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Episode 1.3: The Great Equalizer - Ravi Kumar, CEO of Cognizant and services tech visionary.
589 Plays4 months ago
In this episode, Phil Fersht interviews Ravi Kumar S, CEO of Cognizant, to examine the shifting dynamics of the tech services industry. They explore whether the recent industry slowdown is a fleeting downturn or indicative of deeper structural changes, while also unpacking the ripple effects of rising capital costs and geopolitical turbulence. Ravi talks about how companies are recalibrating their focus toward more sustainable, value-driven technology investments, moving away from discretionary spending.
Drawing on a study with Oxford Economics, Ravi challenges the common narrative of AI as a mere cost-cutting tool, positioning it instead as a catalyst for amplifying human potential, bridging productivity gaps, and driving economic growth. He draws parallels to past tech revolutions like offshoring and cloud adoption but argues that AI holds a deeper promise - one that could not only streamline operations but also dismantle technical debt and revolutionize software development processes.
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Transcript
Introduction to 'From the Horse's Mouth'
00:00:12
Speaker
You're listening to From the Horse's Mouth, intrepid conversations with Phil First, ready to meet the disruptors who are guiding us to the new great utopia by reshaping our world and pushing past corporate spin for honest conversations about the future impact of current and emerging technologies. Tune in now.
Interview with Ravi Kumar
00:00:34
Speaker
Good to be back chatting with Ravi Kumar today, who's needs a little introduction to our audience, but he is the CEO of Cognizant. and I'd love to connect with Ravi a bit about where our industry currently is and where we think things
Tech Industry Changes
00:00:51
Speaker
are shifting. i mean It's been kind of sobering maybe 18 months for our industry, Ravi. What best describes to you why there's been a change in mindsets, maybe a slowdown in some of the rapid growth we've seen. And you know is this a secular change or is this a temporary thing? So, Phil, I would say some of it is temporary and transitionary and some of it is a structural change.
AI's Role in Cost Reduction
00:01:19
Speaker
First of all, the cost of capital has gone up significantly. While there is uncertainty around the world, the geopolitical situation
00:01:28
Speaker
I mentioned this before that we have never seen a period of change and a period of uncertainty coming together. The change because of the technological advances of AI and the uncertainty because of the geopolitical situation around the world. But overall, the economic uncertainty has led to, you know with with inflation and everything else, led to higher cost of capital.
00:01:56
Speaker
And the higher cost of capital almost warrants that the tech deployment costs, tech development costs actually go down. It has happened before. Once it has happened with the advent of cloud, it has happened once before with offshoring. It will happen again. And this time around, there's a pull and a push. The pull is with the advances of AI, you could apply it on tech. I call it tech for tech.
00:02:24
Speaker
and The push is the higher cost of capital will force enterprises to revisit the discretionary spend. If you want to divert it to technology, it needs to be much more viable.
00:02:39
Speaker
And the ability of using AI on tech to reduce the development costs, the software development lifecycle costs will allow you to get there. So that is the permanent shift I'm seeing. The temporary shift is the combination of interest rates and the geopolitical situation. So that's broadly how I see it. Discretionary was at a throwaway price before.
00:03:02
Speaker
I mean, you could experiment with millions of dollars because the cost of capital was so cheaply available.
AI's Focus on Productivity
00:03:08
Speaker
So that's going to change publicly. We've seen a shift in the attitude towards AI deployments just in the last year, I think. We've just got hold of some new data from the Global 2000 that shows cost reduction is now key, particularly amongst AI deployments. so How can organizations ensure that these technological evolution complements human creativity and emotional intelligence and it's not just driving out more and cost and at that type of impact? One of the biggest levers for any tech discontinuity on enterprises is productivity.
00:03:49
Speaker
I know you start with productivity, then you move to innovation, then you move to, like all tech discontinuities of the past, AI's primary pivot in the short run is for productivity and task-based productivity, task-led automation. Now, productivity has been plateaued across the world for the last 25, 30 years.
00:04:15
Speaker
and In fact, one of the biggest ah drivers for technology to be applied in workplaces is higher productivity. I mean, the information age happened in the late 80s, but the productivity really came in early 2000.
00:04:31
Speaker
So the first and the foremost pivot to AI led transformation in enterprises has to be productivity. We did a study in partnership with Oxford Economics. We found out that 44% of our clients, in fact, we interviewed 2000 global enterprises. 44% is related to productivity. 36% of them have spoken about innovation being the reason why they did.
Amplifying Human Potential with AI
00:04:57
Speaker
And of course, a small portion of them for redesigning their The problem is pro productivity has not been measured. It has to be measured at every row, every occupation, so that you could repurpose jobs from a set of tasks they do today to a set of tasks of the future. The last time we did something like this was when robotic process automation happened, and it was a flawed model.
