Upskilling, tapping human talents, and what's really needed for the future of work: Cognizant CEO Ravi Kumar
26:23 Share

With machines and humans working together to solve problems, the next human endeavor is going to be finding the next purposeful problem. Welcome to Meet the Leader, the podcast where top leaders share how they're tackling the world's biggest challenges.

In today's episode, we talk to Ravi Kumar, the CEO of information technology company Cognizant. He'll talk about the traits that we'll need to manage the tech transformations to come. Subscribe to Meet the Leader on Apple, Spotify, and wherever you get your favorite podcasts. And don't forget to rate or review us. I'm Linda Lucena from the World Economic Forum

And this is Meet the Leader. The Industrial Revolution set the template. This is a unique moment for us to disrupt the template. That template is out of the window. It is the start of a new year and our Future of Jobs report has a sneak peek at all the changes that we can expect right around the corner. As you might expect, AI and machine learning have topped the lists of fast-growing jobs, along with things like big data specialists and fintech engineer.

The leaders surveyed this year agreed that the big tech transformations ahead are going to come with big changes in how we lead teams, how we tap human talents. The report finds we will see a net increase of 78 million jobs and an urgent need to reskill people for those jobs.

And the top 10 fastest growing skills list doesn't just include AI or cybersecurity and networks, but what we are most familiar with as soft skills, resilience, creative thinking, analytical thinking, curiosity. In other words, we'll be getting away from top-down structures and into organizations where anyone can drive influence.

Ravi Kumar, the CEO of Cognizant, knows this well. His company has enlisted Oxford Economics for its own research on tech disruption. He talked to me about shakeups to productivity and mindsets that we might see, as well as how advances in technology will push humans to not just solve problems, but to seek the next purposeful problem that needs to be solved.

Ravi will also take us through his unique background. He was trained as a nuclear scientist, and he uses the scientific method as a way to encourage teams to experiment and prove out their hypotheses. He'll tell us how this helps sidestep the command-and-control style of leadership that can stifle creativity. He'll get into all of that, but first, he'll talk more about the research they commissioned and the findings that stuck out to him.

Cognizant works on tech disruptions which come on the way and how do we make sure that they get embraced by large enterprises. So we partnered with Oxford Economics Research and what we did was we wanted to look for the impact

The next wave which is on the way, which is, I would say, really right now, which is generative AI. What does it do to jobs? What does it do to tasks? What does it do to businesses? So we surveyed 2,000 businesses. We looked at the U.S. labor consensus, and we got 22,000 tasks and 1,000 occupations. We kind of mapped all the tasks to each occupation. We looked at exposure scores of each of those tasks.

What does generative AI do to each of these tasks? As AI gets improving till 2032, what does it do to these tasks? What's the exposure score? And what is the friction score? I mean, if you're on a role, say if you're a teller of a bank, you do a set of tasks. If you amplify your potential with AI assistance around you, what are the new set of tasks you will do?

And what's the bridge to get there? What's the friction scores to get there? So we looked at exposure scores, we looked at friction scores, and we tried to map these tasks so that we can understand the reskilling needs for enterprises and how do jobs change. So we do believe if we pivot this well,

we're going to have shared prosperity. So that's the reason why we did it. We did a second version of that report, which was about finding the accelerators for businesses to adopt it and finding the inhibitors for the businesses to adopt it so that we can then understand in detail what it takes to deliver and what is it, what is coming on the way, what are the roadblocks coming on the way. And with this research, was there anything that really kind of stuck out to you or maybe even surprised you?

Yeah, I mean, you know, if you look at productivity for the last 20 years, in spite of tech advances, productivity has been flattish across the world. We do believe this is a disruption which will improve productivity. Just imagine if there is a 1% improvement in productivity just in the United States, to take an example,

It's going to lead to $10,000 increase in per capita GDP. Productivity is going to be a big lever. And productivity is not a lever to reduce cost. It's a lever to actually improve innovation, create new products, create new business models, and more importantly, generate new revenue streams. So we are excited about the fact that this could actually lead to productivity. The last time productivity improved was in the late 80s when

When the information age came down, there were personal computers in enterprises. Productivity did come, but it came with a big lag. We hope this time the bump in productivity because of generative AI will be much faster. This is a technology with an S-curve, like every other technology disruption. It's an S-curve which is sharper. I describe it as an S-curve which will have a slow takeoff, but a very short runaway.

You talked a little bit about these little friction points. Can you talk a little bit more about that? What does that actually look like at a block and tackle level in the workplace? If I'm a leader listening to this and I want to kind of be wary for what that could look like, what are those? It's an interesting impact on human capital. Most disruptions which have happened in the past, they actually disrupted the less productive capital.

