel these things, and really dedicate time to think about the application to your business. On the other end of the spectrum, we'll have clients who are here for days, weeks, and months, and we have ongoing partnerships with clients. We've been open for about a year and a half, for that and longer to actually embed this innovation capabilities into their business, so I think maybe an answer is, what is the most successful model I see? I really get to dig into these clients who are using our services as an innovation engine to help them drive their business, and to help augment their innovation capabilities, and it's those clients I see who are continuously testing, continuously learning, understanding the impact of these technologies, driving proofs of concepts to test them who are able to make progress. >> Can it happen without top down support? I mean, we talked, unfortunately Clayton Christensen just passed away. Innovator's Dilemma, my favorite business book of all time because he said smart people making sound business decisions based on customers, profitability, and business, logical business priorities, will always miss discontinuous change. Jeff Bezos talks about AWS had a seven-year head start on their public cloud because no one down in Redwood Shores, or Waldorf was paying attention to the bookseller in Seattle, so it's hard for big companies to innovate, so is it really necessary for that top down, that, hey, we are going to invest, and we are going to saddle up, and get our hands dirty with some of these technologies for them to be successful, and drive innovation because it's not easy for big enterprises. >> You're exactly right. Innovation is hard. Change is difficult. I was a student of Clayton Christensen, and like you and many others, are mourning his passing. He made a significant impact, this area of research. Change is hard. It's difficult, so we see a lot of clients who are coming in, and are doing interesting things to overcome that inertia to stay put, and I think tops down leadership is a significant piece of that. You need to have leaders who are supporting movement, who are enabling decision making quickly, so they are supporting small decisions they're making frequently so that there's not a massive decision that happens at the end of a pilot, but rather, micro-decisions that help ensure things are being moved along, building pilots and proof of concepts, of course, helped in that movement to get buy-in, to get leaders to see the value, and to also pivot if something isn't working, so innovation is hard. Accenture's Innovation Hub helps to fill some of those gaps because really, we are a sandbox, where you can come in, build the proof of concepts, test these ideas, and then, in an ongoing, continuous way, help understand their impacts to your business. >> Right, and I'm just curious how often, as order of magnitude, this innovation around a particular, existing business, maybe it's the new materials, the new way of thinking about it, versus maybe, is this a way for them to really explore wild ideas, or go out a little bit beyond the edge of what they're going to execute in their normal, day to day, say, product development because which of those do you find is best use of your resources? >> Yeah, so again, it runs the spectrum. I mean, I think the companies who are innovating around the edges, they're spending a lot of money to run pilots, and tests, proof of concepts that may not have significant value to the core of their business, so of course, it's the companies who are really thinking about how they're going to innovate new business models, how they're going to build on these trends to figure out where their company is going in the future, and be ready, and be ahead of the curve, but in order to get there, maybe you do need to get your hands dirty, and run some tests, run some proof of concepts to understand the technology. The key is, in order to ensure that the investment in those activities is actually helping you move the needle. >> Right, so how should people, if somebody's watching this, and they want to get involved, or I'm busting my head. We're not moving as fast as we need to. I'm nervous. I have an imperative. I need to accelerate this stuff. How do they get involved, and how do they end up here getting their hands dirty with some of your team? >> Yeah, thanks for that, appreciate that. Accenture works with the largest organizations around the globe, and there's typically a client account leader, partner, from Accenture embedded into the biggest organizations, and so, for those who are existing clients, they can reach out to their client account lead, and we would be delighted to welcome them in, and do some, either, exploratory research into these technologies, or actually, do some longer-term innovation engine work, where we're helping to augment their capabilities. For those who, maybe, aren't an Accenture client, then, we do have open houses. We do quarterly open events, not only for potential new clients, but also, for people in the community for partners, for schools. We're really committed to helping to be an asset for San Francisco, for this community, so keep your eyes peeled for opportunities to come in. >> Yeah, that's great because last time when we were here when we opened there was a lot of conversation about being a very active participant in the community. You guys are sponsors with the Warriors at the Chase Center, but no, I think we had a number of people from the city and county of San Francisco in talking about the opportunities, and being an active, engaged member of the community beyond just a for-profit company. >> Absolutely, and the undercurrent of this year's Tech Vision, which is about to launch is all about thinking beyond the edges of your organization, and understanding the choices that you make, how they impact the communities you serve, so it's really important to us to be a good steward of that here at Accenture, and we have teammates accessible within the hub. For example, data enthesis, who can help you understand the decisions you're making around artificial intelligence. Are you using data securely? Are you using it in a way that makes people feel comfortable? So we have teammates here who can help clients consider the impact of these decisions that goes beyond the four walls, to really be a good steward for the next generation. >> Okay, well, next time I come, I'm wearing a white coat, so we can go get our hands dirty. >> I like it. >> All right, Ashley, well, again, congratulations to you and the team, and have a great evening. >> Thank you so much. >> All right, she's Ashley, I'm Jeff. You're watching theCUBE. We're at the Accenture Innovation Hub for the Technology Vision 2020. Thanks for watching, and we'll see you next time. (funky electronic music)

>>from San Francisco. It's the Cube covering Accenture Tech Vision 20 twenties Brought to you by >>Accenture. >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're at the Accenture San Francisco Innovation Hub in the 33rd floor of the Salesforce Tower in downtown San Francisco. It's 2020 the year we know everything with the benefit of hindsight. It what better way to kick off the year than they have the Accenture Tech vision reveal, which is happening later tonight. So we're really happy to have one of the authors who's really driving the whole thing. He's Michael Built the managing director of the Accenture Tech Vision. 