00:05:26
Speaker
We relegated humans to the back end of the customer service value chain and we removed cars and we completely complicated the customer service function. And that was where it got applied the most.
00:05:41
Speaker
We are now stepping into an era where AI is in some ways going to be less about removing cost, more about amplifying human potential. So that process is going to lead to higher productivity, higher per capita income, higher output. In the process, the cost of moves are not going to go up. Wages are going to go up.
00:06:10
Speaker
And in some ways, the prices of goods will remain constant. So I'm hopeful that the pivot this time is going to be more towards productivity and less towards reducing cost. And over a period of time, that would lead to more innovation, newer products, ah newer revenue streams, and redesigned operating models. Just imagine if productivity today, which is just 1% globally,
00:06:39
Speaker
goes up to 2% to 3%, which did happen in the early 2000s because of the information age. It would add $10,000 to $15,000 per capita income just in the US. So I'm very hopeful that the new pivot for AI is going to be productivity-led. The more productive will gain less, the less productive will gain more, and therefore it will be an equalizer.
00:07:06
Speaker
We should look at AI as a way to reduce entry barriers to jobs. You're going to see a higher number of journalists who are lending expertise. You would see a gap between our occupations going down. You would see a gap within an occupation going down. This will result, this you know if we pivot it rightly, it will result in multiplying our own human capabilities, AI assistants around us.
00:07:33
Speaker
That is the future we're going into. i mean The co-pilot, as we call it, or a teammate or a coach or a genie attached to us to amplify that human potential. and and leveraging the human endeavor for more value-added work will drive the future. I think you've summed it up with this shift from cost reduction to productivity improvement because the two used to be, I think, confused. and I think your writer on RPA was too focused on taking out cost and taking out human labor rather than thinking
00:08:06
Speaker
I'm going to hire 100 Ravi's to do these tasks for me. Now I can hire the same 100 Ravi's to do these tasks for me, but these Ravi's are super intelligent because they're using agentic software, AI software to be more productive and more capable at the work they're delivering.
Post-Pandemic Work Environments
00:08:24
Speaker
Now, how does a company like Cognizant e evolve into that type of environment where you can generally go to your clients and say, look, we can provide you the same number of people, the same type of engagement, but the value is going to be so much more productive. Do you think clients are ready for that? and How do you see that transition happening? We as an industry have gone through these transitions a couple of times before. When offshoring happened, the cost of deployment went down, the amount of technology consumed went up.
00:08:58
Speaker
Because technology is elastic. If consumption is elastic, you could cannibalize yourself, do more for less, and in the process, create more consumption. The second time when it happened was with the advent of the cloud, where the plumbing to building ratios changed. And when that happened, more human effort was leveraged for building while plumbing was automated. More technology got consumed.
00:09:26
Speaker
because technology is elastic. With AI, one of the biggest use cases is to apply it on your own software development cycles. If done properly, integration of AI into human effort is an important capability set. If you can integrate it well, you get 30% to 40% productivity.
00:09:44
Speaker
That will get transferred to clients because this industry, the tech services industry is very efficient. So it diffuses very fast. And as it diffuses, you're going to see more value to the front end of the chain. And if that happens, you're going to transfer that cost back to clients, which means the backlog will go there. Every client of ours has a backlog that will go there.
00:10:11
Speaker
You will see technical debt coming down. In fact, just in the United States, there's a report which talks about how there is $1.5 trillion dollars of technical debt, technology debt sitting on ah books of enterprises. We use half a trillion dollars to service that debt because we don't have financial capital to retire the debt.
00:10:34
Speaker
We don't have tribal knowledge and we don't have legacy skills like COGOL. You could pretty much leverage AI to take out some of that constraints. You know, financial capital will be lower. Tribal knowledge can be institutionalized. Lack of legacy skills can be overcome by AI. And if you do so, you're going to reduce technical debt. More technology will be consumed in enterprises. Some industries have very low tech intensity.
00:11:04
Speaker
and those industries will absorb more. so I actually believe that doing more for less will actually drive more consumption because of the elasticity of spend of technology. If we do this in know more in a constructive way,
00:11:22
Speaker
We can go back to clients and actually generate more momentum with the concept of doing more for less. That will lead to more work for us. That's how I see this and that's why I'm super excited about ah what AI can do to our operating model, in turn, what it does to technology and the landscapes of points. Equally, the application of AI into business landscapes, into operational jobs, I think is very, very important. In fact, one of the findings of the Oxford study we did, 90% of the jobs will be disrupted, 50% of the jobs
00:11:57
Speaker
will be significantly disrupted. When that disruption happens, we actually can start to think about what are the tasks those jobs had, how do you map the tasks of the future jobs and map it to what would be human effort and what would be machine effort and integrate that entire plan to create jobs of the future where machines and people work
Cultural Shifts in Enterprises
00:12:22
Speaker
together. It's a way of thinking nonlinear.
