 Applied from Las Vegas, it's theCUBE, covering AWS Executive Summit, brought to you by Accenture. Everyone to the Accenture Executive Summit here at AWS re-invent. I'm your host, Rebecca Knight. I'm joined by John Matchett. He is the Managing Director, Applied Intelligence North America at Accenture. Thank you so much for coming on theCUBE. Yeah, great, it's awesome. So we're going to have a fun conversation about AI today. We tend to think of AI as this futuristic Star Trek Jetsons kind of thing, but in fact AI is happening here and now. Yeah, it's all around us. What I think is interesting is how it just sort of bled into the fabric of our lives without really even knowing about it. I mean, just to get here, I mean, a lot of us took an Uber, so there's AI in the route navigation. We may have listened to Spotify and there's AI in the recommendation engine. And if you want to check the weather with Alexa, there's a lot of AI just in the natural language processing and none of that was really possible 10 years ago. So without even trying, you just wake up and AI is sort of like in your system, in your blood. So as consumers, we deal with AI every day, but businesses are also using AI and it's already having an impact. Yeah, oh yeah. I think what is absolutely true and really interesting is that information is just the new basis of competition. Like companies used to compete with physical objects and like better cars and blenders and stereos and thermometers. But today, you know, they're all like on a device and so information is how they compete. And what's interesting to me about that for our clients is that if you have a good idea, you can probably do it. And so you're limited really by your own imagination. And so I just as an example of like how things are playing out, a lot of our clients are in the pharma space to make better drugs. And every pharma company I know of is using some sort of machine learning or AI to create better pharmaceuticals, the big ones, but also the new entrance. One of the companies that we follow, Numerate, really interesting company, what they've been able to do is like ingest just a massive amount of data, like all data, like good data, bad, you know, bias, unbiased. And when it's ingesting this kind of data, the data is about... It's about like drug efficacy, human health, the human genome, like doctors visits, like you could all this diverse information. And historically, if you put all that data together, you just have a way to actually examine it. There was no way that it was too much. Humans can't deal with it, but machine learning can. And so we just all this data, and we let the robots decide sort of what's meaningful. And what's happened is you can now deal with, instead of just a very fraction of that data, but all of it, and the result in pharmaceuticals is we're able to come up with new HIV drugs in six months. And it used to be years and millions of dollars, tens of millions of dollars, but now it's months. And so it's really changing the way humans live and certainly the associated industries that are producing the drugs. So it's, as you said, AI is already being used to reimagine medicine. So many of the high tech jobs openings today are not necessarily in technology. They're in pharmaceuticals and automotives. And these involve artificial intelligence. They're skills in artificial intelligence. What can you tell us about how AI is having an impact in that sense? What I think, this is a really good question. What is interesting is that industries you wouldn't think are digital companies are now actually digital competitors. I'll give you two examples. One is a lot of our clients make liquefied natural gas. Now that is a mucky business. It's full of science, like geology and chemistry and chemical engineering. And they work with these small refineries. But the question is how are you going to get better if you make LNG? And so what they do is they use AI. And the way they do that is they have these small refineries, each piece of equipment has a sensor on it. So there might be 5,000 sensors and each sensor has three or four bots looking at it. And one might be looking at vibration and heat. And what they're doing is they're making predictions, millions of predictions every day about whether quality is good, the machine is about to have a problem, safety is jeopardized, something like that. So you've gone from a place where the best competitors were chemists to the best competitors are actually using machine learning to make the plants work better. Another industry we see that's really just brewing. You don't think, no one would think brewing is like a digital business. Because beer, the Egyptians made beer, right? Like so everyone knows how to do it. But think about it, if you make beer, like how are you going to get better? And again, the way you do it is you begin to touch customers more effectively with better digital marketing, AI to target, to understand who your best customers are, how to make offers to them, how to price, how to come up with new product introduction and even how to formulate new brands of beer that might appeal to different segments of society. So brewing, like they're all about ML and AI and they really are like a digital competitor these days which I think is interesting. Like no one would have thought about that as they were like consuming beer on a Friday with their friends. And craft brewing is so hot right now. I mean, it is one of those things. As you said, it is attracting new different kinds of segments