Future Back Drinking • Ravi Kumar

Welcome to Future Backdrinking, brought to you by PepsiCo in time. I'm your host, Dr. Athena Cagnora, and as PepsiCo's Chief Strategy and Transformation Officer, I believe it's incredibly important to speak with today's industry leaders about the technologies, innovations and ideas that are certain to impact all of us. Future Backdrinking is not just a podcast, it's a journey through the now into the next. And joining me once again is my co-host, Priyanka Ribindy. Hello, Priyanka. Athena, it is great to see you again. We have another exciting conversation lined up today. This one is around a topic that I am particularly interested in. It is the future of work. Our technology is evolving so rapidly, which poses so many implications for what jobs and workplaces and our society at large could look like. Our ideas of work have already changed so much from what they used to be. People used to spend their whole lives working at one single company or working in one field, but for so many, that's no longer the case. Athena, I'm really curious about your own experience with this. How has the practice of work evolved over your career journey? Yeah, and you bring very valid points about how technology has evolved the way we work, either it is in one company or the others. I mean, let's take the example of hybrid, where many of even our PepsiCo employees, you know, work three days from the office, two days from home, and this level of flexibility and agility that technology can give you is something that we've never had before. I mean, typically, you would say, "Oh, I have to be in the office, nine to five, because I have a desktop, maybe you can bring your laptop at home," but, you know, there was some inflexibility in the working model, right? And when you would have to make customers or partners, you would have to fly there. So definitely, I would say that's work that works, that's something we are using in PepsiCo, is something that is very deeply rooted in allowing the employee to work through an environment and through the means of technology that can unleash his or her full potential. Yeah, it's exciting evolutions, and I am looking forward to digging into more about this with today's guest, Ravi Kumar. Ravi Kumar is the CEO of Cognizant, one of the world's leading IT services firm. In 2025, Time named him one of the 100 most influential people in AI. He began his career as a nuclear scientist before transitioning into leadership roles at Infosys, Oracle, and PricewaterhouseCoopers. Today he is recognized globally for his visionary approach to technology, talent, and business. Beyond the boardroom, Ravi is passionate about expanding access to education and investing in community development, reflecting his deep belief in the power of learning to drive opportunity and societal progress. Here is our conversation. Hi Ravi, thank you for joining us today. Thank you, thank you for the opportunity. We like to start things with a very quick cheers. Sure, of course. Cheers. Cheers. Ravi, because as a CEO you have been trying to keep up with many challenges, so we would like to hear from you how do you experience AI and other kind of technologies changing the landscape. Thank you Athena. Thank you for the conversation today and thank you for the partnership. First and foremost, I think the conversation has gone from what does AI do to how do you get it done. Enterprise CXOS are looking at the value chain and looking at what should be centralized and what should be decentralized. Stuff like subscription services, infrastructure, standards, and a lot of work around human capital. I mean, what does this technology do? How do you embrace it to amplify the potential of human? I mean, the technology by itself is not just an automation tool. It's a tool for reinvention and reimagination of a function, of a process, of a workflow. So applying this technology to old processes is going to not give you results for the future. You will have to use the technology to reinvent and reimagine enterprise process. So there's a lot of work around it. One of my favorites is context engineering. The fact that this is a technology which is not just a tool, it's also a technology which is going to be used for action because it's going to be agentic capital. It is going to actually work alongside human capital. You should also look for opportunities to create the interplay between human and agentic capital and that interplay is going to be very important because you will have to create a level of harmony between human work and machine work. So there is quite a bit of this which we've been working on and the context engineering piece is when you have agentic capital, how do you get the hustle of the company embedded into the AI? I mean, working in PepsiCo is going to be very different to working elsewhere. How do you embed the culture of the company into the agentic capital? How do you teach AI to be a part of your team? So we take the tribal knowledge, we take the workflows, we take the access rights the agentic capital has, we weave it into the LLM so that the agent on the other side is a contextual agent and not a generic agent. So all of these are aspects of actually making AI enterprise-grade and I think it is understated today because a lot of the work, a lot of the AI you see today is actually consumer-grade and as you actually transition to more value upstream, you're going to actually see quite a bit of system integration work in partnership with global clients. Just to zoom out a little bit about the work that you're doing, can you tell us about when a CEO calls up, what are the major problems that they are dealing with that you then are deploying this technology to kind of help themselves? So it's a double-engine transformation. It