C Vijayakumar, thank you so much for joining me. So, when you first heard about ChatGPT, was it fear or joy? What was your first instinctive, intuitive response?
Thank you for this session. I think the first thought was curiosity. And when I used it, it was definitely a happy, joyous reaction because it's simple to use. Initially, whatever we could see was very good. So that was a very positive thing.
So as you started thinking about how it would flow down into your enterprise at HCLTech, what were the next thoughts?
While ChatGPT might have gotten 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 three or four 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. It was a very familiar theme: how can you now leverage generative AI to further this whole software development paradigm? I personally saw it as a big opportunity because if you had a bit of a head start and were proactive in leveraging this technology, we could create distinctive propositions. That's how I saw it.
Right. And when we talk about human centricism, why are we talking about human centricism today, and if that is an issue, how is it dealing with the larger pursuit of efficiency in technology?
I think it's more than human centric. The technology is really amplifying human potential. That's the way we should look at it. If you can become more productive, it frees up your time and cognitive capacity to do something much more valuable. If you approach this with that paradigm, first recognize that it will increase productivity significantly, then ask how you can leverage that human capital that is getting released to create new value. If you approach it like this, you will come up with different answers on how to leverage the human capital unlocked by productivity.
Today, the services industry is largely focused on input metrics. Over the last decade, we've moved more to output, but eventually we need to transition from an input-centric model to more output and outcome-centric. For example, can you create a product for a client and get paid based on how successful it is in the market? That mindset will change the current services model, which has grown linearly with people and revenue for the last 30 years. Now is the moment for decoupling. We're already seeing it: more outcome-centric, platform-based, IP-based services. These are the shifts we need to make. It's not completely new; some segments already operate this way, but we need to amplify it. What's propelling it is the productivity unlock from generative AI. In software development, we think there is 20 to 30% productivity improvement possible in the entire end-to-end life cycle. We built a platform called AI Force that uses traditional language models but covers the full life cycle: design, deployment, support. For example, making a change to existing software might take three to four weeks for impact analysis; with generative AI, you can get that output in less than half an hour. That's the kind of change unlocked.
So if I can ask you to illustrate once again. Let's say you were working for a big bank or a retail chain. What kind of problem would they have given you 10 years ago, how would it be solved through the stream, and how would you do it differently today to reflect the productivity savings you're talking about?
A good example is a financial services firm where we are part of a very large transformation program. The client is spending almost a billion dollars a year on a five-year program, and we're probably in the second year. With generative AI, we have showcased 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 important is time to market. If you can launch the modernized platform one year ahead, that creates huge business value. These are the conversations we're having. It's fundamentally different: how can you lead clients to showcase that you can do something much faster, creating faster time to market? A lot of this is still rolling out.
So how are you able to predict substantively that this is the cost saving you will be able to bring in, for example?
It's an iterative process. We constantly engage with customers through what we call 'art of the possible.' A study done in a limited way demonstrates you can do things faster, but that doesn't mean the entire thing can be done. You have to onboard the client; they must be willing to walk the path with you. You define an art of the possible, walk the path together, and there will be changes along the way. As long as you have a good understanding that it's new technology and change management is significant, you need the client's cooperation and full involvement. You really have to onboard them in this journey, and the outcomes can be shared.
So when you talked about the art of the possible, what is possible today that you could define for people watching this, and what is not possible today?
All productivity unlock is still happening with a human in the loop. I do not foresee that a lot of this can be done completely independent of humans. That's a misconception we need to deal with. But the involvement of humans can be much lesser. For example, someone who used to develop code now needs to validate code. That doesn't mean programming basics are not required. You still need strong programming concepts to be a good developer and deliver quality code. You need to understand architecture and how to break work into smaller pieces. You can do that much faster through right prompting. So it's not that everything is being replaced; fundamentals remain the same, but you can do things faster in certain segments using technology.
And when you talk to clients today, how are they defining their expectations? This is more of a market question. The marketplace is unpredictable, always was, but maybe due to geopolitical reasons there are more layers of unpredictability. So what are they asking?
The reaction from clients is very mature. They understand the technology is new and things are changing 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 done by us because change management is very big. Do we use carrot and stick or more carrot? That approach must be agreed with the client, and that gives the right roadmap. Clients don't have unreasonable expectations, but you need an open mind that you can have very different outcomes and levels of productivity, and jointly go after it. That's the journey we are working on with many clients.
And as you do that, do you see clients coming and saying, 'This is my transformation story and you're working with me on that, but I want you to tell me how cocoa prices are going to move or how I'm going to get more customers in this store' – something more fundamental to predicting their future?
