James Kotecki (00:00): 

Hey, it's James Kotecki from CES Tech Talk here to tell you that registration for the world's most powerful tech event is now open. What event is that? You know what event it is. Come on. The greatest minds, the most powerful brands, the most impactful technology, it all comes together at CES 2024. So discover the tech defining AI, transportation, startups, smart cities, digital health and solutions for a better, more sustainable planet. Register now at CES.tech. All together. All in, all on. 


This is CES Tech Talk. I'm James Kotecki. The world's most powerful tech event, CES 2024 brings the future to Las Vegas, January 9th through 12th and today we preview the future of business, and that's a big topic and we've got a big guest today to tackle it. Paul Daugherty is the chief technology and innovation officer at Accenture, the professional services firm where over 730,000 employees are building the future of business around the world. I looked it up. That's about the population of Denver, Colorado by the way. So it's a pretty big deal. And getting Paul's take on the topics of today and tomorrow should give us a good roadmap for CES 2024 and the future as a whole. So no pressure Paul, but there is a lot riding on this conversation. Welcome to the show. So glad to have you. 

Paul Daugherty (01:32): 

No, great to be here. And really looking forward to CES. It's going to be an amazing session as always. 

James Kotecki (01:38): 

Absolutely. And you're the chief technology and innovation officer at an important company like Accenture. What does that actually mean? What do you do all day? Are you getting into the trenches on anything? Are you just sitting up on a cloud kind of observing and managing people? How do you actually spend your time? 

Paul Daugherty (01:57): 

Yeah, it's a fascinating job and I think I have one of the best jobs that there is. It's really a lot of fun and it's a great position from which to both look at technology and look at businesses and industries around the world and look at how they navigate to their future. And there's kind of a phrase I've been using for a while to talk about how we think about technology and how it's impacting business. And there's really two key truths that I talk about. The first truth is that exponential technology innovation is continuing and accelerating, hence new innovations like generative AI that come at us so fast as it has. I'm sure we'll talk a little bit more about that and that'll be all over CES. But the second truth is that every business is becoming a technology business because these advances in technology aren't just about the back office or parts of an enterprise like it used to be for information technology. 


This exponential technology is reshaping every part of every business, transforming the way businesses operate, transforming the way consumers can get goods and services, and that's what's super exciting. So my job is to marry up the two of these, is to look at where is technology heading and what does that mean for business. So I spend a lot of my time with the leading technology companies, and innovators, and venture capitalists, and investors around the world to understand where technology is headed and universities and others as well. And I spend a lot of time with the C-suites and boards and others and businesses around the world to understand their challenges and how they address them. 


And I think about my job in three categories. It's about our clients, our people, and our partners. Our clients is work that I do to help our clients innovate. A large company I'm working with right now, a large consumer company on adopting advanced digital manufacturing practices powered by AI, robotics and other technologies to transform their manufacturing and make it more resilient and more personalized to their consumers. So that's our clients. With our people, it's about my job, we have 730,000 people. That's an amazing resource to tap for innovation. So it's about connecting with the best ideas from our people. With our partners, as I said earlier, we are the leading partner with most of the technology companies and institutions around the world. So we can collect and be the vehicle to get those best ideas and channel them to our customers. 

James Kotecki (04:21): 

And how do you balance all of these things together in one human lifespan and one human work week. Right. Because I imagine that in your role you could probably make a case for doing nothing but reading and learning and absorbing and trying to understand this. You could be talking to clients all the time, you could be talking to partners and employees. So how do you keep your sanity? I guess I'm trying to ask, because what you're doing stretches over to so many different categories that are covered by CES and the Consumer Technology Association. And on this podcast we're trying to absorb and understand it all and here we have you whose job it kind of is to figure it out and understand it all and make some practical value out of all of this. So how do you stay sane? 