is on one side a productivity lever, on the other side it's an innovation lever for new products and new services. So you have an opportunity on both sides. Productivity has not improved in enterprises for the last 25 to 30 years and that's because technology has not really amplified the potential of humans, it's actually replaced humans in many ways. So there are companies and CEOs who call me to say, can we actually reinvent and reimagine a process? I mean, process and functions in an enterprise have actually evolved from the industrial revolution and the only time we had disruptive game-changing technology was the digital technologies which kind of actually disrupted the front office. The middle office and the back office have evolved. I mean, how you do accounts payable, how you do accounts receivable, how do you do supply chain management, how you do procure to pay has evolved over the years but it's not been revolutionary. This is a technology which will diffuse in every part of the company. So when I had a chance to work with corporate CXOs, I actually talked to them about reinvention and reimagination of a process versus taking a path of identification. I mean, identification is only a journey. The real outcome is about reinvention and that's one side of the story. The second side of the story is most CXOs have actually looked at software development cycles. This is a technology over the last two or three years. The single biggest use case for this technology is writing code, being a part of software development cycles. At this point of time, 25 to 30% of it can be written by machine. So how do you increase productivity in an enterprise using this technology? So it's a combination. It's a double engine. One side you have productivity. On the other side you have innovation of new products and new services and better experiences. And I think I know obviously a PepsiCo innovation is so much of what you focus on. Are these similar things that you're working on every day? Yeah. No, for sure. What Ravi says resonates a lot. As we are thinking of end-to-end processes, reimagining our processes, you mentioned some of them which are very critical for us, order to cast, procure to pay, forecast to schedule. These are major processes of how we run the business. And therefore embedding Authentic AI to those processes and pretty much re-engineering those processes is a must-have if companies want to be both efficient, effective, but also dry for growth. Absolutely. It's a double engine. And on one side you have cost and efficiency as well as the other side you can enable it for growth. Yeah. Totally. Totally. So we'll pivot a bit because you have been very passionate about empowering humans, right? And we know very well that this technology is very different from the previous industrial automation, especially in manufacturing, but it does require different career paths. It does require people to learn differently. So talk to us about lifelong learning and how do you see career paths evolving through the power of these technologies? Absolutely. You know, I go back to the Industrial Revolution. The template of work and education was a very linear template. We went to schools, learned for the first 25 years, then we probably worked for the next 40, 50 years and then we retired. It's a linear model. That linear model was at a time when the clock speed of businesses was very slow. The clock speed of businesses is so high now that you need a non-linear template. You need to intertwine work and education into workplaces. And you need to take lifelong learning into K-12 schools. The agency of education, the agency of what you want to do should be moved to K-12 schools. And a lot of pivot to good jobs is with undergrad degrees. And all the four years of the undergrad degrees, actually you need to embed that into the work. So if I have to go back to the traditional model of apprenticeships, that's a very good funnel to do this. And once you intertwine education into work, you can create a lifelong learning template because the life of skills is very short and people are living longer. So you might actually have two or three professions in the same life. So the ability to have those learning resources integrated, but actually create the culture of lifelong learning in K-12 schools, and build a frame of apprenticeship where a four-year education is a combination of apprenticeship and university resources, I think is the way forward. That's a template I would look for. I mean, I almost say, learn, unlearn, and relearn in a workplace with educational resources embedded into your work. Something I found really interesting, you've talked about non-STEM disciplines and how those will become more valuable going forward, which might actually be a little counterintuitive to some people who are approaching this. They see technology evolving and thinking, of course, STEM. I would love to hear you talk a little bit more about why you think that is. Yeah. That's a great question. I mean, you know, what's happened with this technology is, so far, most technology disruptions. Humans wanted to understand machines. This is one of the first technologies where machines are trying to understand humans. And the medium is natural language. So workplaces were all about solving problems, and that was the human endeavor. With machines assisting humans, the next human endeavor is going to be about finding the most purposeful problem you want to solve. And if finding problems is the next human endeavor, you need a diversity in the workplace. Problem solvers were very STEM related. Problem finders, purposeful problem finders will come from very diverse backgrounds, like liberal arts, psychology, and anthropology, sociology. And you're going to see them in the core of the