Infosys Limited Sponsored ADR Stock

Ladies and gentlemen, greetings, and welcome to Infosys Limited Q1 FY '27 Earnings Conference Call. [Operator Instructions]

Please note that this conference is being recorded. I now hand the conference over to Mr. Sandeep Mahindroo. Thank you, and over to Mr. Mahindroo.

Thank you, everyone, and welcome to this earnings call to discuss Infosys Q1 FY '27 financial results. Joining us on this call is Chairman of the Board, Mr. Nandan Nilekani; CEO Mr. Salil Parekh, CFO Mr. Jayesh Sanghrajka, along with other members of the leadership team.

We'll start the call with some remarks by Nandan, followed by remarks by Salil and Jayesh on the performance. Subsequent to that, we'll open up the call for questions with Salil and Jayesh. Kindly note that anything we say which refers to our future outlook is a forward-looking statement that must be read in conjunction with the risk that the company faces. A full statement explanation of these risks is available in our filings with the SEC, which can be found on www.sec.gov.

I'd now like to pass on the call to Nandan.

Thank you, Sandeep, and it's really a pleasure to talk to all of you. I joined this call to make an important announcement. As you know, Salil has done a stellar job as the CEO for almost 10 years. And under his leadership, the company has grown from $10 billion to $20 billion. He's done the transition to the digital era. And he's laid the foundation for a differentiated AI strategy, which will serve the company in good stead for many more years. However, his time is coming to an end on March 31, 2027. And the Board has decided today to appoint CEO -- a new CEO who is coming from inside Infosys from within an internal candidate. His name is Ashish Dash.

Asish Dash has been in Infosys for more than 31 years. Since he joined as a software engineer from IIT Kharagpur. And he has -- he has all-around experience of Infosys -- he has worked in delivery for many years. He has worked on account management. He has been involved with starting a DC in Bhubaneswar he has been in sales. And of course, he has been a sales [sense], segment head for many years running the sure practice, which has many verticals.

And he is an outstanding person. He's very good at his job, he's very collegial. He's very good collaborative. He's accepted and liked by everybody in the company. He has a quintessential Infosys values -- at the same time, he's focused on the market and being able to get good deals at good revenue and good margin. And because of his technical background, he understands the AI, what is happening and that will help him in the future. So the Board has appointed Mr. Dash as the [ next ] CEO Designate.

He will work with Salil over the next few months -- next 2, 3 months, we'll focus on getting more coaching and training on being a CEO. And then for 6 months, he will work as a mentee under Salil's leadership, who will grow him for the complex job of managing a $20 billion company at a very transformational time. So we are all very excited by the choice. It has got a very good response internally and with customers. And you will get to see him in a few months. So you can maybe keep that in mind.

Maybe I now I'll ask Salil to add a few words on Dash.

Thanks, Nandan. Good morning, good evening, everyone. It's an absolute pleasure for me to have Dash be the next CEO of the company. I've had the opportunity to work with him over the last several years. in my mind, he's a fantastic leader and very good with the people around. He's worked very closely with clients and build a portfolio, which is, I think, quite strong and exceptional on the growth dimension and the way it's managed operationally and economically -- so all of the ingredients which make for a successful business.

In addition, to his leadership, Dash is a very good friend, and I'm delighted for this. Congratulations to him. And then I look forward to working with him over the next -- the course of the next few months, as Nandan mentioned, in the way we transition in a smooth transition there. So look forward to all of that. And as Nandan said, you will get to meet Dash in the coming quarters as well.

So thank you, and I'll excuse myself and Salil and Jayesh, the team will continue the quarterly call. Thank you very much.

Thanks, Nandan. Good evening and good morning to everyone on the call. Thank you for joining us. Let me start off with the update for the business in this quarter. Our revenue growth for Q1 was 2.4% year-on-year and 1% quarter-on-quarter in constant currency terms. We had a onetime revenue impact of a client decision during this quarter.

Our AI services revenue was 8.2% of overall revenue. Our large deals were $3.6 billion with a net new of 61%. And operating margin was 21.1%, free cash flow at $955 million, and our earnings per share were higher by 15% in Q1 in rupee terms. We saw a strong acceleration in our AI business, as I shared earlier, with AI revenues for the quarter at 8.2%. T This is growing at double-digit quarter-on-quarter over the last several quarters. With this momentum, we see long-term relevance of our services for our clients. From a delivery team, over 80,000 employees are working today on coding tools such as Cloud Codex for our clients and for some projects in side.