This is uniquely a disruption, which is actually going to help the less productive more than the more productive. Our own research says that the bottom 50 percentile benefited 37% on productivity. The top 50 percentile only benefited 17% because of generative AI. So the less productive get more productive, the more productive really don't get so much more.

So it's an equalizer for human capital because you are going to lend expertise on your fingertips using this technology. I mean, this is a technology which is going to allow you to lend expertise. Unlike the past where you almost lend information, you lend expertise to humans. If you do so, the entry barriers for jobs are going to actually shrink.

The gap between occupations and the gap within occupations is going to shrink. So we think it's a great leveler. I call it the great equalizer. And you're going to bridge the gap between the ones who have skills and the ones who do not have skills. Unlike in the past, to access technology, you needed skills. And therefore, the diffusion was not as efficient. This is a technology where...

The interface is natural language. Because the interface is natural language, the diffusion is going to be much more efficient and very effective. So any technology which is built on one part of the world can diffuse to any other part of the world without any skills. And natural language is the interface. You know, so far, machines and humans...

When they interacted, humans wanted to understand machines much more. And that was the endeavor in all the tech disruptions which have happened. This is the first time machines are trying to understand humans, which is the other way around. Therefore, I think the diffusion is going to be super efficient. So the excitement is all the tech disruptions created a digital divide. This is a tech disruption which would bridge the divide. And if we can anchor this well,

with the right levels of trust, right levels of equity, right levels of safety, we could actually, you know, bridge that divide which was caused by the past disruptions.

If I'm a listener, what should I be doing? What should I be prioritizing with my teams to make sure that, you know, I can make this transition, these early stages as powerful and effective as possible? What should I be focusing on? Is there one or two things I should be focusing on given that equity piece, that safety piece, the productivity piece? What should I be focusing on?

One of the biggest constraints for this technology, you know, if you take the full stack, it has neural networks on the top. The architecture is neural network, transformer-based. The compute is very advanced, and the data is internet-scale data. And if you put all these three together, it is a very, very powerful combination. So,

The things which enterprises have to focus on is to get the foundation infrastructure right for technology. The thing which they have to focus on getting it right for human capital is to identify jobs which will get disrupted, identify the tasks in the jobs which will get disrupted, identify new tasks.

So that the human potential can be amplified and identify the skilling needs. These would be the three things. Technology infrastructure so that you could embrace it.

identify the jobs which will get disrupted, identify the reskilling needs to get to the new jobs. There's been a lot of talk about reskilling for AI. And I think sometimes it's unclear for leaders how that might express itself in their particular organization. And I think it's particularly interesting what you were saying that like, hey, the biggest shift is going to come from the place we least expect it.

So if I'm looking at my workforce and there's an area that maybe hadn't been able to sort of see a step change, you know, how can I bring that step change to that group? What should they be putting into place? Or is there a question they should be asking themselves to drive that forward? If you look at jobs in general, in all enterprises, in all occupations, most jobs have been drawn from the Industrial Revolution.

The Industrial Revolution set the template. The template it set was you kind of go to school for the first 25 years of your life and work for the next 50 years and then retire. And that's a template we've drawn irrespective of the change which has happened around us. This is a unique moment for us to disrupt the template. That template is out of the window. So I would believe that

You have to intertwine education and lifelong learning into the work template. We can completely disrupt the template of the past and look for apprenticeships at the front end and actually look for learning templates in work and intertwining lifelong learning templates in it. So I would say that's a big step change.

to how we actually define jobs in our workplaces. The second important thing I would say, work has always been defined for solving problems. Problem solving was the human endeavor at work. With machines and humans working together to solve problems, the next human endeavor is going to be finding the next purposeful problem.

So the cognitive diversity needed in workplaces is going to be very, very different. In the past, the cognitive diversity needed in workplaces was kind of more indexed towards STEM disciplines. Now what you need, because machines are going to actually partner with you to solve problems, the human endeavor is going to be to find new purposeful problems. You need non-STEM disciplines like human sciences, liberal arts, anthropology, sociology, psychology.

You know, these would go much more mainstream into work. So I do think the diversity at workplaces is going to be very, very different in the future.

You are helping to lead a new ICT community at the Forum. Can you talk a little bit about what drew you to it and also why it's going to be all the more important to be sort of pulling ideas from across different leaders and sectors to really make the most of this opportunity right now? Tell me a little bit about that. You know, we are living in the golden age of technology. Every industry is a tech industry. Every business is a tech business.

