(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're at the Accenture San Francisco Innovation Hub on the 33rd floor of the Sales Force Tower in downtown San Francisco. It's 2020, the year we know everything with the benefit of hindsight. And what better way to kick off the year than to 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 Blitz, the managing director of the Accenture Tech Vision 2020, a very special edition. Michael, great to see you. >> Hey, 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? >> It is. >> You've been involved for at least the last eight. >> Michael: I think a little bit more than that. >> More than that, so what's kind of the big theme before we get into some of the individual items? >> Yeah, so I mean, I think right now, what we're really talking about is that our real big theme is this: We the digital people. And it's that recognition that says that we've fundamentally changed. When you start looking at yourself and your lives, it's that you've gotten to a point where you're letting your cell phone track you. Your car knows where you are probably better than your spouse does. You're handing your key to Amazon and Walmart so they can deliver packages in your house. And more than that is that actually, we're trying to start to revolve our lives around this technology. I look at my own life, and we just sold our second car, specifically because we know that Uber and Lyft exist to fill that void. >> Right, well you don't have to look much further than phone numbers. How many people remember anybody's phone number anymore, right, 'cause you don't really have to. I think it's the 15th anniversary of Google Maps. >> Michael: Yep. >> This year, and to think of a world without Google Maps, without that kind of instant access to knowledge, is really hard to even fathom. But as you said, we're making trade-offs when we use all these services, and now, some of the costs of those things are being maybe more exposed? Maybe more cute or in your face? I don't know, what would you say? >> Yeah, I mean, I think what's happening now is that what we're realizing is that it's changed our relationship with companies. 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. But on the other hand is that, if I'm going to let somebody in my life, suddenly they don't have to just provide me value and this is useful, is that they actually, people are expecting them to retain their values, too. 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 product you're getting, now how it's built and how your company's being run is starting, it's just starting to become important, too. >> Right, well it's funny, 'cause you used to talk about kind of triple bottom line, shareholders, customers and your employees. And you talked about, really, this kind of fourth line, which is community and really being involved in the community. People care, suddenly you go to conferences where we spend a lot of time all the utensils are now compostable and the forks are compostable. And a lot of the individual packaging stuff is going away. So people do care. >> They do, and there's a fourth and a fifth. It says that your community cares, but your partners do, too. Is that you can't, I'm going to say, downgrade the idea that your B2B folks care is that suddenly, we're finding ourselves tied to these other companies, and not just in a supply chain, 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 matter that says, Well, 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, 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 were going to happen around digital connecting everybody is just starting to, and I think that's going to have a lot of positive effects. >> Yeah, so one of the things you talked about earlier today, in an earlier presentation was kind of the shift from kind of buyer and seller, seller and consumer, to provider and collaborator. Really kind of reflecting a very different kind of a relationship between the parties as opposed to this one-shot transactional relationship. >> No, and that's right, and it doesn't matter who you're talking about, is that, if you're hiring folks for skills that you're assuming that they're going to learn, that's going to be different in three years, in five years, you're essentially partnering with them in order to take all of you on a journey. When you start talking about governments, is that you're now partnering with regulators. You look at companies like Tesla, who are working on regulations for electric cars, they're working on regulations around battery technology. And you see that this go-it-alone approach isn't what you're doing. 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. >> Michael: It is. >> And you guys are driving innovation. And, rest in peace, Clayton Christensen passed away, Innovator's Dilemma, my all-time favorite book. But the thing I love about that book is that smart people making sound decisions based on business logic and taking care of existing customers will always miss discontinuous change. But you guys are really trying to help big companies be innovative. What are some of the things that they should be thinking about, besides, obviously, engaging with Mary and the team here at Innovation Hub? >> Yeah, no, and that's the really interesting thing is that when we talked about innovation, you know, five or even 10 years ago, you were talking about, just: How do I find a new product or a 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 that things are good is that there's no reason why you wouldn't look at somebody like a Lyft or 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 is 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 going to have on all of these different aspects? >> Right, Law of Unintended Consequences is always a good one. >> Michael: It is. >> And I remember hearing years ago of this concept of curb management. I'm like, Curb management, who ever thought of that? Well, drive up and down in Manhattan when they're delivering groceries or delivering Amazon packages and FedEx packages and UberEats and delivery dog food now. Where is that stuff being staged now that the warehouse has kind of shifted out into the public space? So, you never kind of really know where these things are going to end up. >> No, and I'm not saying that we're going to be able to predict all of it. I think, rather, it's that starting point that says that we're starting to see a big push that says that these things need to be factored and considered. And then, similarly, it's the, if you're working with them up-front, it becomes less of a fault, on a fight of whose 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, if we're working with our employees, if we're working with our customers? >> Right, now another follow up, you guys've 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 it earlier today, in doing so and in converting from products to service, and converting from an ongoing relationship to a one-time transaction, it's not only at that point of 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 model. >> Now, 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 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 to ask questions that says, All right, in this new world, what do I have to fundamentally do differently? And sometimes that can be as simple as 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 block chain, and so they're not actually sharing the data. So they do all the good things, but they're pushing that up. But fundamentally, that's a different way to think about it. You're now creating an entirely new infrastructure because what you're used to is just handing somebody the data, and what they do with the data afterwards is 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 a little earlier. But 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 going to 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 mobile phone. But the two are related, but not equal. >> Michael: No, I mean, they're not, I mean, and it's really pushing this idea that says we've been looking at all these, I'm going to say scary headlines, of people not trusting companies for the last number of years, while at the same time, the adoption for the technology has been huge. So there's this dichotomy that's going on in people, where at one point, they like the tech. You know, I think the last stat I saw is that everybody spends up to six-and-a-half hours a day involved on the internet, in their technology. But from the same standpoint is that they worry about who's using it and how and what is going to be done. And I think where we're at is that interesting piece that says we're not worried about a tech lash. We don't think that people are going to stop using technology. Rather, we think it's really this tech clash that says they're not getting the value that they thought out of it, 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 gap. >> Right, yeah, don't forget there was a Friendster and a MySpace before there was a Facebook. >> Yeah, there was. >> So, nothing lasts forever. So, last question before I let you go, it's a busy night. The first one was the I in experience, and I think kind of the user experience doesn't get enough light as to such a defining thing that does move the market if, again, I love to pick on Uber, but the Uber experience compared to walking outside on a rainy day in Manhattan and hoping to hail 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 it's a bunch of APIs stitching stuff together in the back. >> No, 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, 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, I'm trying to customize. And whether it's an ad or a buying experience or whatever, but they're pushing it as this one-way street, and when we talk about putting the I back in 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 itself, means that it's going to become a partnership. So you're actually going to start looking for input back and forth, and it's sometimes going to be as simple as 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 that that's what I was looking for. But it's sometimes that little things, the back and forth, is how you take something from, what can be a mediocre experience, even potentially a negative one, and really turn it into something that people like. >> Yeah, well, Michael, I'll let you go. I know you got a busy night, we're going to present this. And really thankful 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's going to be big, or Edge is going to be big. So this is great material, and thanks for having us back. Look forward to tonight. >> No, happy to do it, and next year we'll probably do it again. >> [Jeff\ I don't know, we already know everything, it's 2020, what else is unknown? >> Everything's going to change. >> All right, thanks again. (upbeat 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'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)

>>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,

>> 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)

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