businesses as we go forward, because you can actually lend expertise from machines. The asymmetry between individuals and organizations was actually intelligence. And intelligence is now going to be available at such a low marginal cost that is no longer a differentiator anymore. Applying intelligence is going to be a differentiator. That is the asymmetry we're all going to look for. Applying intelligence is going to be the asymmetry. And applying intelligence means you need a much diverse workforce. And you are going to find more non-STEM disciplines contributing to that next human endeavor, which is finding the next purposeful problem. So do you believe STEM is there? Not really. I mean, I think STEM had over-indexed position in enterprises. There are going to be deep programmers who are going to continue to work on AI algorithms. And applying them to businesses, applying them to operations of an enterprise is actually going to be that unlock is actually going to come from non-STEM disciplines. So the equilibrium and the balance is going to be much more now. I also think it has a lot of hustle in the middle. And it doesn't have as much in the front and doesn't have as much in the back. On the front, you're going to see purposeful problem-finding, conceptualization, critical thinking and all of it. On the back, you're going to see validation and verification services because a lot of things we consume will be assisted by machines. So the validation and verification, the human in the loop is actually going to be at the end. Oh, this is very interesting. Yeah. Because the realities, enterprises, history, we have been thinking of, okay, let's infuse more STEM talent to do the transformation and of course, you know, liberal arts and social sciences were much more for the marketeers, were much more for the enabling groups. For the enabling groups, right? You know, the other interesting aspect which is going to happen is, because expertise is going to be on our fingertips, easily available at lower cost, marginal cost, and at some point of time it'll be zero. If that's the case, are you going to give a premium for expertise, or are you going to give a premium for interdisciplinary skills? The reason why I think interdisciplinary skills will play an important role is, if you're a technologist, you're going to get some premium. If you're deep in a domain, you're going to get some premium. If you have skills at the intersection of the two, which is primarily if you're a marketer with computing skills, if you're a biology major with computing skills, you could actually crack drug development cycles. If you're a history major with computing skills, you could be a futurist. So interdisciplinary skills will be the new premium versus the premium we give for deep expertise in a domain. And I would say that's the next big thing which is going to happen, which is how do I actually take every discipline and intertwine it with computational skills? Very provocative. Exactly. Very provocative. And I will let me take you to a different topic. I mean, there was a recent article about the ROI of the EI investments. Are those investments like data centers are going to pay off because of the big capex investments that they are making? I mean, you are so into this industry, you are helping many companies transform across the board, and you are a big partner of those technology companies. So are we in the middle of a bubble? Are we in the middle of another AI wave? There's a difference between industrial bubbles and financial bubbles. Financial bubbles, the downstream is most people in the bubble lose. In industrial bubbles, the technology endures, some players lose. If you go back to the internet, the company which put the most money was Global Crossing, which put a lot of undersea cabling. It went burst because it overestimated how fast internet is going to be embraced. The technology endured, but the players burst it out. So this is an industrial bubble where the technology will endure. Now, what's going to happen is the thesis of it is there's going to be consolidation, and the distribution network you're going to build is going to be valued. The IP is going to build over a period of time. For businesses, it has to actually be economically viable on day one. And that's why it takes longer for businesses to embrace because there is no capital in between. You need an ROI, as you rightly pointed out, for every use case. So I do believe that this is a unique opportunity for reimagination and reinvention we spoke about. And it will be a very powerful business case. The marginal cost of consuming it is going to be much less. And as the value gets to the front, we are going to see it going to be a viable, economically viable thing. But this is an industrial bubble. I mean, industrial bubbles are good. The last time the biotech industrial bubble happened, we got a couple of life-saving drugs. So is this a bubble? It looks like one, but the good news is it's an industrial bubble and not a financial bubble. Well, which is very encouraging for many of the people who are investing in AI and the durability of the technology as well, to your point, because these are huge investments that this industry has never seen before. It's exciting to hear you kind of give this bird's eye view. I want to zoom in and ask both of you, actually, for workers on the ground, what practical steps do you think that employees should be taking to sort of upscale or stay up so they aren't left behind with the new technologies that organizations are introducing that are being rolled out all the time? So I think I have been talking for the past two years about setting up Digital AI Academy for the organization, which is about lifelong learning, as Ravih has said, but more importantly on the