00:12:25
Speaker
It's a way of scaling without growing, as I call it. It's a way of giving the small the same advantage as the big. Remember the cloud did that. The cloud actually took the capital barriers out and created the same advantage for the small as the big. You could take technology on the tap.
00:12:44
Speaker
This is another leap and I call it small gets the advantage of the bank you could almost say an enterprise to the version where you could scale without growing every function of an enterprise will get refactored so that you can allow small teams to scale without growing on a stack i mean a modern agent based.
00:13:05
Speaker
intent-driven AI stack will replace classical, functional-driven stack of tools. so It's going to be an exciting, transformational phase. so You've managed to articulate four of the five debts that we write about, technical debt,
00:13:22
Speaker
Skills debt, process debt, data debt. There's a fifth debt we think is Paramount, which is culture debt. And you mentioned a couple of times, this is a big mindset shift more than anything else. It's easy to think about the how practically we can do a lot of this stuff.
00:13:38
Speaker
but Ultimately, there's a cultural shift that companies have to go through. Where do you think we are with that and how hard is this going to be, not just for services firms like yourselves, but your big enterprise clients to overcome some of these cultural hurdles that are facing them? i think That's a fascinating question, Phil. i mean Of course, you've touched upon the intangible aspects of this transformation.
00:14:01
Speaker
and culture is in the middle of it. As much as this looks like a hard shift, there is a soft shift as well. As you shape enterprises which have gone from a hub and spoke model, an enterprise organizational design has always been hub and spoke. You have central headquarters, which is the hub, and then you have spokes across the world. You're going to go from there to a networked organizational structure, which is going to be headless.
00:14:28
Speaker
Many enterprises now, and I know a few of my clients, were starting to think about, I would call it the enterprise 2.0, where you build a network organization where technology and ARPs are intertwined. They're no longer in the headquarters. They're actually and distributed across the world. Already the tech capabilities of most enterprises have been distributed across the world. You want to revisit and see if ARPs has to be distributed and there has to be in close approximately to tech.
00:14:56
Speaker
because tech and ops are intertwined. Entrepreneurs are able to revisit what they will insource and what they will outsource. That's also because the core is changing. I mean, at one point of time when outsourcing happened, tech was non-core, and today tech is core. So how do you bring that back into your organizational muscle? I think it's going to be very important. So building culture, creating the rhythms at work, thinking nonlinear,
00:15:22
Speaker
Thinking about scale without growing your teams, I think are very interesting cultural nuances enterprises have to adapt. And it is going to be an interesting shift as we go forward, because cultures where you had this buzzing offices, which were headquarters of companies, where walking the corridors, you would feel what the culture is.
00:15:45
Speaker
You will now have to redefine that in a networked organization. and Remember, we are no longer just networked, we are networked and hybrid. Hybrid because of the post-pandemic era, we have landed in a hybrid environment. So networked and hybrid, thinking nonlinear, thinking scale without growing, distributed organizational structures,
00:16:05
Speaker
I think it's just going to create a confluence of things which will generate a very different culture for enterprises. We're also going to move from organizations which have built specialists over a period of time to buy functional broad-based capabilities.
00:16:21
Speaker
where data sciences and the arithmetic is going to be at the core of all the other things you do is also going to create a very different culture. There's also one other aspect for you and I have discussed in many podcasts before, which is about problem solving being the endeavor of machines, while the new human endeavor is going to be finding new problems.
00:16:42
Speaker
which means businesses of all kinds will have to hinge on human human ingenuity and creativity will be the source of new products and services because that will be the human endeavor, which also leads to a different culture and a different organizational construct.
Global Talent and GCCs
00:16:58
Speaker
So I think you've touched upon a very, very interesting point on how cultures will evolve in enterprises.
00:17:04
Speaker
We've seen a shift towards you talk about this outsourcing of technology when it was non-core to now it's coming up to a core and we're seeing a heavy reinvestment in global capability centers and i think part of this is clearly around companies wanting more control over quality control over value.
00:17:24
Speaker
Do you see this as a long term trend towards a centralization of talent, in particular in locations like India, that are managed in a different way than they have been traditionally? Where do you see this trend going? This is certainly a big trend. I mean, right now,
00:17:42
Speaker
1.6 million and professionals in India work in GCC's Global Capability Centers, which is one third of the Indian IT workforce. Almost one third of that capacity got added in the last literally two years, and it is growing. So I don't see that reversal of trend. I think it will go on for some more time till you reach an equilibrium.
00:18:04
Speaker
where you start to believe that whatever you have in-sourced, you've been sourced. I want to go back to the conversation we did a few minutes ago. There is a revisit of what needs to be in-sourced and what needs to be outsourced. Till you get to that equilibrium, that trend will continue. The second thing, Phil, which is happening is the last one-third which got added in the last two years is more of ops and less of tech.