2020. A very special edition. Michael, great to see you. Thanks for having me. Absolutely. So you've been doing this for a while? I think we heard earlier. This thing's been going on for 20 years, but you've been involved with at least the last eight a little bit more and more than that. So what's the, uh, what's kind of the big theme before we get into some of the individual? Yeah, So I >>mean, I think right now what we're really talking about is that our real big theme is this ui the digital people? And it's that recognition that says that we fundamentally changed. I mean, when you start looking at yourself in your lives, is that you've gotten to a point where you're letting your cellphone track you. You know your car knows where you are, probably better than your spouse does. You know you're handing your key to all go to Amazon and Wal Marts. They deliver packages. Your help, and more than that, is that actually, we're trying to start to revolve our lives around this technology. You know, I look at my own life and we just sold our second car specifically because we know that uber and lift exists to fill that void, >>right? Well, you don't look much further >>than than phone numbers. How many people remember anybody's phone number anymore? Right, cause you don't really have to. I >>think it's 1/15 anniversary of Google maps this year, and to think of a world without Google Maps without that kind of instant access to knowledge is is really hard to even fathom. But as you said, we're making trade offs when we use all these services and and Now, some of the costs of those things are being maybe more exposed, maybe more cuter in your face. I don't know. What would you say? >>I mean, I think what's happening now is that what we're realizing is that it's changed our relationship with is that suddenly we've actually brought them into our lives. And on one hand they're offering and have the ability to offer services that you could never really do before, you know. But on the other hand is that if I'm gonna let somebody in my life suddenly they don't have to provide. Just provide me value. And this is useful is that they actually irks people expecting them to retained their values to, you know, so how they protect your data. What they're good for the community, for the environment, for society, whether it's sustainable or not, is that suddenly whereas people used to only care about what the products are getting now, how it's built, how your company is being run, it's starting like it's just starting, you know, to become important too, >>right? Well, it's funny cause you used to talk about, you know, kind of triple bottom line shareholders, customers and your employees and you talked about really kind of this fourth line, which is the community and really being involved in the community. People care suddenly go to conferences that we spend >>a lot of time and you know, all the utensils air now compostable and the forks air compostable. And you know, a >>lot of the individual packaging stuff is going away, so people do care. >>They do. And then there's 1/4 and 1/5 that says, the your community cares, you know? But it's also your partners. Do, too, is that you can't you know, I'm going to say downgrade. You know, the idea that you're B two b folks care is that suddenly we're finding ourselves tied to these other companies, and not just in a supply chain, you know, but from everything. And so you're not in this alone in terms of how you're delivering these things. But now it's becoming a data that says the man, if my partners are going to get pummeled because they're not doing the right thing or they don't have that broad scope, is the that's going to reflect on me, too, And so now you're suddenly in this interesting position Where all of the things that we suspected we're gonna happen around digital connecting everybody is just starting to. And I think that's gonna have a lot of positive effects. >>Yep. So one of the things you talked about earlier today, earlier presentation was kind of the shift from kind of buyer and seller seller, consumer to provider and collaborator, Really kind of reflecting a very different kind of a relationship between the parties as opposed to kind of this 11 shot transactional relationship >>now And that's right. And it doesn't matter who you're talking about. This is that, You know, if you're hiring folks, you know, for skills that you're assuming that they're going to learn, you know, that's going to be different in three years and five years. You're essentially partnering with them in order to take all of you on a journey. You know, when you start talking about governments, is that you're now partnering with regulators. You know, you look at companies like Tesla who are working on, you know, regulations for electric cars. They're working on regulations around battery technology. And you see that this go it alone approaches and what you're doing? You know, Rather, it's becoming much more holistic, >>right? So we're in the innovation hub, and I think Number five of the five is really about innovation today. And you guys are driving >>innovation and you know the rest of peace. Clayton Christensen passed away. Innovator's Dilemma. My all Time favorite book The Thing I love about that book is it's smart people. Making sound decisions based on business logic and taking care of existing customers will always miss this continuous change. But you guys are really trying to help companies be innovative. What are some of the things that they that they should be thinking about besides obviously engaging with marrying the team here? And >>that's the really interesting thing is that you know, when we talk about innovation, you know, five or even 10 years ago, you were talking about just how do I find a new product or new service to bring to market? And now that's the minimum stakes like that's what everybody's doing. And I think what we're realizing as we're seeing tech become such a big part is that we all see how it's affecting the world. And a lot of times the things they're good is that there's no reason why you wouldn't look at somebody like a lifter uber and say that it's had a lot of positive effects. But from the same standpoint is that you ask questions of Is it good for public transit? It's good for city infrastructure, and those are hard questions to ask. And I think where we're really pushing now is that question that says We've got an entire generation of not tech companies. But every company that's about to get into this innovation game and what we want them to do is to look at this, not the way that the tech folks did. That says, Here's one service or one technology but rather look at it holistically. That says, How am I actually going to implement this? And what is the real effects that it's gonna have on all of these Different >>lot of unintended consequences is always >>a good, and I remember hearing years ago >>this concept of of curb management, curb management you ever thought of that will drive up and down in Manhattan when they're delivering groceries or delivering Amazon packages and FedEx packages and uber eats and delivery dog food. Now where's that stuff being staged? Now? The warehouses kind of shifted. You got into the public space, so you never kind of really know where these things they're going to end up? >>No. And I'm not saying that we're gonna be able to predict all of it. I think rather it's that starting point that says that, you know, we're starting to see a big push, you know, that says that these things need to be factored in and considered. And then similarly, it's the If you're working with them up front, it becomes less of a fault in a fight of who's fault. It is at the end, and it becomes more of a collaboration that says, How much more can we do if we're working with our cities that we're working with our employees? We're working with >>another follow up. You guys been talking about this for years? Is every company is a tech company or a digital company, depending on how you want to spin that. But as you were talking about earlier today in doing so and then converting from products to services and converting from an ongoing relationship 21 time transaction, it's not only at that point of view touch with a customer, but you've got to make a bunch of fundamental changes back in your own systems to support kind of this changing business >>models. And that's right. And I think this is going >>to become The big challenge of the generation is that we've gotten to a point where just using their existing models for you know how you interact with your customers or how you protect their data or who owns the data. All of these types of things is that they were designed back when we were doing single applications and they were loading up on your windows PC. And where we're at now is that we're starting ask questions that says Alright in this New World order why it's a fundamentally do differently, you know, And, you know, sometimes that could be You know, a simple is asking a question that says, You know, there's a consortium of pharma folks who have created a joint way for them to develop all of their search algorithms for new drugs, but they're using Blockchain, and so they're not actually sharing the data, so they do all the good things but they're pushing that. But fundamentally, that's a different way to think about it. You're not creating an entirely new infrastructure because what you're used to is just handing somebody the data on what they do with the data afterwards. It's kind of their issue and not yours. And so now we're asking big