Srinivas Pallia
Chief Executive Officer
Having said that, the specialist in AI, you know, to be honest, is not just driven by models. Rishi? For us, having the client context, understanding the domain and industry aspect of it, understanding the process, Rishi? And the you know, driving the data for an AI implementation becomes very critical. And also, you know, clients are looking at security and change management, organization change management. In this context. So that is where I would say that, you know, the direction that, AI is moving on. And for us, Ravi, you know, very clearly, we are pivoted to AI. And in you know, we are doing an AI first approach. And our consulting led you know, you know, AI power strategy is all about that. When you are doing a run aspect of it, which is application management infrastructure, or in a process. We are doing with the AI first approach, and, we are clearly built a strong platform around things, which we are gaining very, a good traction, which is our delivery platform. And the second thing, you know, I mean, obviously, you are busy. Now listening to a lot of commentary around that, the software development life cycle, there is a dramatic improvement in productivity. Now the I do not know. We have to have the context of if it is a pure play green project, which is like a tool, like a, let's say, Python, the productivity is significantly higher. But on the other end of the spectrum, it is a complex code. And, you know, if you do not have the right, you know, target environment which is dot 4 legacy, deployment and production also becomes difficult. There, the productivity, you know, comes down, significantly. And so that is how we see it. But for us, the biggest opportunity is all the new AI services that we are seeing in the market. Now we call that as reimagine AI. Now, I think it is very important also, you know, what we are trying to do. Maybe I will double click later, but we have clearly created the AI native unit which I talked about. We are building the industry and cross industry platforms. In fact, some of the, you know, margin dilution that you talk you know, the question that was asked, investing in this. I think it is very important for us to invest for the future. So that is number 1, AI native unit. Second, no. We have the half a billion dollar Wipro Ventures, and now we are specifically focused on targeting AI and data and, you know, security startups. This will also enhance our overall Wipro intelligence platform. 3. We invested in our Wipro innovation network. We actually launched the innovation networks for our clients, and that is actually picking up. The clients are co innovating with us in those innovation network. And finally, you know, ecosystem partnering with the frontier AI companies. So that is how we are driving AI. Across our industries, and each industry is different in terms of adoption. But everyone wants to be you know, in the AI journey, Ravi. Yeah. We said but I have 1 more thing. When you said that the much productivity benefit in the you know, the old complex code. So then can we say that there is all the investor concern about significant, you know, erosion on the existing book of business Can we say that this is really unfounded? So the way I see it, Ravi, is that, you know, I am looking at for the industry and for Wipro. What are the like I said, structural-- what are the structural opportunities? Today, if you look at the traction that we have, the reimagined AI services, that is how I call them, you know, new AI services. 1, AI advisory and change management. that is something that, you know, for example, Capco is leading it to kinda OpenAI gave us an award around that. So is data priming for AI. Rishi? You know, if you do not have the right and the enterprises are struggling with data. We have to be honest about that. Enterprises have told us we have got too much of data. We do not know whether it is we do we need all this data to get the AI right. 3. Is, you know, agent implementation and managing agents. Organization is building number of agents. How do you deploy them? How do you orchestrate, deploy, and manage them? And, Ravi, you know, the token tokenization, token economics, whatever you call it, it is going, you know, it is actually skyrocketing right now. So then they especially the CFOs are saying, you know, hey, you know, what is my ROI? So do I use a high end LLM for a particular process of the workflow? Do I use an open source model? So that is the conversation that is going on. We are having the deep tech, we are able to actually have that conversation with the client. So there are multiple, new opportunities, whether it is model ops, You know, EID is something that is picking up within enterprises. You would have heard of Sovereign AI. So that is another 1. And finally, every client wants us to make AI secure and, you know, responsible. So to me, NetNET is a positive, you know, in terms of new services that are coming in. Short term, SDLC life cycle will continue to bring in higher productivity and shorter development life cycle. But I just want to call out even there, human it is going to be human plus AI always. Because in a software development life cycle, the business requirement, the user stories, you need humans. At the same time, when you are deploying and taking into production, need human intervention. Of course, you know, AI can prove millions of lines of code, but we need to make sure that code is optimized. So that is how I see it, Ravi.