Paul Daugherty (05:02): 

It's a good question. Well, first of all, I just love this stuff. So this is my passion, my hobby in addition to my profession. So I'm fortunate to have that alignment. This is just kind of what I do, but it's also about having an amazing team and set of resources and capabilities that we've set up across Accenture. So within Accenture, one of the organizations that we have is our R&D organization called Accenture Labs, which has been around for 30 years and has an amazing track record. It's PhDs and researchers located in key spots all over the world looking at technologies and charting out how they're going to be applied to business in the future. We have also a venture capital arm we've set up called Accenture Ventures that's out there talking to early stage companies and we take positions so we can learn from the innovators and early stage companies as they go as well. 


So that's a key capability that we have out there. And then it's innovation teams and what we call our innovation hubs and innovation centers all around the world who are doing those day-to-day discussions with clients. So we're learning from the new problems that are coming up. We're learning about how to apply new technologies. So the way I maintain sanity I guess is by having an amazing team and a network and a fabric. We actually call it our innovation architecture of how we pull all this together and then assimilate and collate to get to the real trends and actions that we need to take. 

James Kotecki (06:29): 

So I think we've established that you're in a great position to speak broadly about a vision for the future of technology and in fact, Accenture has this annual, I believe it's a report called the Technology Vision. You mentioned generative AI, you mentioned this idea of exponential increase of technology and innovation in the pervasiveness throughout the business community and around the world. What other pieces of this technology vision are on the table right now for Accenture? What's the vision? 

Paul Daugherty (06:58): 

One way of looking at it is the journey that companies are on. The title of our vision 10 years ago was every business is a digital business. That was 10 years ago in 2013. 

James Kotecki (07:11): 

Wow. A more innocent time to be sure. 

Paul Daugherty (07:14): 

Yeah. And at the time,- 

James Kotecki (07:15): 

Simple times. 

Paul Daugherty (07:16): 

I spent a lot of that year defending it. I'd go into companies and they'd say, that's crazy. Our industry, our business isn't digital. But quickly digital became the driving force for companies and they're still on that journey. Most companies, everybody had embraced that idea by the way. Everybody does believe their digital businesses have been on that journey, but most have a lot of work to still do to become truly digital. So companies are only on general, on average, I should say 40% in the cloud right now. If you look at enterprise workloads, 40% in the cloud. Only half of those really modernize to take advantage of the cloud. So it's a lot of work when you look at kind of vision of what companies need to do, a lot of work left to do and things that may seem more basic but are relatively new also like cloud computing to really take advantage of it. 


And then generative AI is obviously the new kid on the block. We've been deploying AI solutions for clients for almost two decades. So AI isn't new. AI for visual video technology to identify defects in manufacturing plants, we've been doing that kind of thing for years as an example, or forecasting retail demand based on predictive data patterns and machine learning algorithms. So AI isn't new, but generative AI is a step change and an amazing new capability that allows us to create new content, whether it be images or language or what have you, and its master language and the ability to converse and interact with us as humans in a more human way. And that's really at the foundation of some of the things we'll be talking about at CES this year. This idea that exponential technology is now becoming more human is actually a great thing. For some it becomes scary, but I would argue it's the best thing for human potential and human productivity that we've seen to date in the digital revolution. So that's very exciting. 


If you look at other trends that we're looking at, we're doing a lot of work around quantum right now as an example. We think Quantum has some interesting applications today, although the big general breakthroughs are a little bit off still. We're doing a lot of work around various space technologies, space-oriented technologies that work a little differently and have an application as you look to the next frontier or the final frontier of space and many other areas, but that just gives you a flavor for it. 

James Kotecki (09:32): 

We've talked about AI on this podcast with other guests before. We've talked about space with other guests before, and I'd love to get into both of those topics with you on this interview as well, but I want to make sure we cover quantum computing because I don't think I've spoken to a guest on that about this topic on this season of the podcast or any of the season of the podcast, I think. So can you explain a little bit about the current state of quantum computing? It's always kind of seemed like this sci-fi concept, the value is just around the corner and folks are working on it. What is actually practical right now or kind of in the foreseeable future there? 