So the ICT community can never find itself in a better spot than what it is today. It's at the intersection of every business, every technology and every community at the WEF. So I do think we have a lot more to contribute to the shared purpose of and the mission of the World Economic Forum. So I would say we charted out four objectives and looking at the new disruption which is coming on the way, which is

generative AI. The first is, what does it do to human capital? Second is, what happens to the infrastructure needs? I mean, the amount of compute, the amount of energy needs for this new technology is just mind-blowing.

How do we solve that problem? I mean, just look at the compute costs and the compute needs which are going to come on the way. The third is how do we find purposeful use cases of generative AI? Or for that matter, any technology which is coming on the way. And lastly, responsible AI. I mean, unlike technologies of the past where safety and equity was good enough for the technology to be enabled, this is a technology that

where trust, safety, and equity, all three play a very important role. The reason is because of transformer-led machine algorithms, you're going to find output which is going to come out of it almost from a black box. It's going to be more generative in nature and that's why it's called generative AI. So,

If you have output which is going to be more generative, you need to build trust, you need to build traceability, you need to build explainability of the model because this is technology which is going to amplify human potential. It's going to support humans and decisions. Sometimes it's going to take decisions on behalf of humans. So you need to have a human in the loop to do this. So the whole responsible AI framework and the regulation attached to it is what the ICT community is going to work on. So these are the four pillars and the four objectives

at least for the next 18 months. As we progress on this journey, we hope to immerse this into all the other industries. I mean, the impact on jobs is going to be in every industry. The impact of

AI is going to be in every industry. So we are very, very keen that we are at the center of this transformation, which is going to happen in the world. You were trained as a nuclear scientist. I have to ask about this. How does this sort of help you maybe learn about new advancements? Or how does this sort of help guide you and your decision making and choices in a way that somebody else wouldn't have? I've been very fortunate to start my professional career as a scientist. What it does, what it curates,

is a sense of curiosity in your mind. And curiosity is a very important trait in a changing dynamic world. So that is something I actually bring. The second important thing is when you're working as a scientist, you're always building hypothesis.

And you're testing the hypothesis with data and you're validating it and then you're rebuilding your hypothesis. So the ability to bring that thinking to business enterprises, I think is fascinating because when you get to business enterprises, decision-making is a combination of experience, intuition, and data. And building the thesis, building the hypothesis, tweaking it, iterating it, creating iterative approach, and the ability to start to see what is coming on the way

Assimilating that to make impact for your business, I think is what I love. And my initial days as a scientist has helped me to draw that mindset into the work I do today. And the work I do today is at the intersection of technology and human capital. So it's kind of so apt.

Do you think that this tendency to sort of want to have a hypothesis, but then test it out, and you can only do that in an organization across a lot of teams, a lot of people, do you think that that sort of helps make a more collaborative environment as opposed to maybe a top-down environment? So someone who's looking to sort of build change, maybe that's like a framework that they can apply. Hey, we've tested, experiment, we use the whole team as opposed to

here's how we're going to do it. Do you think that that would be a helpful thing that people could apply? I mean, you're absolutely right. You know, one of the things which new age companies work on is not hierarchical structures, but network structures.

I assimilate community knowledge from my employees and build things which make my institution resilient. I assimilate knowledge from my clients and wire that information back to the offerings we can actually bear. It does help me to do that. It does give a little bit of, as I said, the ability to take decisions on gut, but the ability to actually support it with data. It's a virtuous cycle of gut, data, gut.

You start a thesis on gut, you validate it with data. And when you get close to 60 to 70% of conviction that it is the right decision, then you start to make that decision because you don't want to stay behind by waiting for that validation all the way to 100%. So I have a thesis in my mind, you should at least get to 40 to 50% conviction for a decision, but you should not cross more than 70 to 80%.

by the time you take the decision, because otherwise you're going to be behind the curve. You're going to be delayed. So the ability to calibrate that with your teams in a network structure, the ability to see what is coming. And, you know, when you're working in large companies, I have 340,000 plus employees, seeing what is coming

is a virtue. I can connect the dots at my vantage point because I meet policymakers, I meet clients, I meet employees on a daily basis. Seeing what is coming is a virtue, but making everybody believe

on what is coming is a much bigger virtue. So building the trust with people so that they can start to believe what they don't see, but they see it through me and they actually are convinced to rally behind me, I think is an important trait, at least in companies like ours, where human capital is our asset. As a relatively new CEO at Cognizant, what's a point where you have applied this experimentation thing so we can kind of see how that has expressed itself?

I'm a believer to surround myself with people who are not like me. I'm a believer to surround myself with people I can work with, but I should be able to work with them even if I disagree with them. So I have a lot of things around me which are very heterogeneous. Growth lies in heterogeneity. So I've always experimented with heterogeneous thinking around me. So you pop up a thesis,

If you have a heterogeneous leadership around you and not people like you, they're probably going to disagree with it. So the art of persuasion

is an important art. It's an art to get people who disagree with you to work with you and get people to work with you in spite of their disagreement. So, you know, all the thesis building sometimes is from your standpoint, from your vantage point, but you should be able to stand it down when you want to, when you believe it's wrong and you should be able to take over somebody else's thesis and adapt it and make it believe like it is yours.