We saw strong traction across the 6 areas of growth in our AI strategy, Hexagon -- we see client work, for example, in building agents for processes, work on data, in AI, in modernization and, of course, encoding tools.

For a health care company, we implemented AI agents to automate Medicaid eligibility verification and operation support. The solution reduced eligibility verification time from -- which was about 6 to 8 days to approximately 4 minutes. We are building a team of frontier engineers to support our client work -- our plan is to have 6,000 frontier engineers over the next few years.

We built a platform to pass fabric that allows our clients to get benefits of AI while keeping the sovereignty of their data and company knowledge with themselves. Our clients are able to work with any foundation model closed, open weight, on cloud, on the server to pass fabric provides a harness to a client to enable them to more fully deploy the benefits of the foundation models into their organization.

Our clients are also able to optimize their token cost by ensuring appropriate models are used for appropriate tasks.

Overall, we see a good pipeline for AI services, and that gives us a good view for continued AI work with our clients. Outside of that, we continue to see the macro environment remaining uncertain. With our Q1 results and a view of the rest of the financial year, we changed our revenue guidance revenue growth guidance to 1.5% to 3% year-on-year growth in constant currency terms. Our operating margin guidance remains the same at 20% to 22%. Thank you.

And with that, let me hand it over to Jayesh for his update.

Thank you, Salil. Good morning, good evening, everyone, and thank you for joining the call today. We entered FY '27 against a backdrop of a dynamic and evolving business environment, which is reflected in lower-than-expected volumes. Clients continue to prioritize investments in AI modernization, cloud and productivity initiatives while remaining selective in discretionary spending.

Our focus remains on disciplined execution supporting clients' transformation agenda and delivering sustainable financial performance. Q1 revenues were at $502 million, an increase of 1% sequentially and 2.4% year-on-year in constant currency terms. Acquisition contributed approximately 1.1% sequentially. Our AI revenue momentum is very strong with AI revenues at 8.2% of our overall revenues, growing at a strong double digit sequentially over the last many quarters. We are seeing strong traction across all 6 value pools with higher share of revenues coming from process AI, AI strategy and engineering and data for AI.

Q1 revenue growth was lower than our expectations, mainly due to one-off 50 basis point impact on account of program termination by an EURS client during the quarter. This was not factored in the earlier guidance. Volumes were soft and weaker than expectations and also versus the historical Q1 trends. Additionally, client expectation on productivity, along with high competitive intensity is resulting in softer increase in price versus our expectations.

Sequential revenue growth was also impacted by higher offshoring to derisk our business model, along with lower revenues from a European manufacturing client, as I mentioned in the last earnings call. Despite lower-than-expected growth, gross margins improved by 60 basis points sequentially.

Operating margin improved by 20 basis points sequentially to 21.1%. Major components of the change are as below. Tailwinds of 70 basis points from rupee depreciation, 20 basis points from project Maximus, 20 basis points net benefit due to amortization of costs on intangibles incurred in Q4, offset by impact of new acquisitions in Q1.

Headwinds of 50 basis points from investment in AI sales and marketing, 40 basis points from onetime revenue impact arising out of program termination. We also had onetime cost benefit of approximately 30 basis points, which was offset by 20 basis points due to increase in various other expenses. Our tight focus on improving operational efficiency led to utilization, excluding trainees, improving by 1.9% to 84.9%.

On-site mix, excluding new acquisitions, dropped by 30 basis points. However, including acquisitions, it remained flat. We expect on-site mix excluding new acquisitions to reduce by 75 basis points to 1% for the year. DSO reduced by 4 days sequentially to 63%. DSO, including unbilled net of unearned was 76 days versus 78 in Q4. Headcount reduced by 500 employees after adding over 2,000 employees from acquisitions. -- attrition increased slightly to 13% versus 12.6% sequentially in line with Q1 seasonality.

We plan to give salary hikes to most of our employees effective October while the rest of the employees will be covered in January '27. We expect effective tax rate for the year to be in the range of 29% to 30%. EPS for the quarter stood at INR 19.19 up approximately 15% year-on-year.

Q1 yield noncash investment balance was at 6.8%. Our balance sheet continues to be strong and debt-free. Consolidated cash and cash investments were at $3.9 billion at the end of the quarter after returning more than $1 billion to the shareholders through dividends. Free cash flow was strong at $955 million at 16.5% of net profit.