Paul Daugherty (10:05): 

Yeah, we've been doing R&D and quantum computing for over eight years now, probably closer to 10 years. And we've been doing some applied projects with clients as well. Quantum computing in terms, the big breakthrough people talk about is quantum supremacy, when quantum computing can generally surpass all the capabilities of classical computing that we use today, and that is still a ways off in terms of quantum supremacy, but that doesn't mean that quantum isn't relevant today. It is, and it can be used to solve some problems today. There's two broad dimensions of where we see quantum being applicable today. The first is in cryptography and security. At some point, quantum algorithms will be able to break today's RSA-based encryption, and that means that companies today need to be readying themselves for post-quantum cryptography, and those that follow these things will know the White House, the US government issued an executive order about preparedness of federal agencies for post-quantum cryptography. And that's creating work for us to help government agencies and some leading clients who are concerned about these things prepare themselves. 


The way to think about it is the bad guys have a treasure trove of stuff they can't yet decrypt, but once they can decrypt it, they've got the gold mine. So how do you better secure your documents today so they can't be unlocked in the future? So that's one application that's out there. A second is that there's certain problems that can be modeled much better by quantum algorithms. There's problems we've seen in material science, problems we've seen in drug discovery where quantum algorithms or problems modeled in a quantum way can be solved more effectively partially by quantum computers, but also by quantum simulators in the cloud. 


For example, we've done work with one of the large cloud companies to model the chemical bonds of what's called PFAS. PFAS are the plastics that don't decompose that lead to some of the contamination in the oceans, very difficult to break those bonds. We did a quantum simulation. We modeled the problem using quantum. Quantum computers aren't ready to fully solve the algorithm, although they can solve a small piece of it. And then we solve the rest of the problem using a million cores on a hyperscaler of classical computing, but operating on a quantum algorithm. So that idea of modeling problems in a quantum way, solving part of it using quantum and solving the rest using classical computing opens up new ways of solving problems. 

James Kotecki (12:33): 

I really can't get past the really cool name, quantum supremacy as a potential Netflix series or maybe a title of a novel that you can go to work on, but you already have plenty of things on your plate. Speaking of science fiction kind of becoming real, obviously we do want to get deeper into AI. You mentioned you're going to be talking about it at CES. You seem optimistic and excited about the ways that generative AI is playing out. What are some of the ways that you see it playing out either inside Accenture from a day-to-day perspective, from how employers are using it, how your clients are using it? Are there some interesting generative AI applications that you can highlight for us? 

Paul Daugherty (13:13): 

Yeah, I mean generative AI, just to put it in context, we are big believers in the impact of generative AI. It is a massive breakthrough that unlocks new capability and we believe it will lead to the reinvention of business. It'll redefine the leaders in each industry. Those that adopt it will be in a different position, kind of like digital and other technologies have. And we do also believe it really is a fundamental enabler of greater human potential and productivity, and I'll talk about that a little bit as I talk about some of the examples. So we're using it in our company today already. We've got a large language model that we use for knowledge access within our company. Used by over 100,000 employees very effectively to access information in ways they couldn't before. And for us, that's massive. A 700,000 person organization, if you can make it easier to access information to better solve client problems, that's big for us and it's big for many other,- 

James Kotecki (14:11): 

So it's kind of like the Accenture hive mind, so to speak. You're kind of all being able to tap into it. 

Paul Daugherty (14:14): 

Exactly. Think about it like that. And it's for all sorts of information that might help you in serving a client, but also information about how do I access my benefits and things like that, that sometimes the big companies are a little hard to do. We've taken that same type of idea to an energy company and the application they wanted was how do they increase their safety practices, which is massive focus in industries like that. Very effective application in our case, again, a large language model, generative AI providing people with better information on real-time events happening that might cause safety conditions combined with all the environmental health and safety and regulatory information so that they can it operated better and more safely on a day-to-day basis. So real benefits of things that you can do today. 


So we see it going in a two-speed manner. That's the way we talk about it with companies. Think about two speeds. The first speed are what are the things you can do today that are relatively safe that you can do with today's technology because the technology is very, very early. Important to say that with generative AI. 