I think is institutional strength in a company like mine because when I have 350,000 to 40,000 plus employees, I am going to find heterogeneity.

Is there an easy habit that people can build so that they're sort of modeling this again and again and again, and that value becomes a truth? What's a way that people can make sure they build this in their organization? I would say psychological safety. If we can build psychological safety, we can build great teams. Psychological safety ensures that you can voice your disagreement. You can open up your opinions, which are very diverse.

And psychological safety allows you for people to disagree with you and feel comfortable about it. So psychological safety in big teams, I think is a very important trait to build successful teams, to build successful teams who can thrive on that. The second thing I would say, this is my personal strength.

I believe vulnerability is a strength. It's not a weakness. So as a CEO of the company, if I'm able to express my weaknesses and if I'm able to ask questions, which I should not be afraid of, I think it gives a sense of comfort for the rest of the company to stay vulnerable. So I'm a strong believer that I should be vulnerable. I actually thrive on it and I want to stay humble and hungry.

So that I look for more and I don't feel overwhelmed with the success around me. I don't feel overwhelmed with the failure around me. Is there a big goal or something that you are prioritizing for 2025? You know, 2025 is going to be a fantastic year. It's an unusual time for CEOs. If I go back to the last 30 years, I've seen periods of change. I've seen periods of uncertainty.

I've very few times seen periods of change and uncertainty coming together. It's an interesting conflict. The period of change is because of the extraordinary technological advances we all discussed today, which is the generative AI-led technological advances. And that is going to profoundly impact how the world is going to shape. The period of uncertainty is because of the geopolitical uncertainty around the world.

When both of them come together, they have conflicting natures. Change is forward-looking. Uncertainty is going to put you on a status quo or put you on a limbo. So how do you tackle the two and still make progress? I think it's going to be a very interesting opportunity for CEOs to navigate. How will you approach that?

You know, the ability to take bold bets, believe in yourself and stay ahead of the curve in spite of the uncertainty will allow you to break the deadlock and will allow you to look forward to the future

rather than being worried and being tentative about the present. So that's how I would approach it. And you need to have the strength to back your ideas at a time when there will be a level of mutinous and uncertainty. Is there a book you recommend? You know, one of my favorite books is Think Again by Adam Grant. He's a fantastic author. It's a book which talks about

how important it is to rethink and to unlearn. And in a dynamically changing world, rethinking what your beliefs are and unlearning what your strength is, I think is going to be a very important trait. So I think again, is a fantastic book, which kind of propagates this philosophy. So I love that book. What's something that you've unlearned lately?

As a CEO, you're always impatient. So how do you make sure that you change the velocity and calibrate it to the speed of how the company can run with and then influence it and catalyze it? The second unlearning is I've always believed when I was not a CEO that working on direct control is a big strength. What I've learned now is working on sphere of influence

is a much bigger virtue than working on direct control. And working on sphere of influence, I think is again, a much more sustainable virtue, much more sustainable way of making change. Is there one piece of advice that you've just always been grateful for and that it has always served you? I would say being vulnerable, being vulnerable and staying hungry. When you are vulnerable and when you're staying hungry,

Humbleness is actually the foundation of it. These are three things which have always grounded me. Sometimes you could be overwhelmed with success, which will take away the authenticity of who you are. Sometimes you are overwhelmed with failure. If you're too much onto the fact that you've failed, you're never going to lift yourself up and come out of it. Being vulnerable and staying hungry for the next big thing

I think has been my strength and or rather that's been my motto on how I approach my job, how I approach my life. That was Ravi Kumar. Thanks so much to him. And thanks so much to you for listening.

Cognizant is a champion of our Reskilling Revolution initiative, looking to reskill 1 billion people. I'll have a link to that in our show notes, as well as our Future of Jobs report that just launched this week. That's just one of a slew of insights launching at this year's annual meeting. My colleagues and I are breaking down the latest research all month. Do not miss a single session or insight. Follow for the latest on social media with the hashtag WEF25.

Find a transcript of this episode, as well as transcripts from my colleague's podcast, Radio Davos, at wef.ch slash podcasts. This episode of Meet the Leader was produced and presented by me, with Jerry Johansson and Taz Kelleher as editor, Edward Bailly as studio engineer in New York, and Gareth Nolan driving studio production. That's it for now. I'm Linda Lucina from the World Economic Forum. Have a great day.