new questions to do it >>right. Another big thing that keeps coming up over and over is trust. And again, we talked little. Really? I find this really ironic situation where people don't necessarily trust the companies in terms of the people running the companies and what they're gonna do with their data. But they fundamentally trust the technology coming out of the gate and this expectation of, of course it works. Everything works on my on my mobile phone, but the two are inter related, but not equal. >>No, I mean, they're >>not. I mean, it's really pushing this idea that says the we've been looking at all of these. I'm going to say scary headlines. People are not trusting companies for the last number of years, while at the same time the adoption for the technology has been huge. But there's this dichotomy that's going on and people were at one point is the they like the tech. I think the last stat I stall is that everybody spends up to six and 1/2 hours a day involved on the Internet in their technology. But from the same standpoint is that they worry about who's using it, how and what it's done. And I think where we're at is that interesting piece that says the we're not worried about a backlash. We don't think that people are going to stop using technology. Rather, we think it's really this tech backlash that says they're not getting the value that they thought out of it, you know? Or they're seeing companies that may be using this, technologies that don't share the same values that they do. And really, what we think this becomes is the next opportunity for the next generations of service providers in order to fill that >>right. Don't forget, there was a Friendster and MySpace before there was a Facebook. Nothing lasts forever. So last question finally goes busy night. The 1st 1 was the eye and experience, and I think you know the kind of the user experience doesn't get enough light as to such a such a defining thing that doesn't move the market again. I lived in an uber right, but the uber experience compared to walking outside on a rainy day in Manhattan and hoping to nail down a cab is fundamentally different. And I would argue that it's that technology put together in this user experience that defined this kind of game changing event as opposed to, You know, it's a bunch of AP I stitch and stuff together in the back. >>That's right. And I think where we're at right now is that we're about to see the next leap. Beyond that is that you know, most of the time when we look at the experiences that we're doing today, they're one way is that people assume that, Yeah, I have your data trying to customize and whether it's a ad or buying experience or whatever. But they're pushing it as this one way street. And when we talk about putting the I back experience, it's that question of the next step to really get people both more engaged as well as to I'm going to say improve the experience. Self means that it's going to become a partnership. So you're actually going to start looking for input back and forth, you know? And it's sometimes it's going to be a simple is saying that that ad that they're pushing out is for a product that I've already bought or, you know, maybe even just tell me how you knew, You know, that that's what I was looking for. But it's sometimes that little things that back and forth is how you take something from, you know, which could be a mediocre experiences, even potentially a negative one and really turned it into something that people like. >>Yeah, well, Michael, I let you go. I know you got a busy night, and we're going to present this and ah, I really think to you and the team And congratulations for coming up with something that's a little bit more provocative than Cloud's Going to be big or mobile is going to be big or edge is going to be big. So this is a great material. And thanks for having us back. Look forward to tonight happening. >>Happy to do it. And, you know, next year will probably do it again. >>So we already know everything is 20. >>20. What else is No, A All right. Thanks again. >>Yeah,

>> From the Salesforce tower in downtown San Francisco, it's theCUBE, covering Accenture Tech Vision 2019 brought to you by Silicon Angle Media. (upbeat music) >> Hey welcome back, everybody. Jeff Frick here with theCUBE. We are in an exciting new location. Last year we covered the Accenture technology vision release 2018. It was at Minna Gallery, cool event. But this year the venue is off the hook and 33 stories high and we're really excited to be in the brand-new Accenture Innovation Hub and joining me here our first guest, John Del Santo, he is the senior managing director for the West region for Accenture and he is responsible for this beautiful five-story. So John, first off congratulations to you and the team. >> Thanks, it's been a big project opening up this place over the last year, but it's come together great. >> Yeah and this morning they had a nice ribbon cutting, all kinds of dignitaries so, you know, what does this mean in terms of kind of, you've been with the center a long time. Your presence in the Bay Area specifically, but also as part of more of this global innovation effort. >> Well I think it's this, this is bringing together all the best of Accenture that we already had in the Bay Area. We're putting it all under one roof. We're relocating everybody and we're expanding the team. So we announced 500 new technology jobs here in this location over the next year and expanding our apprentice program. But basically, it's all about bringing more talent to this location in San Francisco to do more projects with clients in this space. >> Right. So we'll get into it with some of the other folks that we have scheduled, but it's both a coworking space for the Accenture people in town and three solid floors of all kinds of labs and innovation, kind of hands-on spaces, if you will, to do this work with your clients. >> Absolutely, that co-creation, we think, is what is really differentiating us from our competitors and it's really allowing our clients to work with us and our experts, our technology experts, and the ecosystem partners that we do a ton of work with, real time to solve a problem. Brainstorm a problem, prototype it, solve it over a very short period of time. >> Yeah, I think it's a pretty unique approach that you guys have, which is imagine the future and then create the future. >> Yeah >> As opposed to just reacting to the future. And you made an interesting comment this morning about, you know, be the disrupter, not the disruptee. And my question is really, as you see the leadership at these traditional companies that are afraid of being disrupted, how are they kind of changing the way that they do things, knowing that the digital natives and the threats that they don't even see coming from a completely different direction are now bearing down, and they have to get with the program. >> Well they do have to. And then it's really our job, our purpose, you know, the talent that we have in this company's purpose is to make our clients succeed and be disrupters. Because if they're not, they will be disrupted. And so it's in our best interest to make sure we're bringin' in the best talent, pushing their thinking on ideas, and actually getting to a solution that can actually allow them to differentiate and serve their customers better. >> Right. >> So that's what we're all about, is making sure our clients are successful. >> And draggin' 'em kicking and screaming? Or are they, are they seeing-- >> Absolutely not. >> Are they seeing it in their competition? I mean, in terms of kind of that board-level discussion, where, you know, it's passe that everybody's a technology company, and everybody's doing digital disruption, but you're down in the weeds helping these people actually execute the detail. >> Yeah, well it's funny, you say everyone's a digital company, that was our big theme a few years ago at this exact event. >> Right, right. >> Absolutely, not kicking and screaming. Most executive teams, most business teams that we work with understand that they need to change. The pace of change at their business is rapid, it's faster and faster, and every year it gets faster, and so they need to actually be a lot more agile in that >> Right. >> And move quickly. >> So one of the big things in like the singularity and accelerating pace of change. And some of these big kind of macro trends that we're experiencing is that there's no single person that sees all the innovation change across