James Kotecki (15:17): 


Paul Daugherty (15:17): 

And you can do it in a cost-effective manner. That's speed one. Some of the things I talked about. It might also be using the capabilities of existing products, using Einstein GPT from Salesforce or ServiceNow's agents they've rolled out or SAP as they roll out their Joule generative AI capabilities. So you can use the capabilities that are there today. The second speed or another one is Copilots through Microsoft or Google's technology for the same. So a lot of potential for that. Then the second speed is what's the game changer in your industry? And this is where we're spending a lot of time with senior executives at companies to look at, if you're a life sciences company, where's the game changer? 


And for them it's can I reduce the time to market for new drug from seven years to one year or to six months? And they see opportunities to do that, not necessarily overnight, but using information in new ways, new generative AI models around biology to better understand the pathology of what's happening, new generative AI models around chemistry to understand the molecule match to solve that condition, generative AI models around people in clinical trials to better diagnose results and improve the trials process. So that's an example of what will be kind of raising it up to the higher gear, that strategic differentiation for companies. It might be the underwriting and claims processes in an insurance company, might be the wealth management and investment processes in a bank. And we're seeing a lot of focus in helping clients at the early stages of these more game-changing applications. 

James Kotecki (16:49): 

Wow. So much to think about and so much impact this is going to have on the world of business and the global economy. I'm always curious from the individual perspective on how people think about these technologies as far as how it reshapes their own understanding of their brains and their own creativity and their own kind of human spark that they bring to projects. And the argument goes something like, well, look, obviously right now ChatGPT is not quite as good as a human and you still need a human to polish it and prompt it, and you still need to give it feedback and tweak it, et cetera. And over time though, these models are going to become better and better and more and more creative, or at least they're going to feel like they're creative. Whether or not they actually are is maybe a philosophical debate. But how are you seeing these kinds of questions and what do you think about this idea of humans needing to maybe redefine their relationship to what it means to be creative and I guess to get philosophical, what it means to be human? 

Paul Daugherty (17:44): 

Yeah. Yeah. I think that's the paradox of this, is that the technology is becoming more human-like and I think so it leads people to think, well, it's going to replace me in everything I do. The reality is, again, we believe it's much more often augmented than replaced because the human-like technology means you can use it in different ways and be more effective. We see an example of this in an application we did for a very large multinational bank. We used a GPT model in their post-trade settlement process. This is highly manual processes where you need to read a lot of emails and look at transaction exceptions as you're closing out trades and deal with a lot of anomalies. We use generative AI to understand all these emails, understand the transaction activity, and then provide it in a more digestible fashion to the humans so that they didn't need to do the drudgery of looking at this, looking at that. 


They just need to use their investigative and judgment capabilities to take the right actions, increase the satisfaction that people doing the work, made them more productive and it was a better outcome. That kind of implication is what we see much more often. And yes, as things become more productive, do you need less people to do it? That'll be one implication. But in a lot of cases, companies are looking to repurpose the talent to do more. So we're working with a public service agency in Europe that it's also a commercial agency in this case, on productivity in their customer service organization. They don't want to do it with less people necessarily. Though what they want to do is do more cross-selling and enable their people to do more and different things than they could do before to provide better satisfaction to the constituents that they're serving. 


So it's a complicated question. I think this will change as the technology matures. And if you look out 10 years, it's a little harder to predict maybe. But and as far as we can see, we really believe this human plus machine view. And in fact, I wrote a book called Human + Machine six years ago talking about how we would see this all playing out. It's kind of largely on track with that kind of view. 

James Kotecki (19:55): 

Yeah, you nailed that with that concept. And what I love about interviewing, by the way, a senior leader from Accenture is that with every question I have, you have specific examples of companies that you can actually point to as real examples of what we're talking about. I want to touch on a couple of other topics here, and we're just going to kind of go rapid fire because we could cover so much in this conversation. And you did mention space. Space is obviously increasingly important to what's happening on the ground. What should the average CES 2024 attendee understand? What's something interesting for them to realize about what's going on in space and how that might impact them in their industry? 