of customers. Right, and so the question is like if you are a craft brew or like how do you go find the people that you want? So what we're doing is we have new digital ways to go touch them. We can create a very personalized offer. Like if you like running, we can give you an offer like fun run followed by a brew. And we know who you are, what you like, what your friends like to do and get very specific as we examine the segments of society to do very personal marketing that's actually fun. Like it gives you things to go do. We did one event where we looked at companies and we had a beer tasting with barbecue instruction. So if you want to learn how to cook barbecue and also do a beer tasting. So now you can get 20 people together and you have a social experience and you buy more of the product. But what's interesting is like well how do you find those people, how do you reach them, how do you identify these are the right folks that will actually participate and that's where AI comes into play. So this is fascinating and you've just described a number of different industries and companies, beer brewers, liquified natural gas pharmaceuticals that are using AI to transform themselves. What is your, what do you recommend for the people out there watching who say I want to do that, how can I get on board? Well what we advise companies, our clients they really get good at three things. And the first is just to do things differently. So you got to go into your core operations and figure out how you can extract more cash and more profit from your existing operations. And so that's like we talked about natural gas, right? Like you can produce it more profitably and effectively. But that's not enough. The next thing you need to do, step two would be to actually grow your core business. Everyone wants to leap to the new right away. But you're generating all your cash and your legacy businesses. And so like we saw in the brewing history if you can find new customers, profitable customers, interact with them, create a better digital experience with them, then you'll grow both your top line and your bottom line. But from our perspective the reason you do both of those things is to generate cash then make investments into new, net new businesses. And so the last thing you do is to do different things. So find an adjacency and grow it. And it's important to talk about the role of AI on that because that's the way you develop outcomes with speed, right? Like you're not going to build a factory anymore, you're not going to build a service or some sort of information centric offering. And so what we like to do is we talk about like the wise pivot from your old legacy businesses where you generate cash and you make selective investments in the new and how you regulate that is a really important question because you're too fast and you starve the legacy businesses like too slow and you're going to be sort of left out of the new economy. So doing those three things correctly with the right sort of managing processes is what we advise our clients to focus on. So I see all of this from the business side but do you, because you're also a consumer, do you ever see any sort of concerns about privacy and security in the sense of why does anyone need to know if I like to run or I like barbecue with my beer? I mean, how do you sort of think about those things and talk to clients about those issues too? Well, I think actually for Accenture, a large part of our focus is what we call just ethical AI. And so it's important to us to actually have offerings that we think or that we're comfortable with that are legally comfortable but also just societally are acceptable. And it's actually like there's a lot of focus in this area, right? How you do it. And there's actually a lot to learn. Like what we see for example is there could be bias in the data which affects the actual algorithm. So a lot of times rather than focusing the algorithm you need to go back to the data and look at that. But it's something we spend a lot of time on it's important to us because we too are consumers and we care about our privacy. So when you talk about the wise pivot and the regulation, this is a big question. There's a lot of bills on the table in Washington. It's certainly dominating our national conversation, how we think about regulating these new emerging technologies that present a lot of opportunities but also a lot of risks. So how are you at Accenture thinking about regulation and working with regulators on these issues? Well, we get involved with talking to the government. They seek independent counsel. So we participate when they're seeking guidance and we'll give our offer. So we're a voice at the table. But what I would say is there's a lot of discussion about privacy and AI. But if you look at a national level, particularly the government, I think there used to be more focus just on the parts that are incomparably not problematic with privacy. So I gave you the example of working with liquefied natural gas. We need better AI to run our factories better. There's a lot of AI that goes into those kinds of problems or supply chain planning. Like how do I predict demand more effectively? Or where should I put my plants? And AI is the new way supply chain is done, right? And so there's very few of the consumer-centric problems. I think actually as a society, like 90% of the use cases are going to be in areas where they don't actually influence your privacy. And a lot of our time is actually working on those kind of use cases