this broad front, by industry, by role, etc. You guys are in a pretty unique position 'cause you actually get to see the technology innovation and the disruption and the digitization across a number of industries as well as a number of roles. So you can kind of see this big huge glacier that's moving down the valley. >> That's one of the really cool things about this particular geography and location is that literally steps from our door here on Mission Street in San Francisco, we've got clients from ten, fifteen different industries that we serve, and we can bring talent from ten or fifteen plus different industries plus the technology skills to make sure they're looking at the problem from all angles. So if it's a retailer, are they really thinking about financial services, 'cause we've got both skills here. If it's a retailer, are they thinking about platform-based selling? Do they have an omnichannel strategy? We've got the skills in this location cross-industry to help serve banks, retailers, products companies, software platform companies, etc. And I don't think you can find that anywhere else, at least in the Continental United States, given kind of where we are in our geography. >> Right. So you had a couple of special guests this morning at the ribbon cutting. You had a customer, which is great, but you also had a representative from City of San Francisco and I just want to shift gears and talk about, you know, what it is to be kind of an active member of the community. You know, the responsibility of companies we're seeing, with kind of this backlash, if you will, against some of the mega-companies out there. It's more than just taking care of your customers. It's more than just taking care of your employees and even your stockholders. But now companies are being asked to be more kind of responsible and active participants in their local community. That's always been sort of part of our ethos. It's always been part of our vision to help our clients succeed, but also to change the way the world works and lives. And therefore, we have to be really active in our communities. We're being a little bit more explicit about it lately. But it's our view that we need to be able to improve where we're working and living, 'cause our people are active and it's important that we help serve 'em. We have a very strong public service business. We serve the State of California, we serve the City and County of San Francisco as well as well as other entities in California. And it's critical for us to help improve California as we improve the businesses in California. And so it's clearly part of our mission. >> Right. The other thing I think it's interesting is kind of companies' roles with higher education. We've seen a lot of work that Accenture's doing with community colleges and, you know, it's more than just helping so that you get good talent to feed your own system, >> Right. >> But it's really, as the pace of change just continues to accelerate, you know, historical institutions aren't necessarily best-equipped to move that fast. So again, you guys are taking a much more active, you probably done it before, but more active vocal role in the local academic institutions as well. >> Absolutely, I mean, our university relationships are really, really strong, always have been. But it's always been a little selfish on our end. We're always trying to get the best talent out of the universities locally here and there's obviously great schools in the Bay Area. We want to be more engaged with those universities on projects together as well. We want more of a 360-degree relationship. We've got great examples of where we've done research with some of the universities here locally, where we've co-innovated with some of them and we want to do more of that so that there's more of a solid relationship. It's not just about us, you know, helping them find the best students to work here, >> Right. >> Which we want, (laughs) and we do every year, but making sure that we're actually involvin' them from a research perspective and any other kind of, you know, philanthropic idea that we might have together. >> Right. So big event tonight, big event this morning, >> Yeah. >> So before I let you go, it's a brand-new space, I wonder if you could share a couple fun facts for the people who haven't come to visit yet, but hopefully will come as part of a project and a co-creation about some of the cool unique features that you guys have-- >> Well some >> Built in this thing. >> Unique features in the building. First of all, there's unique features with the talent. So we have researchers here, labbers, we call 'em, from our labs, that have, you know, Accenture has thousands of patents. More than 10% of them have been actually invented here. So our inventors are a secret that we've had in Northern California for a long time and they're all based here now. We've got some really cool spaces. We've got an augmented reality room, which is basically a 360-degree room where you can, rather than having to wear virtual-reality goggles, you can actually go inside of a computer, go inside of a lab, go inside of a hospital, and get an experience that's much more hands-on and a lot more immersive, if you will, than you could any other way. We've got a maker lab where we actually are makin' stuff. So we've got a design business here where we've helped physically make not only software, we make a lot of software, everyone knows that, but we've actually made products that have embedded software in them and so there's that fabrication capability we actually have in this building as well, which is pretty unique for a high-rise. (laughs) so >> Right. No, we saw all the machines back there, >> Yup. >> Had a good tour earlier today so-- >> Oh lots of robots and toys and all that good stuff, too. >> Yeah, that's right, it's all the robot room. All right, well, John, thanks for taking a few minutes of your time. Really exciting day for you and the team, >> Yeah. >> And nothing but congratulations. >> Thank you so much. >> All right. >> Thank you, thanks for coming. >> He's John, I'm Jeff, you're watching theCUBE. We're at the brand-new Accenture Innovation Hub in downtown San Francisco in the Salesforce tower. 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 a brand newly open Salesforce Tower, the 33rd floor, the middle of the brand new Accenture Innovation Hub. We're excited to have our next guest, who's been part of the Innovation Labs and the Innovation Hubs and a lot of innovation in the center for years and years and years. You've seen him before, we're at the 30th anniversary, I think last year. All the way from Paris, is Marc Carrel-Billiard. He is the Senior Managing Director for Accenture Labs. Marc, great to see you again. >> Great to see you Jeff again as well, I'm so happy. >> So, what do you think of the new space here? >> I love it, I just love it. I saw it building and everything and now it's ready, and we open it today, I mean it's just amazing. The stairs, did you see the stairs? >> I saw the stairs, yes. >> Really amazing, everything's good there. I think it's not an office, like Paul already said, it's really something better and I think it's a tool for explaining what is innovation at Accenture at play, I mean, how we use it, how we connect the labs, we use the liquid studio, all the ventures and everything, that's great. >> Great. But now it's all brought together, right? You had a couple satellite locations in the Bay Area-- >> Yeah and I think that with the story of putting all this stuff in what we call the Innovation Center, the Innovation Hub, and so putting everything in the same building and have different floors where we can address different talking with our clients. Are we talking about research? Are we talking about more polythiophene? Are we talking about, I mean ideally, it's all about driving innovation at scale. >> Right, right. >> At scale. >> So, we're here for the technology vision-- >> We are. >> Which will be in, in a little bit and then, Paul and they team will present-- >> Yep, they will. >> Five new transfer for 2018. One of the ones they called is DARQ, D-A-R-Q, >> I know. >> Which is distributed ledger technologies, formerly known as blockchain, but we don't want to call it blockchain. AI, extended reality, which is every kind of form, extended, augmented-- >> Mix relating everything, that's right. >> And quantum computer. >> You bet. >> So, from the labs point of view, from an Accenture kind of innovation looking