India’s AI Opportunity: Frugal Innovation & Global Impact | C Vijayakumar On What’s Next | The Core

Thank you for this session. I think the first question or the thought was curiosity, right? When I kind of used it, it was definitely a happy, joyous type of reaction because it's simple to use. Initially, whatever we could see was really very good. So that was a very positive thing.

Yeah, I think while ChatGPT might have got all the attention around generative AI, if you look at some of the technologies preceding it, like GitHub Copilot was being used for software development even 3-4 years ago, even before ChatGPT came in. So we had invested significantly to see how AI can be used in the software development life cycle. So it was really a very familiar theme where we can now leverage generative AI to further this whole software development paradigm. So I personally saw it as a big opportunity because if you had a little bit of a head start and if you're trying to be very proactive in leveraging this technology, we could create distinctive kinds of propositions. That's how I saw it.

Well, I think it's more than human centric. The technology is really amplifying the human potential. That's the way we should look at it. If you can become more productive, it just frees up a lot of your time and cognitive capacity to do something which is much more valuable. If you approach all this with that paradigm, first recognize that it is going to increase productivity significantly, then say that the increased productivity, how can I leverage that human capital that is getting released to create new value? If you approach it like this, you will really come up with different answers on how to leverage the human capital that gets unlocked due to the productivity.

Yeah. Today, I think the services industry is largely focused on a lot of input metrics. Over the last maybe a decade or so, we've moved more to output, but I think eventually we need to transition from largely an input-centric model to more output and outcome-centric. For example, can you create a product for a company, one of your clients, and you don't charge anything for the product but you get paid based on how successful the product is in the market? That kind of mindset will change the current services model. The current services model, for the last 30 years, the industry has grown very linearly with people growth and associated revenue growth. Now is the moment the decoupling should happen. We're already seeing the decoupling, and that means more outcome-centric, more people-based services, more platform-based services, from just services to more IP and services. So these are some of the shifts we need to make. It's not completely new; already a lot of industry has some segment of their business in this model, but we need to really amplify that. And what is propelling it right now is the productivity unlock that generative AI is able to do. Whether it is software development, we think there is 20 to 30% productivity improvement possible in the entire end-to-end life cycle of software development. So we built a platform called AI Force, which uses some of the traditional available language models, but it really covers the end-to-end life cycle of software development from design, deployment, support, all of that. If you want to make a change to an existing software, to make a change impact analysis, depending on what the change is, sometimes it might take three or four weeks for an engineer or a team to come up with these changes. But with generative AI, you can get that output in less than half an hour. So that is the kind of change which is unlocked.

Yeah, a good example would be a financial services firm where we are part of a very large transformation program. The client is spending almost a billion dollars a year, and it's a five-year transformation program. We're probably in the second year now. With generative AI, we have showcased in a certain segment how the entire program can be done in 30% less time. So the five-year program can be done in four years, which is a billion dollar plus saving, but more importantly, the time to market. If you're able to get those features and capabilities, if you can launch the modernized platform one year ahead of time, then it's a huge business value that gets created. So these are the conversations we are having, and it's fundamentally different. How can you lead these conversations with clients to showcase that you can do something much faster that will create faster time to market? And a lot of this is still rolling out.

Yeah, so it's an iterative process. We constantly engage with our customers by what we call art of the possible. While a study done in a limited way demonstrates that you can do things faster, it does not mean that the entire thing can be done. So you will have to onboard the client. The client also should be willing to walk the path with you. You define an art of the possible, walk the path with the client. There will be some changes in the way, and as long as you have a good understanding with the client, it's a new technology, change management is very significant in this. So you need the client's cooperation and full involvement to make this happen. So you really have to onboard the client in this journey, and then the outcome you get out of this journey can be shared value.

I think all productivity unlock is still happening with human in the loop. I do not foresee that a lot of this can be done completely independent of humans. I think that's a misconception we need to deal with. But the involvement of humans could be much lesser. Somebody who is used to developing code now needs to validate code, but that does not mean that programming concepts and basics are not required. You can do everything through generative AI, but you still need very strong programming concepts to be a good developer to deliver good quality code. You still need to understand the architecture of how to break that work into smaller pieces. You can do much faster just developing the code through prompting, but it's not that everything is getting replaced. A lot of fundamentals remain the same. But how can you do things faster in certain segments using technology? And when you talk to clients today, how are they defining their expectations? The marketplace today is also unpredictable. It always was, but maybe in some areas, because of geopolitical reasons, there are more layers of unpredictability. The reaction from clients is very mature because they also understand the technology is new, a lot of things are changing very rapidly. The overwhelming conversation is let's do this together, let's look at the art of the possible together. It has a lot of dependence on the client; everything cannot be just done by us because the change management aspect is very big. Do we do carrot and stick or more carrot? What kind of approach you want to follow is something you have to agree with the client, and that gives you the right roadmap. It's not that clients have unreasonable expectations, but you just need to keep an open mind that you can have some very different outcomes, very different levels of productivity, and really jointly go after it. That's the journey we are working on with a lot of clients.