just to make the operations of our organizations more effective and more efficient. So we talked about the very beginning at this conversation about the companies that are disrupting old industries, using a lot of these technologies. I mean, is AI a case where you need to be using this? You need to be using it. You need to be using it. My view, my personal view is that there is going to be no basis of competition in the future except for AI and digital. It just is going to be the case. And so all of our clients at some state of maturity and they're all asking the question, like how do I grow? How do I get more profitable? Like certainly the street wants more results. And so if you want to move quickly into new spaces, you only have one choice really. And that is to get really, really, really good at managing and harnessing digital technologies inclusive of AI to compete in a different way. And so, I mean, we're seeing really interesting examples where like retailers are getting into healthcare, right? Like you see this, like you go into Walmart and they have, or Walgreens, they have like a doc in the box, right? So we're seeing, but lots of companies that are making physical things that then turn around and develop a service. And what they use, they use their know-how, their tech, everything they know about like something, you know, about like healthcare or how to like, you know, offer services to customers in a retail setting, but then they need to do something different. And now how do I get the data and the know-how to then offer like a new differentiated health service? And so to do that, you know, you have a lot, you have a lot of understanding about your customers, but you now need to get all the data sources in place. You may need certain help desks, you know, you need ways to aggregate it. And so you probably need new partnerships that you don't have. You probably need to manage skill sets that you don't have. You may need to get involved with open source communities. You may need to be involved with universities that where they do research. So you'll need different kind of partnerships to move with speeds. And then companies have probably used in the past, but when they put all those ecosystems together and a new emphasis on the required skill sets, you know, they can take their legacy knowledge that's probably physically oriented and then create a service. They can create, they can monetize their experience with a new service. What we find usually doesn't work is just to monetize data. If you have a lot of data, it's not usually worth that much, but if you take the data and you create a new service that people care about, then you can monetize your legacy information. And that's what a lot of our clients are trying to do. Like they've gotten very mature. And now like, where do you go? And where they go is something maybe nearby to their existing business, but it's not the same legacy business that they've had for years. I want to take a little deeper on something you brought up about the skills. And there is a real skills gap in Silicon Valley and in companies in this area. How are you working with companies to make sure that they are attracting the right talent pool and retaining those workers once they have them? Well, so this is I think one of the most important questions because like what happened with technology in the past is we would put in these like ERP systems and that was a big part of our business like 15 years ago. And once you learned one of those things, SAP or Oracle or, you know, like whatever, your skill set was good for 10 years. You probably, you were good. You could just like go do the work. But today, if just to just go down to like the convention center and look at this vast array of like new. Humanity. Yeah, humanity and new technologies. I mean, half these companies didn't even exist like five years ago, right? And so your skill set today is probably only good for a year. And so I think the first thing you've got to realize is that there's got to be a new focus on actually cultivating talent as a strategy. It's the way to compete. Like people is your product if you want to look at that way. But what we're doing actually starting very, where we can very early in the process like much beyond a corporation. So we work with charter schools to work with kids. We get them into college. We work with universities. We do a lot of internships. So we're trying to start like really early on. When you ask a question or like, what would our recommendation to the government be? We're actually advising like get kids involved in IT like earlier. And so we can like get that problem resolved. But otherwise once companies work, I think you need your own talent strategy. But part of that might be again, like an ecosystem play. Like maybe you don't want all of those people and you'd rather sort of borrow. And so I think figuring out what your ecosystem is. Cause I think in the future, like the competition will be like my ecosystem versus your ecosystem. And that is the way I think it's going to work. And so thinking in an ecosystem way is what most of our clients need to do. Well, it's like you said about the old ways that it was a good idea or a good product versus a good ideas and good ideas that are keep circulating. Thank you so much, John for coming on theCUBE. A really fascinating conversation. It was my pleasure. Thank you so much. I'm Rebecca Knight. Stay tuned for more of theCUBE's live coverage of the Accenture Executive Summit coming up in just a little bit.