forward, inventing the future, as you like to say, which I think is a great tagline, what are some of your priorities going forward, now that you got this great new space? Which is one of what I think 11 in the United States, right? >> So, my priorities are all of them, I mean, all of the above! Because I was like, do you remember at the time we were talking about SMAC? Like Social Mobility, there was analytics and cloud. I would say that DARQ is the new SMAC. So, we saw that basically, that technology has evolved and, from analytics, we'd like more AI work and everything, but it's still being combined and everything. You can still think about social media, collaborative stuff, we going to go through immersive reality where we going to continue collaborating. Think about cloud. I mean, just like cloud will bring you height, throughput computing power through the cloud. Well, I mean, also quantum computing can give you like amazing capability in terms of computing power. So I would say probably, like, DARQ is a new SMAC and so the lab has been working on it since, I would say, not since day one, but at the very beginning. And so, well obviously distributed ledger, you know that we have a lab in Sophia Antipolis, they're really spending a lot of time in the blockchains. So there's a couple of things that we're doing. I give you a couple of ideas. One is, maybe people talk about blockchains, and there's bunch of blockchains all over, there's like blockchains for manufacturing, there's blockchains for trade finance, there's blockchains for this and that. Problem is there's no very good interoperability between those blockchains. One thing that the lab is going to be working is how we can interoperate between those different blockchains. So you are basically a supply chain, you want to connect to a financial organization, how their blockchain will connect to your blockchain. Number one. The second thing we're going to be working on is the SMAC contract. The lab believes the SMAC contract is not smart enough. So we going to add more artificial intelligence in the SMAC contract to see what we could do better. Think about this SMAC contract as a stock procedure in database. How we make those stock procedure a little bit better. I mean, it's just analogy type of thing. >> Obviously, the blockchain conversation, any kind of demo, talking about DHL-- >> Yeah, DHL, exactly. >> But is that logistics, that merchandise move through their system, as you said, there's a lot of different touch points with a lot of different systems. So it's not an aggregated system, it's a problem, and the other thing is you don't necessarily need all the data for each person, >> You don't. >> Or transaction all along the line, right? >> You're absolutely right. And I talk about interoperability between blockchains, but there's going to be also interoperability between the blockchain that you're implementing and the legacy environment that you have. And this needs to be addressed as well. So lot of thinking about blockchains, I've always said for me that blockchain is the digital right management of your future. That kind of protocol, and we're working with companies that are basically creating movies and stuff like that, and how we leverage blockchain to change those movies between different parties. I mean, there's going to be a lot of cool stuff that we're going to be able to do. So that's blockchain. The D for distributed ledger. A for artificial intelligence. So artificial intelligence obviously is something very beginner labs. We have three labs that are delegated to artificial intelligence. >> Three? >> Yup, out of seven. One here, San Francisco. The other one in Bangalore, and the third one in Dublin, Ireland. And each of them are covering a little part of the things that we want to do with artificial intelligence. It's all about accelerating the artificial intelligence, so how we're going to think about new infrastructure, a new way of doing machine learning, using weak labeling, it's all about explainable AI, how you're going to connect the knowledge graph with machine learning, so that's the probabilistic model will give you an explanation of why they've decided to select this picture, or this information and so forth. And basically the other things we're going to be working on, artificial intelligence, is that human-machine interaction, and one thing that we want to address is what we call the conversational aspect of virtual agents. If you look at virtual agents today, voice comment type of things. >> Right, right. >> You can't really engage in a conversation. I want to look at that. How they're going to understand context, and how you're going to be exchanging better, and how you're going to flow a better conversation with that. One thing that's going to be very important in everything that we're doing is going back to semantic network, knowledge management, knowledge graph. How we combine knowledge graph with all these machine learning capabilities. That's artificial intelligence in the lab. >> Then you get, we'll just work down the list, right, then you've got the extended reality. >> Extended reality. >> So whatever kind of reality it is. >> So we're going to continue doing a lot of stuff for extended reality, immersive learning, we're going to use that, I think what's going to be important for us is that not to look at extended reality just from a vision standpoint, but try to use the combinatorial effect of every immersive sense that you have. So like, basically, hearing, also, smelling, touching the aptic, and how you combine all those senses to change completely, not the vision, but the experience. What you really feel. In fact, if you go to this Innovation Hub, I don't know if you've seen that we have an igloo-- >> We did, I saw the 360. >> That's right the 360, to try to immerse you already in some quantum computing experience, I think it's a good segue way also for quantum. So quantum, is that we've been doing a lot of progress with quantum too, you know, two years ago we started already to work with D-wave and then we have work with this company called 1QBit, so we build a software, so we use their software development kit, to program the quantum computer, and then we work with Biogen to do drug discovery, and changing the way you do that, by accelerating that through quantum computing. But we've continued, we've announced basically some partnership with IBM to look at their platform, we're continuing working with other interesting platform like Fujitsu, their Digital Annealer, and so forth, and what we want to do is that Accenture is very, very agnostic related to all those vendors. What we want to do is that we want to understand more about how you program those different architecture, how you see what type of problems they can solve, and how based you can program them. And so if we use the Abstraction Layer on top of all the others, and we can program on top of that, this is really cool, this is exactly what we want to do. >> So how close is it? How close is it to getting the production ready? I mean, you got it in the new vision for 2019, I mean, what are people just playing with it or is it ready for prime-time. >> No, no, no. >> Where is it these days? >> So first of all, DARQ stuff, all the people, all of our clients-- >> I mean quantum specifically. >> Okay quantum-specific. I think we're talking about three to five years to start to have real solutions. Right now, we have prototype, but we're moving to more pilot, and I think the solution will come soon. Probably in five years time, we're starting to ascend soon. Let me give you another idea. >> So the order of magnitude difference in the way that you can compute, the AI. >> Exactly, and I think that's going to change the game. It's going to change the game on everything. Let me give you maybe a last example that I'm sure you're going to love. And it's all about optimization matchmaking. Our tech vision this year is all about hyper-personalization, plus on-demand delivery, and so that's how at the moment, you know, you're going to change the game. The momentary moment. How you're going to change the reality of people. What you're going to be able to do. I'm going to tell you that, where we're going to use quantum computing. We're going to use quantum computing to do a better matchmaking between a person who is waiting for an organ and an organ that you can transplant to this person. And the moment is the accident that happens on the street. There's going to be someone basically