job training, because the employees need to experience AI in the natural environment. You're a track driver. You need to sit while you do the engineering on the car, while you talk about health and safety, while you drive and you want to do root optimization. So embedding AI in everyday tasks and then amplifying the experience and making it better and making it easier and making it much more interactive is what we have been trying to do. And that's why I think, as Ravih said, this time around is not the threatening technology for the employees. It's the technology that they want to embrace because they do feel their job being much better than what it used to be. So absolutely, we are very supportive and we have been, for the past two years, doing on-the-job training in every facets of the employee base that we have in the organization. This is a very popular saying that the technology is not going to replace your job. Somebody using the technology is going to replace your job. So effectively, what it means is if you can embrace it, you're pivoting to the future. The job you do could be very different because you're assisted by machines. I mean, this is a technology which is literally at a task level. So some of the tasks you do today, you do because there's nobody else to do it. You're probably going to outsource it to a machine and you are starting to look for more value-added tasks. So in our studies, what we have seen is it's also an equalizer. What I mean by an equalizer is the entry barriers for jobs are going to be diffused. It's going to be marginalized. You can enter into jobs which you could not enter before. The gap between occupations and the gap within an occupation is actually going to shrink. And that's very important. You have to incorporate AI tooling into your daily work routines. That is the only way you can embed it. It is not a side thing. It has to be embedded into your daily routines and the culture, I mean, Pepsi does that very well as well. I mean, we work on a variety of platforms which are applied on software development cycles which are owned by you completely. So I think it is a technology which will be an equalizer. In fact, one of the other stats I had, which is an interesting stat is the top 50 percentile of my developer community got 17 percent productivity. The bottom 50 percentile actually got 36 percent productivity. So it kind of took the bottom up and it kind of took the top up and it allowed the bottom to actually move up much more. To become closer. To get closer to the average. So it's a fascinating thought. I don't know whether that's going to sustain for a long term, but at least at this point of time, that's what the community within my team is experiencing. It's a tool for amplification of your potential. If you see it that way, you're going to benefit significantly. You should embrace it with a sense that is not placing you, you should embrace it with a sense that it's going to increase your productivity. You can do things which you could never do before. No, I echo what Ravi said. It has to be embraced as if it is in the natural way of doing things. So the way you decide in the morning what to do and what to eat and what to wear and where to go, AI is becoming part of that daily routine. I have two sons, 16 and 13, they use AI in everything they do and now they probably use more than us. Much more than us. For sure. For sure. But also I see schools embracing it now in the States where they finally have decided and they have understood that it is a great means of communication plus also enhancement of knowledge. So I do believe that from your point, K-12 education is going to be super important for this next generation of workers and employees. I do feel there is a big gap in universities right now, bridging that K-12 till the workforce. And therefore that gap currently is being bridged by companies like Kravitz, companies like mine, that we are giving this ability to the employees to create these enhanced experiences. But I do believe that we are just scratching the surface of how AI is going to truly redesign the way we run businesses and how we learn in the future. I do have one question before we go to the lightning round because you keep talking about decision-making approaches and you talk about gut data guts. So maybe you can elaborate here what exactly you mean by gut data guts. You know I happen to build this theory. I started my career as a scientist. I was a nuclear scientist and then I thought this pace at which science was moving was less than the pace at which technology was. So I switched to technology and now I hope technology can actually contribute back to science because you could use technology to understand human DNA, material sciences and stuff like that which you can do with AI. So coming from that background, every time we see a new thing, a new experiment, I've always had this philosophy that the first 30 to 40% has to be gut and the gut will come from intuition, your experience, your ability to connect the dots. And the next 30 to 40% has to be powered with data. It should be layered with data. And after you get to 60 to 70% you cannot actually continue double clicking on it with data because then you'll miss the bus. So you then switch back to gut. So the ability to continuously build the gut data, gut template for new things has kind of worked for me. You can stay ahead of the curve because you're not going all the way to the 100%. You're not just doing on gut. You have a science behind it. Therefore, there is data on it. And it's just a thing which I have a mental model around it. Okay. So human intuition is still very important. Human intuition. I mean, the first 30% to 40% is that. And then you layer it with data and then you don't want to miss in a high clock