Large deal wins were strong at $3.6 billion with high net new of 61%, reflecting the relevance of our value proposition. Out of the 22 large deal one, we had three deals worth $400 million each. We have been on the positive side of vendor consolidation, with 20% of the total large deal CCV being from new vendor consolidation deals.

Vertical-wise, we won five deals in financial services and communications, four in EURS, three in manufacturing, two in retail, one each in life science, high-tech and others. Region-wise, we signed 11 deals in North America, 8 in Europe and three in the rest of the world.

Coming to verticals. In financial services, uncertainty and geopolitical instability is causing some clients' hesitancy as spending patterns are taking a more cautious approach. -- client priorities are centered on efficiency, productivity and modernization with discretionary spend being evaluated more carefully. We see momentum across banking, payments, capital markets and wealth management.

AI adoption has been incrementally incremented an additive with clients increasingly engaging us to support their AI journeys across strategy, platforms, engineering and operations. This is reflected in our strong deal wins this quarter with approximately $1 billion in large deal TCV or largely in net new TCV, GCCs continue to expand, and we are partnering with our clients both in setup and growth of GCCs.

Growth in manufacturing continues to be impacted due to lower revenue from a large client. Clients remain cautious on discretionary spend and decision-making is elongated, especially in European auto. The impact of tariffs, geopolitical uncertainty and energy cost is keeping budgets tightly controlled. While AI adoption is creating new opportunity areas, it is also raising productivity expectations from clients.

We are getting better pricing on AI skills and consulting. We remain focused on supporting clients through digital AI modernization and consolidation initiatives while balancing growth opportunities with disciplined deal selection and sustainable pricing.

EURS segment was impacted by one-off client termination, adjusted for which the growth was strong. Macroeconomic uncertainty continues to influence client spending patterns and decision-making time lines. Clients are driving business priorities, including cost optimization, operational resilience, productivity improvements and regulatory compliance.

Generative AI is emerging as a strong growth catalyst, driving process re-imagination and productivity initiatives. Our partnerships with hyper-scalers and AI native companies is allowing us to experiment and ideate faster. In retail and CPG, consumer spend remains muted and budgets are tightly controlled due to geopolitics, inflation and talent. -- spend is shifting towards AI modernization and productivity-led programs funded through operational efficiency and cost optimization.

Clients are asking for AI-led productivity commitments leading to new pricing structures. We are leveraging our native knowledge of the clients' business processes and technology landscapes and augmenting it with AI. Large deal pipeline is healthy, but decision cycles are longer. In Communications, operating environment remains challenging as clients continue to exercise discipline on discretionary spending and closely scrutinize investment decisions. AI is reshaping spending patterns, enterprises are increasingly prioritizing initiatives that deliver near-term gate.

Telkom is undergoing significant transformation with consolidation and M&A with increased investments, especially for OEMs. We remain focused on aligning our offerings to these evolving client priorities and helping enteprise realize measurable business outcomes. Considering lower-than-expected Q1 revenues and revised view of the rest of the year, we are revisiting our revenue guidance to -- we are revising our revenue guidance to 1.5% to 3%.

This includes approximately 1.7% contribution from recently closed acquisitions of Optimum Health care and stratus slightly over 1% impact from large European manufacturing clients due to reduced client spend along with our conscious decision to not pursue certain deals that were not aligned to our return expectations approximately 0.75% to 1% impact from shift towards offshore.

Overall business environment continues to remain volatile. The lower end of the guidance assumes further deterioration in macro top end of the guidance assumes an improvement in macro, though lower than what we had assumed in April guidance. FS and EURS are expected to grow higher than the company average. The underlying fundamentals of our business remains strong. We continue to see healthy client engagements leading to a robust pipeline.

We are taking decisive actions to capitalize on the opportunities ahead, especially on six identified AI value pools. Spending is shifting towards areas with clear business cases such as AI modernization, cost transformation, cybersecurity, [ cloud optimization ] and vendor consolidation.

As we look at the rest of the year, we remain confident in our strategy, discipline in our investments and focus on delivering stronger performance. Margin guidance is maintained at 20% to 22%. This assumes headwind from wage hikes productivity pass-throughs, AI investments and 50 basis point impact from acquisitions of optimum health care and strategies. These headwinds will be partly offset by initiatives under project maximums and currency benefits.

With that, we can open up for the questions. Thank you.

[Operator Instructions] First question is from the line of Kumar Rakesh from BNP Paribas.