dying on the street, so someone dead and then you need, basically, to get this organ, it could be a kidney, for example, every organs have a time-lapse that you can use basically to transport that to someone else. Now the question is that you have the organ, it's in basically an ice-cubed environment-like box, and then you transplant that to someone, you have like few hours to figure out who are the best receiver. And this is hyper-personalization, because you need to understand the variable of all the body that is going to receive that but all the variables of the organ, until now is all main front to do the matchmaking. We're rethinking that using quantum computing. >> It's just wild, you know, what the cloud really enabled to concept. If you had infinite compute, infinite store, and infinite networking, at basically free, asymptotically approaching free, what would you build? And that's a very different way to think about problems. >> Not only will we build some amazing things, but I think we would change the reality of every people. Every people will have their own reality that they could use product and service the way they want it, and this will be a completely different, not a world, but a game set, that would be completely different. >> Marc, we're almost out of time, but I just want to ask you about Pierre, former CEO of Accenture passed away recently, and I was really struck by the linked investors. So many people, you know, I follow you, I follow Paul, a lot of people posted, what a special man, and what an impact he had, sounds really personally with most of the leadership here in Accenture. I was wondering if you could share a few thoughts. >> Well obviously, I mean, everyone's been very sad that we lost Pierre. I mean, he was just an amazing person. He was really a role model, not only in business, but in life. And he was so fun about fun of innovations, he loved the labs, he loved what we could do in it, I think he was really thinking about better future for the people, better future for the world, and everything, and it was really amazing for that. Everyone was struck really to see that. But I think there was so many testimonials pouring from our people, but what I was even more amazed was our clients. He really moved clients. And his visions is an amazing legacy for Accenture, and we're going to, I mean, this is so precious what he left us and I think that I really want the lab, every day that we're inventing something, I'm always thinking about Pierre and what he would have thought about these things. He was always enthusiastic reading our research paper and everything, so definitely the lab's going to continue to innovate, and I hope that Pierre, wherever he is, will be watching. >> I'm sure he's smiling down. >> And will be happy with that. >> Alright, well Marc, thanks a lot for taking a few minutes and congratulations on this continual evolution of what you guys are doing with labs and Innovation Centers, and now the Innovation Hub here in downtown San Francisco. >> Thanks, Jeff. >> Alright. He's Marc, I'm Jeff, you're watching theCUBE. We're at downtown San Francisco at the Accenture Innovation Hub as part of the Accenture Technology Vision 2019 presentation. Thanks for watching. See you next time. (light electro music)

>> From the Salesforce Tower in downtown San Francisco, it's theCUBE, covering Accenture Tech Vision 2019. Brought to you by SiliconANGLE Media. (upbeat techno music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are live in downtown San Francisco, the Salesforce office in the brand new Accenture Innovation Hub. It's the grand opening, like I say the soft opening, but we had the ribbon cutting, we're presenting the Accenture Technology Vision 2019 and we're excited to have somebody who's not a technologist who's very important to technology, she's Doctor Rumman Chowdhury, she's the Global Lead For Responsible AI at Accenture. >> I am. >> Great to see you. >> Thank you for having me on your program. >> Absolutely. So I was doing some background research on you and I love you introduce a lot of your talks about the fact that you're not a technologist, you come at this from a very, very different point of view. >> I do. So I am a social scientist by background. I've been working as a data scientist in artificial intelligence for some years but I'm not a computer scientist by trade. I come more from a stats background, which gives me a different perspective. So when I think of AI or data science, I literally think of it as information about people meant to understand trends in human behavior. >> So there's so many issues around responsible AI. We can talk, probably, to all these people, go on above, you know. >> Yeah. >> We don't have too much... And the first one is really a lot in the news right now, about AI is simply a codification of existing biases often, unless you really take a very proactive stance to make sure you're not just codifying biases in software. What are you seeing? >> Absolutely. So we really have to think about two kinds of bias. There's one that comes from our data, from our models. This can mean incomplete data, poorly trained models. But the second one to think about is you can have great data and a perfect model but we come from an imperfect world. We know that the world is not a fair place, some people just get a poor lot in life. We don't want to codify that into our systems and processes, so as we think about ethics and AI it's not just about improving the technology, it's about improving the society behind the technology. >> Right. >> Yeah. Another big topic I think that's really important is if you're doing a project and you want to think through some of the ethical issues, should we be collecting this data, why are we collecting this data, why are we running these algorithms and you make a decision it's for a particular person, purpose and the value outweighs the cost. But I think where the challenge really comes into is the next people that use that data or the next use that you don't necessarily have in mind and I think we hear that a lot in terms of kind of the complaints about the current state of big tech, where everyone is doing their little piece. >> Right. >> But what happens over time as those get rolled into maybe bigger pieces that weren't necessarily what they were starting with in the first place. >> Right. >> Absolutely, it's something I called moral outsourcing. Because what we build is often, we feel like a cog in a machine, we feel sometimes as technologists people aren't willing to take the responsibility for their actions, even though we should be. If we build something that is fundamentally unethical, we need to stop and ask ourselves, just because we can doesn't mean we should. >> Right. >> And think about the implications on society. Right now there's often not enough accountability because everybody feels like they're contributing to this larger machine, who am I to question it and the system will crush me anyway. So we need to empower people to be able to speak their minds and have an ethical conscience. >> So I'm curious in term of the reception of your message when you're talking to clients because clearly there's a lot of pressure to innovate fast. Everyone is telling everybody that data's the new oil and we've got to leverage these micro-experiences, et cetera, et cetera, et cetera. And they don't necessarily take a minute to step back and reflect >> Right. >> Is this the right thing, is this the right way? Are we collecting more data than we really need to achieve the objective? So how receptive are companies to your message? Do they get it? Do they have >> Yeah. >> To get hit upside the head with some problem before they really understand the value? >> So I'll give you a phrase that everybody understands and then they get the point of ethics in AI. Brakes help a car go faster. If we have the right kinds of guard rails, warning mechanisms, systems, to tell us if something is going to derail or get out of control, we feel more comfortable taking risks. So think about driving on the freeway. Because you know you can stop your car if the car in front of you stops abruptly, you feel comfortable driving 90 miles an hour. If you could not stop your car, nobody would go faster than 15. So I actually think of ethics and AI are an ethical implementation of technology as a way of helping companies be more innovative. It sounds contradictory but it actually works very well. If I know where my safe space is, I'm more capable of