speed economy. So you switch back to gut. Amazing. Now it's time to move on to the lightning round at the end of each episode. We like to ask our guests a series of quick hitting questions to get to know them on a more personal level. Okay, Ravi. Are you ready for the difficult questions? First one. One skill you'd love to learn outside of work. Story telling. I thought it's an understated skill. I mean, we're all living in this economy where there is so much information available. So storytelling is a unique differentiator. I kind of undermined it growing up when my grandmother used to tell stories or my mom used to tell stories. But now I actually think that is the skill I would like to learn if I have to do it outside of work. Amazing. Made a whole room of producers. Very happy, I'm sure. You see this profession would not go away. If you were not leading cognizant, what career path do you think you'd be on right now? I would love to go back to being a scientist. Interesting. I mean, it's an extraordinary profession to work on things which people have not worked on. So I would say being a scientist. Well, then I'll follow up from what Priyanka asked. So what is one perspective from science that still shapes how you live today? It's a great question. I think we all create a thesis in our mind with assumptions and we are so passionate about those assumptions. I think as I've noticed implementing it into my workplace, you have to revisit those assumptions on a continuous basis and you should be able to abandon them and be as passionate about abandoning it and quickly switching on to the next set of assumptions. So rethinking assumptions and having the discipline in that flexibility. It's a counterintuitive thought to say discipline and flexibility, but having the discipline in that flexibility, I think can get you past things which you believe you want to take it to the finishing line. So I've kind of applied it, but I want to ask you one question. Oh my God. Okay, that's a fair answer. No one is asking my question. What is that one skill you look for when you hire somebody? What is that one thing which you believe when you want them to be a part of your team? Azzility. Azzility. Azzility. For sure, azzility. Yeah. I mean, to your point earlier, you can have deep scientists and they can be the best executors of a strategy, but as you know very well in a corporation, you have to tweak it. You have internal and external disruption. So you need your people to be flexible, to be agile, to be street smart. So that level of agility is always what I'm looking in someone, at least we are hiring in strategy and transformation. They need to be able to adapt and adjust very quickly. And thrive in ambiguity. And thrive in ambiguity. It's a hard skill. It's a hard skill, especially nowadays, as we all know very well. Okay, now I'm pivoting. I read you were once a Bollywood movie reviewer. Is this true? I mean, it's on my Twitter handle, so whoever has researched it has researched it well. I did. I mean, I used to enjoy the process of seeing a movie and coming back with very refreshing view of what the movie is about. I don't get time anymore to see movies, so I don't do it now, but it was just a way to unleash myself outside of work. And I love Bollywood. By the way, on record, it's an amazing industry. So it wouldn't be a future back drinking episode if we didn't ask you if you were to have one drink with anyone, who that would be and why? My wife. Oh, that's so sweet. I think the ability to see your blind spots, the ability to be critical enough, and the ability to stay invested in your journey are your spouses. And I always enjoy the process of having a drink with my wife. Okay, if you're listening to your husband, well done. Very well. Ravi, thank you so much. Thank you so much. Thanks for the opportunity. I had a lot of fun. You have been an amazing partner of PepsiCo all those years, and I can't wait for us to keep on working on all the tough problems. Absolutely. Absolutely. Thank you so much, and thanks for the partnership, and thank you for inviting me. Thank you. Thank you so much. Cheers. What a great way to kick off our exploration into the future of work. I really appreciated Ravi's insight into the workplace and some of his ideas about the ways that people and organizations need to be adapting to be ready for it. Athena, from your perspective, how else should people who want to stay ahead of the curve or who want to grow and adapt within their roles be preparing for what's to come? Well, firstly, they have to be curious. Life doesn't end when you finish university. This is actually what it starts. You need to keep on experiencing through the power of technology, different domains, different functions, different capabilities. I would say that's number one. And second, you definitely need to get your hands dirty with technology. I mean, unless you try and you fail, you will never learn. So this concept always that has been around technology fail fast is even more important with AI, because AI will not have all the answers. Don't feel that now that you stopped with university, whether it's undergrad or postgrad, your learning has finished. Actually, this is when the learning is starting. I love that advice. It's very actionable and it's a mindset shift. It's not necessarily that you have to go out and do X, Y, and Z. It's just change the way that you're thinking about it and then how you approach it will follow. It's very actionable advice for our listeners. Wonderful, Bianca. Thank you so much. Ken, thank you all for listening to Future Back Drinking. We hope that you enjoyed the conversation with Ravi. Please be sure to like, subscribe, and stay connected with us on all of your favorite podcast platforms. Until next time, take care.