Jatin Dalal: Yes, and if I just add a perspective of the deals that we have won in last, let’s say 18 months, typically you would see that compared to what you expected at the time when you won the deal. Typically you will go sometimes faster because you are fulfilling better you are executing better than what you initially thought and customer thought and sometimes you would be slower because there are more change management issues than you need to deal with, etcetera. So I think we are we are evenly placed with the pace versus expectation. I don’t see anything out of ordinary. There will always be one of the deals that that is taking a little longer time to ramp up because there is some change in the client organization, but nothing that is out of ordinary on a win versus execution of the deal.
Jonathan Lee: That’s great color. Thank you.
Operator: Thank you. Our next question comes from the line of Jason Kupferberg with Bank of America. Please proceed with your question.
Jason Kupferberg: Thank you guys. I just wanted to start on GenAI. I kind of had a 2-part question there because I know, Ravi, you mentioned the rule of GenAI and accelerating software development a couple of times. Just curious what your longer-term views are on role of a human software developer will change as GenAI tools potentially do more of the actual coding and then just you mentioned 450 active GenAI client engagements. Can you give us a sense of the average project size there? Thank you.
Ravi Kumar: Thank you, Jason. The 450 let me start with the first one the 450 odd client engagements we’ve come a long way. If you remember in quarter 2, 2023 we spoke about 100 and now we have 400 early client engagements and these are very short prototype rapid prototype kind of kind of deals. 500 of them more than 500 of them we have in the pipeline and the thing to watch for now is how many of these will go into scaled execution for our clients. And that’s where that’s where the monetizable opportunities are. So we are continuing to work on it. There are broadly two things we are investing on or rather three first follow the innovation cycles of AI. Second, build the last mile infrastructure so that the raw power of AI can be made production grade enterprise grade for our clients.
That means last mile infrastructure related to managing AI platforms, orchestration, in case of AI and like other discontinuities. How do you improve the accuracy of the models? How do you create explainability because this is a black box? How do you create explainability? How do you create observability? So all of those platforms we have built and we have announced is the last mile infrastructure I kind of referred to, which helps us to take the raw [ph] power and make it production grade. The second thing we are investing on is productivity studies. I mean, what does AI do to different roles and different operations of different industries? And how do we make embrace of AI much faster on larger cohorts? And we partnered with Oxford Economics and we created templates for every industry, every role so that we can do an anatomy of tasks as I call it.
And then we then start to figure out how to create a much faster and a much broader embrace in enterprises. So this is preparing for the future where we believe enterprises are going to be people plus machine endeavor. Now what does it do to our operating model or tech for tech, as I call it. It, of course, changes the productivity of a developer. When the cloud came into picture a couple of years ago, it flips the productivity where, as a developer, you spend very little time on the plumbing, but you spend a lot of time on innovation. You spend a lot of time on building. This is our second shot at improving developer productivity and not actually spending time on repetitive pass, not actually spending time on things which a machine can write, but you could actually pivot developer productivity on innovation.
So this is the second shot at it. And I would believe this is probably more disruptive than what the cloud did. And we think what will happen is this will lead to reducing backlog, improving the throughput to our clients, increasing the tech intensity at a lower cost. So I always believe that this is going to be an opportunity than a threat if we can pivot ourselves well. And the opportunity is about creating the tech intensity. Every industry doesn’t have that intensity. So we have this unique opportunity to create that intensity at a lower cost and a lower entry barrier. I mean you don’t need to be a developer to embrace software code, which means the entry barrier goes down. So we think we have a bigger opportunity than before as long as we can embrace this into our own landscape and equally build the use cases for our clients to embrace it.
So I see this as a uniquely big opportunity for companies like Cognizant.
Jason Kupferberg: That’s good color. And then just a quick follow-up. You mentioned 8 large deals you won in the quarter, $100 million plus TCV, I think. Are those expected to contribute materially to 2024 revenue? And if so, were they already contemplated in your original revenue guidance?
Ravi Kumar: Yes, I mean the visibility we have so far on the deals we have won, we have baked it into our guidance range. But Jason, the deals we won last year have a better throughput this year. And the deals we win this year will have a better throughput in the second half of this year and in 2025. The challenge in 2023 was we did have that backlog as we got into 2023 because we were not playing on much deals. Right now I don’t have the challenge because I had a good, healthy pipeline in 2023 that’s contributing to 2024. And then we keep doing this in the same sustained manner. We will exit into 2025 with tail velocity. So the first year is normally lower than the second year. And by the end of the second year, you get to the run rate you have to normally the span of the deals has changed.
Earlier, it has to be lower now, it’s 3.5 years or plus because large deals now come on a cost takeout model, unlike transformation related to unlike transformation-related large deals. But once we start to execute and get the bid versus did in a good shape, then the committed spend will then flip over the new spend because you’re already in the group. So that’s what we are betting on as well. I mean, once you start to perform well, you have the license to take more from our clients.
Jason Kupferberg: Thank you.
Operator: Thank you. Our next question comes from the line of James Faucette with Morgan Stanley. Please proceed with your question.