Paul Daugherty (20:34): 

Well, I'll tell one thing I learned from our researchers and the early work we're doing in this space is a way of thinking about opportunities in space. I'd share that as maybe the way to think about it. And we think about it in three categories. There's space to space technology, and that's things you do in space for space. So one example here is thinking about how mesh-based communications and even payment infrastructures might work in space. You could envision a future where with so many satellites up there where one satellite needs to communicate with another on collision avoidance, and there might be a financial transaction involved with that, that can't be mitigated on earth because of delays and such. So that's work we're actually doing with some organizations looking at things like that, about space-to-space interaction and communication. 


There's space to earth, which is how do you use innovations in space to do things on earth better? An example of this is low earth orbital satellites that are used for much better earth-based imagery than you could get previously. Companies like Planet Labs, which is one of our Accenture Ventures companies we invested in that has tremendous governmental and business applications because they can daily scan the planet at a pretty good level of resolution and help you make lots of different decisions. That's space to earth. 


And then earth-to-space, which is how do you make the missions more effective and get things in space in a more safe, secure, cost-effective manner. Work we're doing in this case is with another one of our venture companies that we invested in, is securing the satellite communications because one of the new frontiers for cyber warfare is hitting the satellites. And so the satellites need to be secure because it's not as easy to dynamically update the software and patches and things on the satellite. So you need to think about security in a little different way. And in fact, quantum communications and some other techniques that we talked about earlier come into play in how you deal with that. 

James Kotecki (22:35): 

And just to clarify that first example, the satellites from the space-to-space example, one satellite needs to do a financial transaction with another satellite. Is that as a condition of avoiding the collision or just because communication costs has some kind of cost to it, and so there needs to be a financial transaction as well just for the satellites to be able to talk to each other? 

Paul Daugherty (22:54): 

By the way, that was a hypothetical example of,- 

James Kotecki (22:56): 

Yeah. Oh, sure. 

Paul Daugherty (22:57): 

That I used there. The idea there would be that that's an example of a financial transaction. You could envision satellites needing to negotiate or other space-based devices, vehicles needing to negotiate as you have more of them up there. Yeah. 

James Kotecki (23:12): 

So obviously we're really positive about what's going on with generative AI and its ability to reshape business and work for the better. This technology is not without its risks, and I think you probably know better than anyone what some of those are. So can you just talk to me a little bit about how Accenture is thinking about mitigating risks? 

Paul Daugherty (23:32): 

Yeah, it's something that every company needs to spend time on, and we have focused a lot in Accenture on responsible AI, which is how to use AI in a way that avoids bias and make sure the outcomes are fair. How do you use it in a way that's explainable where it needs to be? Because sometimes in some industries and some processes, you need to be able to explain and show your work. How do you make sure you don't have intellectual property or other considerations and how do you make sure that the hallucinations don't get in the way of the accuracy, level of accuracy that you need? And then finally, sustainability. How do you make sure that you're not using models that use inappropriate amounts of compute and carbon and such? 


So it's really important to get a foundation in place to proactively manage that. We've got a approach to doing that at Accenture. We actually have a responsible AI compliance program that reports to our board of directors on a regular basis. And we believe that that level of rigor and discipline is needed by every company as you move down this path. And simple way of saying it is if you don't have a rigorous responsible AI program in place in your company, it's simply irresponsible and you'll run into trouble at some point. 

James Kotecki (24:45): 

And I would just highlight that point you said. The responsible AI folks are reporting periodically, directly to the board. So obviously this is a risk that the company is taking very seriously and working to make sure that it's not a factor in impeding the productivity gains that we all want. 

Paul Daugherty (25:00): 

Exactly. Yeah. 

James Kotecki (25:01): 

I promised a rapid fire conversation, so we're going to go from the universe to the metaverse. This is something I know that you have been thinking about, and we don't use, the term metaverse, I don't know if it's kind of diminished in fashion or it's gone out of vogue a bit. The last couple of CESs, I was maybe talking about it more than I expect I'll be talking about it at CES 2024. But has the concept gone away? Has the concept just shifted to some different language? How are you thinking about the metaverse today? 