making true innovations. >> Right. So I want to get your take on another kind of topic, which is really kind of STEM education versus not STEM, or ethics. >> Right. >> And it's interesting, huge push on STEM, it's very, very important thing that's going on now. But as you look not that far down the road, and this events all about looking down the future, reinventing the future. As more and more of those kind of engineering functions are taken over by the machines >> Right. >> It seems like where the void is is really more talking about what are the implications, what are the deeper questions we should be asking, what are the ethics and the moral questions before just building a better mousetrap. >> Right. So you're raising a very hot button issue in the ethics and AI space. Is it simply enough to say all technologists should take an ethics course? I think it is very important to have an interdisciplinary education but, no, I don't think one ethics course, taken out of context in college will help you. So I think that there's a few things to think about. One is that corporations need to have an ethical culture. It needs to be a good thing to be ethical, number one. Number two, we need interdisciplinary teams. Often technologists will say, and rightfully so, "How was I supposed to know thing X would happen?" It's something very specific to a neighborhood or a country or a socio-economic group. And that's absolutely true. So what you should do is bring in a local community, the ACLU, some sort of a regional expert. So we do also need to move towards creating interdisciplinary teams. >> Right. So you brought up another really cool thing I think in one of your talks, FAITH. Fairness, Accountability, Transparency and Explainability >> Yes. >> Which is a, you know nobody likes black box algorithms. >> Yep. >> But fairness, specifically, is such an interesting concept. We all feel very slighted if we perceive things not to be fair. >> Yes. >> The reality is life is not fair, a lot of things are not fair. So as people try to incorporate some of these things into the way they do business, how can they do a better job, what are some of the things they should be thinking about >> Yeah. >> So they can have the faith? >> Fairness is a very complicated, complex thing and I invite you, or whenever someone asks, "What does it mean to be fair?" I point them towards this really great talk from this conference called Fat Star and it's called, 21 Definitions of Fairness. And it's all these different ways in which we can quantify and measure the concept of fairness. Well at Accenture, we took that talk and some other papers and created something called the Fairness Tool. So it's a tool to help guide discussion and show solutions on algorithmic bias and fairness. Now, the way we think about it is not as a decision maker but a decision enabler. So how can you communicate as a data scientist to a non-technical person to explain the potential flaws and problems and then take collective action? So the algorithm can help you make that decision but it's not automating the decision for you. So what it does is it helps smooth conversation and helps pinpoint where there might be bias or unfairness in your algorithm. >> Right. Well we don't have time tonight but another time we're going to >> Sure. >> Dig deeper into this and all the biomechanics and bioengineering >> Yes. >> And a lot of great topics that you've covered in a number of your talks. So I really enjoy getting to meet you and you do terrific work, really enjoy it. >> Thank you, thank you very much. >> Alright, thank you. She's Rumman, I'm Jeff, you're watching theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco. Thanks for watching, see you next time. (upbeat techno 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)

>> Hey welcome back everybody, Jeff Frick here, with theCUBE. We're at the Accenture Technology Vision 2018, it's actually the preview event, a couple of days before the report comes out. We came last year, it's really Accenture querying all their customers and partners, as to what are the hot topics for 2018? We're excited to have a return, from Accenture Labs, he's Marc Carrel-Billiard, the Global Lead for Accenture Labs. Last we saw you at the 30th anniversary. So, Marc, great to see you. >> Great to see you too, very happy to be here. >> Absolutely, and we saw you a year ago at this event as well. So, as you look at this Vision compared to last year's Vision, what really jumps out at you as being so different? >> I think what really jumps is just the fact that what we say here is that, you remember last year, it was all about technology for people, technology by people. What we see is that we move forward into, not just technology for people, by people, but how technology basically is shaping the society. And what people, basically I mean, like technology is changing their life, the way they work and everything. What we say to all this technology is that they're going to be a major impact in the society itself, and then companies need to work with people, need to work with society basically to change, basically, the new models. What we say also is that, something which is very important is that there's a transparency that needs to be brought out by this technology. I mean, it's like if you look at companies and everything they will have to build a social contract with these people. Bring in the technology. It's a two-way street now. >> Right, right. >> Like, you build a lot of technology, and people adopt this technology, and then need to bring back feedback. So what are you going to do about it? And it's not going to be about selling products, selling services, but building partnership. Partnership with the people, partnership to the society that you're going to build around them. That's very important. >> But it's kind of weird, because it's kind of bifurcated. On one hand, there's a personal level of connection that you've never had before. On the other hand, we're trying to automate, with software and data, as many processes as we can, which we've seen in Martek, probably on the cutting edge of that. And that sometimes can cause issues. So we're kind of bifurcating. Automate as much as you can, on the other hand, there's a personal touch and trust and a relationship that I never had before. >> I love this discussion, because I'll tell you this, I completely agree. But I think that people need to recognize that artificial intelligence, we've made tons of progress there. And you remember, we had so many winters along the way and everything. I think there will still be winters for artificial intelligence. Machines can do things very very well. >> Jeff: Right. >> But they still can't do what people can do. You know, for example, common sense learning. It's very difficult to explain to a machine what is common sense learning. You know what is common sense. For example, if I would like to build a robot that comes in your office, and picks, for example, a cup of coffee, and decide whether they want to throw it in the bin or basically reserve it for you, it's very difficult. You need to weigh the cup of coffee. You need to understand if it's warm or not warm. I mean, there's so many things that come to play. A robot would not be able to do that. You can do that, even your kids could do that. >> Pretty interesting. >> I know! >> So there's like five big things, I want to jump into a couple with you. One is, and you guys have twisted kind of common phrases-- >> We did, yeah >> A little bit of Accenture branding, of course, right? So one of them is the Internet of Thinking. So rather than the Internet of Things, which is very popular, and then, of course, we hear about the industrial Internet of Things. You talked about the Internet of Thinking. What do you mean by that? >> Okay, so Internet of Thinking is all about to recognize that every product in the world today will be very intelligent. We talk about artificial intelligence. We're baking the intelligence into systems. They all have matched learning, they all learn about what you're doing. So what we need to do is that, when we're going to build a new environment and everything, we need to understand exactly where all the processing power for this intelligence going to be sitting. Is it going to be, for example, if you have to reinvent the car of the future, where it's going to be driverless. You need to re-think about the cockpit of the future and the experience. There needs to be a lot of matched learning, intelligence, to