My first question was a bit of a clarification around the guidance, especially the like-to-like guidance what we had given last quarter versus this quarter. If I'm looking at the new guidance that is at the midpoint, suggesting 2.25% sort of growth, which I understand you indicated includes acquisition of about 1.7%. So that would imply and organic growth of about 0.5% or slightly higher than that versus 2.5%, which was in the last quarter. So is that about 2 percentage point of cut at the midpoint in the guidance or am I reading that wrong?

Kumar, so the last quarter would be -- midpoint would be around 2.2%. In the guidance because, as you say -- as you remember, we had said 20 basis points was the status, which was already baked in, in the guidance, which was 1.5 to 3.5.

Okay. Got that. So in that case, like to like this time, it would be about 8 points sort of a number, excluding the incremental acquisition that we have baked in.

Yes.

Got that. And looking into the second quarter, given some of the impact that we have seen in this quarter with lower-than-expected volume and onetime client-related decision as well, how much of that you are expecting that to flow into second quarter as well? And how you are looking at the demand environment and the growth momentum?

So Kumar, as you know, Typically, whatever happens in Q1, it will have a cascading effect in Q2. And especially if the volumes have been softer through the Q1, automatically, it will have some impact on Q2 and therefore, the rest of the year. That kind of largely explains the guidance change. As I said earlier, the multiple reasons on the change in guidance is, first of all, one-off that we had in 1 of the EURS plants the volumes that were softer with the cash-cutting effect, the ask of productivity from clients and increased competitiveness competition in pricing that reflected in a lower-than-expected pricing this quarter, which will again have effect on the rest of the year. And as I had called out at the beginning of the year, we expect our on-site mix to be lower by roughly around 0.75% to 1%, which will have impact on a year-to-year comparison, if you're doing.

We had called out a European manufacturing clients impact between 0.75% to 1% last time, which is now clearly above 1% as we have progressed on certain other deals as well. So that is an additional headwind as well. So all of that is baked in the revised guidance.

Just one clarification around the onetime client decision which you spoke about, if you could give some context to that, that would be great. That's all from my side.

Thanks so much. So this is with respect to a client, which has terminated a project in the EURS vertical.

Next question is from the line of Jonathan Lee from Guggenheim.

You mentioned that softer volumes and pricing contributed to Q1 alongside the premium termination and at the upper end of the prior guide assumed macro stabilization, that's not materialized. Can you walk us through how the quarter progressed relative to internal expectations, whether April, May and June trended differently when the program termination was communicated to you and whether decision-making velocity and discretionary spend deteriorated or stabilized through the quarter? And what have you seen in the first 2 weeks of July that may inform your shape of Q2?

So Jonathan, sorry, I wasn't very clear with the question, but from whatever I understood the question is whether we saw the change through the quarter and the increase in volatility. The softness that we saw in terms of volumes was through the quarter, the one-off impact that we saw was mainly on account of a client termination, which happened towards the end of the quarter. And the additional -- the deal that we talked about, European client that was also towards the end of the quarter. So I think all of those factors reflected in the revised guidance, if that is what you're looking at.

And given your commentary on pricing, particularly around the competition has been building for several quarters and MAXIMUS explicitly includes value-based selling. Why were pricing headwinds not more fully contemplated in the April outlook what has changed over the last 3 months? Is the pressure concentrated in specific verticals or deal types of renewals versus the new? And what gives you visibility that pricing may actually stabilize from here?

Jonathan, we are not saying that we are not seeing a price increase. What I'm saying here is we haven't seen the as much price increase that we envisaged at the beginning of the year on the back of the AI productivity ask of the clients, plus the intensifying competitive competitiveness in the market. But we are still seeing a net increase in the pricing.

Next question is from the line of Gaurav Rateria from Morgan Stanley.

My first question is on the multiple client-specific issues, one is the European automotive that we highlighted last quarter than this quarter on the EURS vertical -- how should we think about all these like our completely disconnected issues and just happened to take place at the same time coincidentally, or there are certain common links, which basically could be early renewals, competitive pricing, et cetera, going on because of the technology change. So just trying to understand how much of it is led by underlying changes in technology happening and driving clients to take these decisions and creating competitiveness in the market? Or is -- are they completely disconnected events?

So Gaurav, there are two parts of the question. One is the European manufacturing client that you talked about it, we knew certain part of the deals that we had we knew at the beginning of the year, which was in April, and there was additional deals that happened in Q1 of this year. Both of these were the deals where we did not -- we decided not to pursue the deals beyond a certain point because it was not economical -- it did not make economic sense for us a commercial sense for us -- and that is -- that's the reason that has nothing to do with the client behavior in terms of AI, et cetera. The other deal is a contract where the client has terminated the contract for various reasons. Again, nothing to do with AI here. It's a termination of the contract. And therefore, a reduction in revenue.