Paul Daugherty (25:27): 

Yeah, it's a really important question and a good question. Last year, our vision was titled meet me in the metaverse, and we stand by that. I don't think that was wrong. I think that the trends toward what we defined as the metaverse, we call it the metaverse continuum, which was spatial computing combined with Web3 technologies like distributed ledger and other types of technologies for different forms of transactions would really revolutionize identity and the way we interact in not just a flat 2D dimension, but a third dimension with technology. That will come to pass. I think Apple's announcements on what they're doing with spatial computing and the headset are an example. 


I think a little bit of that is the timing, is taking longer to play out. Also, generative AI came along, and I think that took a lot of the attention around innovation and where companies wanted to focus and driving their innovation. But I think the world we live in is three dimensions, and for our digital world to be confined to two dimensions is ridiculous. And I think that will change as technology evolves and it will come back around. The word metaverse has a bad connotation, so we're kind of avoiding the word just to avoid that debate. But the underlying concepts we believe are still the right ones. The question is the timing. 

James Kotecki (26:45): 

Yeah. Metaverse Continuum, by the way, is the sequel to Quantum Supremacy that we're going to be working on after we finish that one. 

Paul Daugherty (26:52): 

Another chat. 

James Kotecki (26:54): 

Let's talk about CES 2024 for a second. We've been alluding to it. What is Accenture going to actually be doing on the ground? How are you going to get involved? 

Paul Daugherty (27:02): 

I'm so looking forward to CES this year just because everything, it's such a dynamic, exciting, overwhelming experience every year, and I'm really excited about what we're doing this year. So for the first time we're unveiling our annual Technology Vision at CES. We thought about it earlier in the year. We typically release it a little bit later. We thought about it and said, why not do it, yeah, do it at CES? It's the best place to talk about trends and vision, what's happening. 


So I'm really excited that our unveil of our vision is at CES, and we'll do that on one of the stages there. So that's very exciting to me. I'm going to have some surprise guests that are going to join me for that, which I think people will love. I can't say who they are, but I think we'll have a really, a great session there on the research stage. We also have an Accenture innovation hub that we've set up. We've actually, think of it as a pop-up of our best innovation. We're going to bring in some of the client innovation we're doing. We're going to bring in generative AI and generative AI examples, and we're going to do some workshops and education for people that are there too on the technology and also showcase what we're doing with a lot of our partners. So super excited about all that. It's just such a vibrant experience that I'm really looking forward to. 

James Kotecki (28:15): 

And you know CES well. Can you pick two kind of technologies or types of companies at CES that you hope will run into each other and maybe do some kind of collaboration? Because CES is all about different technologies, kind of collaborating and meeting up in places where they might not otherwise. 

Paul Daugherty (28:33): 

I think health is one that I would maybe single out. I think there's such amazing opportunities for healthcare, and I think healthcare is, I think, a little bit behind generally in the digital revolution. And there's so much and so many ways that this current wave, incoming wave of technology can do to improve the human condition, improve healthcare, improve the effectiveness, the cost, the access, the personalized nature of it. So I hope there's a lot of connections around that, and there typically is at CES, but I hope there's some real new exciting connections and developments there. 

James Kotecki (29:09): 

Well, Paul Daugherty, chief technology and innovation officer at Accenture. Thank you so much for joining us today. This has been a wide-ranging and really interesting conversation. 

Paul Daugherty (29:18): 

That's great. I look forward to seeing you and many others at CES very soon. 

James Kotecki (29:21): 

Yes. We'll see you soon. And that's our show for now. But there's always more tech to talk about. So if you're joining us on YouTube, be sure to hit that subscribe button, leave a comment, and if you're listening on Spotify, Apple Podcasts, iHeartMedia, or wherever you get your podcasts, be sure to hit that follow button. You can get even more CES and prepare for Vegas at CES.tech. That's C-E-S.T-E-C-H. Our show is produced by Nicole Vidovich and Mason Manuel, recorded by Andrew Lynn and edited by Third Spoon. I'm James Kotecki talking tech on CES Tech Talk.