understand exactly how they want to interact with you. Should sudoers sudo-vise? To recognizing your face when you're frowning, and stuff like that. I mean there's going to be so many things, so there's lot of processing power to put. Where do you put all this processing power? In the chip in the car? >> Right. >> Do you want to split it between the chip in the car and some other chip in the cloud? Where do you put all the data related to what you're going to be doing in this car? You want to look at all these data only in the platform in the car or you want to put a little bit in the cloud so you're going to be able to crunch all the data? You going to be sitting in a seat. American people spend on average, 500 hours per year in the car. Can you imagine what we can do there? Imagine we have sensors in the seats. We're going to be able to collect a lot of data about your wellness your well-being and everything. We want to make you more healthy. What are we going to do with all this data? Are we going to crunch the data basically in the car? Or in the cloud? So, what we want to say is that the Internet of Things is going to evolve to Internet of Thinking because we're going to have to be smarter. Not only to implement smart product in the car or something else, but to decide about our fixture. Where are we going to put all that stuff? Which process are we going to use? CPU, FPGA, GPU, even quantum computing? People need to think about where they're going to put the architecture. What type of flavor of architecture they want to have. All these things need to come into play. >> I know, I know! >> Marc we could go and go and go, unfortunately we're getting the hook, they're going to start their program so maybe we'll get you back after the program. >> Sure. >> Thanks for taking a few minutes, they're going to start the program behind us. I'm Jeff Frick, he's Marc, you're watching theCUBE at the Accenture Technology Vision 2018. We'll be right back after the presentation. >> Alright, sure. >> Thanks Marc. Alright, welcome back everybody! We are still the Accenture Tech Vision 2018 free event, the autonomous band is playing, very loudly. But it's good. So we've got Marc back, Marc Carrel-Billiard, and again he is Accenture Labs' Global Lead and he is also all on top of Extended Reality. >> Extended Reality. >> So Marc, we could talk about OR, VR, AR. >> Optics, olfactives, everything. >> Now it's ER? >> That's right. >> Extended reality. >> Extended reality's VR, I mean it's like, I think it takes every type of sensors or immersion, feeling and everything you can have because it's all about combinatory effect. If I combine the augmented reality with the audio, as well with the smell, as well as with the touch then you feel that something is happening. In fact-- >> How long until you just pass all the sensors and just go right to the wires? That's what I'm waiting for. (laughing) These things are not built to look at googles, right? >> I know, I know, I know. But it's coming. >> It's coming but what's interesting though, you guys put a play on it about distance. >> Marc: That's right. >> You guys are, you're positioning this as really a way to break down distance. >> Absolutely, I mean-- >> Jeff: How does that work? >> Well, we call that the end of distance because I think the feeling that we have is that what you're going to be doing is that, you know what I mean it's always the same stuff that you're looking for talent. You're looking for skill. You're looking for people. You're looking for information. Here. Where it's out there. How how are you going to bridge that? How are you going to reduce the distance? To bring people to you, to bring the skills you need, to build the information you need. Extended reality, virtual reality, that can help you out to do that. I'll give you an example, Komatsu, it's a Japanese company. >> Big tractors and things. >> That's right, big tractors and everything. Sometimes, I mean it's a lot of investment and everything, you want to try them out, you want to test them, but it's snowing, it's pouring, it's raining. You're not going to do it. What are you going to do? Why, you're going to use the vehicle a bit in virtual >> They're all autonomous though, and they all drive themselves around. >> But not now, there's some not there. But eventually you can use that in your office. You're going to be training in your office and when it stops raining, basically you're going to be there and you're going to be able to drive that and you're going to be able to use them. We see that in the oil and gas industry. We are building very complex platforms. It takes 10 years to build them, maybe less. The question is that, do you want to wait for five years, 10 years until the platform is delivered, to start training your people? No. I'm going to bring basically that to them directly. It's not only end of distance, it's end of time. I can reduce the time that this stuff is delivered, virtually, to train the people onboard and when they're going to be there. So they're going to be using virtual reality, to be trained on the platform, and then when they're going to be on the platform, they know how it works. But even more, then you go to augmented reality, When they can do maintenance on equipment by augmenting information, to make them more efficient. >> So what's the killer app going to be? Is it a killer app problem? Is it a hardware problem, right, we're still wearing the clunky goggles. What's the breakthrough? >> So the breakthrough is really new devices because right now, if you look at the market today in AR, VR, we're talking about $14 billion, one-four. The billion dollars-- >> Today? >> Yeah, today. Which is a lot. >> Yeah, it's a real number. >> But most of it is on the devices. Most of it is on gaming devices. You know, the stuff that you find on Xbox, the stuff that you find on the PlayStation, very consumer-driven. The big business is really enterprise business which is how you're going to use these devices in oil and gas industry, in automotive industry, in very toxic environments. Where the device needs to be lightweight, with long battery-life, it needs to be intrinsically safe as well. Safe in the-- >> Jeff: Environment, right. >> The devices are coming, and then by 2020 the estimate is that, that whole business is going to shift from $14 billion to $143, one forty three. >> By 2020? >> Yeah. >> Two years from now? That's right, two-three years, because the devices are there. And then, right now 70% of this business is consumer-driven, and 30% is enterprise. We're going to flip that. 70% is going to be enterprise, and 30% will be consumer. >> In 2020? >> Yes. >> Just right around the corner. >> Right around the corner. I mean, I met with a couple of companies, this company called RealWear, they doing amazing device. It's a device you wear, you can put that on the helmet, very very light. You can drop it from 10 meters, it bounce back. It works. And then basically you have bots with cognition in the very noisy environment, like this one, you can speak, you recognize everything. It can provide you with augmented reality information about what you need to do and everything. That's the typical device that we need. You can use it in toxic environments. It has other certification. I mean it's IPv6 and everything, you can run on it and it doesn't do anything, and that's exactly what we need to develop the new use case, that's going to drive these further. >> Yeah, cause we're still a long way from there but two years is not very long, >> It's not long. >> for the devices. >> I mean, it's acceleration. >> Right, right. Alright Marc, well we're excited. What's your favorite AR-VR-ER application? >> You and I, we go to Venice tomorrow, always virtual reality, and so with the combination of the olfactive, the sound, the sun and everything. You can be sitting there on the terrace, you can hear the Vaporetto passing by, you eat the bread, and I fake your brain with the olfactive stuff, you believe it's a pizza, and you drink the water and it's Chianti. That's what it's going to be. >> See I think the device is going to be when it plugs into your head. Again, avoid all these things and go straight in. And then it begs the question, did you really do it? >> I know, I know. Or not? That's way deep, we don't have time Marc. >> It was great to see you. >> Thanks for stopping by. He's Marc, I'm Jeff, you're watching theCube, Accenture Technology Vision preview party, thanks for watching. (bright music)