Got it. My second question is on your margin outlook. I know that you maintained your outlook on the bank, but now that you have announced the wage hike for second half for the company as a whole. So there will be incremental headwinds around that. So just wanted to understand what would be some levers that will help you to offset these pressures in the second half? And would it be fair to say that our aspiration will be to just hold on the margin level compared to the last year and this year?

So Gaurav, at this point in time, we have given a guidance of 20% to 22% let me say that at the outset, we are very confident of that guidance. Of course, as I called out at the beginning of the year, we will have a headwind coming out from the acquisition that we have done from -- in terms of amortization of intangibles and retention be out of to the founders or the management team, et cetera, or the acquired entities. But we also have tailwinds coming from currency coming from project maximums. As you see this quarter also, we've got 20 basis points of tailwinds from project maximum, 70 basis points of currency -- so all of those are tailwinds. As we look forward, as I said earlier as well in the call, we will have 75% to 1% reduction in on-site mix. So that is -- so all of those are tailwinds. -- puts and takes all of that put together, we are still very confident of maintaining our margin guidance.

Next question is from the line of Abhishek from Motilal Oswal.

I think my question is on deal wins. It does look like we've had a pretty decent quarter on deal TCV net new seems to be decently strong as well as compared to historical levels. But clearly, that's not kind of translating into kind of guidance. So -- how is the TCV versus ACV dynamic playing out? Are we seeing extended TCV sort of or extended 10 years right now, which is leading to lower ACV? Or are we seeing sort of delayed ramp-ups, but clients are still commiting to spends, That will be very helpful to understand with regards to the conversion of the deals that we are winning.

So Abhishek, if you look at the deal typically, the terms of the large deals have not gone up. They still remain between on an average between 3 to 5 years. Of course, when you look at some of the mega deals, the terms are -- could be longer. But in the current year, the -- we have most of the deals which are not mega deals -- the deals that we signed, most of -- while most of them were less than $500 million.

We did have some deals between $400 million to $500 million, 3 of them. What we also need to remember is whenever the deal comes up for renewal, we always used to have the additional productivity asked from the client, which is how traditionally this industry has been -- on the back of AI, there is a deflation on -- additional deflation on the AI deflation as we call it.

So that's a headwind that's there. That's only on the large deal portion that's also there on the non-large deal portion. So that is what is getting offset by the net new business that we are seeing.

Understood. And could you quantify the deflation, if you can? I know it's -- I mean, it's so dynamic, but just a quantification about the deflation entails would be helpful. And lastly, how do we define AI-led revenues? Is this AI implementation or are infused just a broad sort of sense of that will also be very helpful. That's from my side.

This is Salil. On the AI line, and I'll come to the other one after that. I think what we are seeing on the AI revenues is these are revenues which are coming from the strategic framework we described at the Investor Day, which are the six areas that we see new growth, the new addressable market of $300 billion.

For example, process AI, for example, making AI engineering strategy work. For example, data, which is needed the data layer for AI.

And each of those six areas, we see a good growth. This revenue is 8%, 8.2%, growing double-digit Q-on-Q over the last several quarters. And that's the primary AI revenue. Internally, we also look at AI revenue, which you referenced like infused augmented or where AI is and part of an existing work stream that becomes more AI. But this specific one that we shared externally is what we see from the AI strategy that we put together.

On the -- so on the quantification, we don't quantify that compression part externally, but we acknowledge that, of course, there is a compression. And internally, we track it to see how that works. Now in many cases, when there is the compression, we typically given the work we are doing with clients, have the opportunity to do more work in other areas. So the contract terms, scope, et cetera, gets really fine.

And in many cases, we see adjacent to that other pieces of work, not related to that, which come through. So it's very -- it's not easy to simply say like-for-like in many cases, but they're definitely we see a compression.

So just to add to what Salil was saying, the AI first revenue is everything that is around the Hexagon and AI augmented revenue is what we presented on the AI [indiscernible] also. That is not part of this. While we track it internally, that is still not part of this. So AI first is everything that we do in terms of Hexagon and the subservices that we called out at Hexagon.

We have a very robust process inside the company of identifying these other child subproject level and tracking it and monitoring it. It is growing at a very strong double-digit growth.

Next question is from the line of Ankur Rudra from JPMorgan.