00:18:29
Speaker
So this is going back to what I said, which is co-locating ops in close approximately to tech because they are intertwined. So the concept of having your ops in and around your headquarters is going to go away. The concept of having your ops closer approximately to technology is real. So the re-architecting of the 2.0 organization structure for most enterprises is starting to happen.
00:18:58
Speaker
And that is also leading to the GCCs. So there is a revisit of the networked organization, revisit of tech and ops being co-located, and of course, revisit of insourcing of your core versus what it was before. So all three coming together, there is an influx of GCCs in India. But after a point, you will also know that it's a different labor market.
00:19:20
Speaker
So in a different labor market where you are vying for talent, not with your peers, you're vying for talent with companies who are not your peers in different industries and companies who do this for a living, like companies like ours, you will get to that point where you will believe that it is no longer viable for you to build it yourself.
AI and Equal Job Access
00:19:41
Speaker
It will get to, ah I would say, a circuit breaker where there will be a little bit of a reversal. Equally,
00:19:48
Speaker
You should not in source only because of arbitrage of labor. You should only in source if you can do arbitrage of if you can nullify the arbitrage of labor and nullify the arbitrage of technology. I mean, a lot of times you want to hand it over to a partner to do this because they not only can do it for labor, but they also can do it for the technology arbitrage. So the tooling and the instrumentation of AI which will also drive that equilibrium that you use a partner who is more equipped to do this. I think it's fascinating the fungibility of talent across different industries. It's a big change that I think is much needed in our industry. Final question is, will the future be equally distributed, Ravi?
00:20:36
Speaker
If I look at the lens of access to good jobs, I would say AI is a great equalizer. In fact, our own study field says that the top 50% of my developers gained only 17% and the bottom 50% of my developers gained 37% productivity being equipped with AI tooling. So I do think it is an equalizer to that extent.
00:21:00
Speaker
So if I look at it from the lens of capability and the lens of access to jobs and the lens of entry barriers to jobs, it is a good equalizer. Unlike other technologies, I mean, digital technologies created a divide in many ways. The ones who had the tools and the ones who could use the tools leveraged the highest potential of it and the ones who couldn't were left or behind.
00:21:25
Speaker
Some industries were left behind, some economies were left behind, and some individuals were left behind. This is a technology where, for the first time, natural language is the interface. Computers are trying to understand what humans do versus is humans trying to understand what computers do. And that leads to the point that this is a technology which will diffuse very fast.
Key Insights and Wrap-up
00:21:50
Speaker
because the barriers of tooling, the constraints attached to its diffusion are no longer there. Economists use this model called the Basque Diffusion Model, where they apply the model to every technology wave and they discount the impact of the technology.
00:22:07
Speaker
And economists now say that on the Basque diffusion model, this is probably the least discounting because it will diffuse so fast. I mean, you know technology built in the United States will diffuse to a farmer in India because the farmer in India can actually, on a local dialect,
00:22:25
Speaker
interact with the technology and not just use it for information sake, but use it for expertise. So I do believe that could be we a potential equalizer. The question is whether the companies which are involved in the models, the companies which are involved in the chips,
00:22:41
Speaker
Are they going to keep the value or the value will diffuse to the front end of the chain? And if it diffuses to the front end of the chain, I think this will be a big equalizer. So far, that value has not diffused so much. So we don't see it in front of us, but based on everything I know about the nature of this technology, it should be an equalizer. And therefore, the distribution should be much more efficient.
00:23:03
Speaker
Fantastic. This has been a wonderful conversation, the ability to scale without growing, the impact of culture on changing what we do, the commoditization of legacy, the whole change of the workforce, and the increasing core of technology at the heart of the business. This has been an amazing conversation, Ravi, really. Look forward to sharing our conversation with the world, and thank you very much for your your time to today.
Closing Remarks and Invitation
00:23:29
Speaker
thank you phil Thank you for always pushing the boundaries and trying to get the best. It's always about the interviewer, then the interviewee, if you start to make me tell things which I never did before. Yeah, I know we cover the whole spectrum around these five decks and where it's all coming together for the future. So I enjoyed it very much and look forward to more of these discussions with you. Perfect. Thank you so much. Thanks for the opportunity.
00:23:58
Speaker
Thanks for tuning in to From the Horse's Mouth. Intrepid conversations with Phil first. Remember to follow Phil on LinkedIn and subscribe and like on YouTube, Apple Podcasts, Spotify, or your favourite platform for no-nonsense takes on the intricate dance between technology, business and ideological systems. Got something to add to the discussion? Let's have it! Drop us a line at fromthehorsesmouthathfsresearch.com or connect with Phil on LinkedIn