I'm just curious to start with on the demand environment worsening especially from a AI product to pass-through demand that we've been getting. Can you talk about how secular this is across our industries and geographies? And how often do you see...

Sorry to interrupt you. We are losing your audio in between, -- can I request you to please come in better reception area?

Is this clear now?

Yes, go ahead.

Sure. So my question was on the worsening demand environment from an AI productivity pass-through perspective. How secular is this across industries and geographies -- and how often do clients ask for productivity increases in the middle of a contract as opposed to on renewal.

This is Salil. Ankur, I think -- what we are seeing is there is a demand for AI productivity, which is across most industries. Now if you look at where AI is most getting used -- we probably see telcos, we see financial services. We see even on retail utilities. That's where their usage is pretty high, especially with the foundation models, the modernization, the coding tools.

On the productivity side, it's a broad sort of coverage that we see. And it typically at least in the recent past has come up as there's progress made by the AI foundation model companies or there's a perception that, that sort of a benefit can be achieved the discussion stats. And of course, at the renewal time, it's definitely time. Sometimes it does come in between the time frame of the contracts renewal as well there.

Okay. I just wanted to sort of follow up on AI revenues, which have been growing at a very high pace like you've been highlighting. -- if we think this out a few years, at what size of your overall portfolio do AI revenues have to be so that you can overcome the AI deflation of the compression in the rest of the portfolio in thought set.

So we don't have a view in that sense externally on what you're sort of referencing -- but I think if we are able to execute on this AI transformation, as we have done in the last few quarters, we get this sort of momentum -- it's not that difficult to see that in the coming few quarters, it will start to become more and more larger part of our overall revenue and that will drive the growth of the overall company.

If I go back to how we saw it, not that it's the same thing, but there's some lessons maybe on the digital, we saw that there was a way that at one stage, we were at 20% and then over a few years, we then went to 60% of our revenue becoming digital. So if that sort of path becomes followed we can see a big sort of a transformation and a long-term sort of support to the view that what we are doing remains relevant in terms of services for our clients.

Now here, there are strong partnerships with the foundation model companies. There is extremely strong internal work on Topaz Fabric. We are building things where clients can use multi-model scenarios within Topaz Fabric, where they can use different models for different types of work, so the token cost is optimized. We have a ability to provide a harness so that they can build what they want to build and keep the soverenity of the data and like the knowledge of the company more within themselves. So to me, all of that points to that, it's a nice growth area for the long term. And we are now looking at 8%. It's fairly sizable, and we're looking at it becoming more and more sizable in the quarters to come.

Just one last clarification.

Sorry, I could just one additional data point I would want to add is, if you remember, in February, we talked about our AI revenue, which was 5.5% for Q3. And in 2 quarters, it's already become 8.2%. So you can -- you can imagine the rate at which is growing. And it's -- even if you look at a longer 5-, 6-quarter view, it's growing at a strong double digit and that kind of gives us the confidence that this is becoming our growth engine.

I appreciate it. Maybe just one clarification, Jayesh. Can you confirm that the program termination was fully absorbed in Q1? Or will it have an impact in the second quarter also from a sequential basis?

So Ankur, the program has been terminated. What we know has been -- has obviously been taken in Q1 at this point in time.

So no follow-through in Q2 in terms of that program specifically.

Yes. What we know at this point in time has been considered in [ December ].

Next question is from Bryan Bergin from TD Cowen.

First Salil congrats to you and congrats to Dash. My first question is on AI talent and [ incompetition ]. I'm curious what your view is on hyper-scalers like AWS, Microsoft recently announcing new investment in their own FTE practices. Just considering [indiscernible] use of the services channel around cloud deployment, they seem to be a bit more surprising and OpenAI or Anthropic doing it. So what are your thoughts there? And you've announced plans to add 6,000 frontier engineers -- but it seems everyone is looking to add that base of talent. So can you just talk about how you plan to navigate that elevated competition for top tier talent.

So first, thank you I think on the -- with other companies launching services companies to help large enterprises with making AI work. At a high level, I see that as a positive for Infosys because it reconfirms that what we do and now with the AI revenue growth that we are demonstrating that we have sort of relevance for the long term for our clients. What I think works for us is we have over 300,000 employees. We have deep knowledge and context of select clients that we work with, and that becomes the way to really ensure that AI gets leveraged into that environment, which is typically quite complex. We are also in a position where we are partnering with some of the companies you named, and I've spoken with them as they have launched their programs -- and the intent and the idea is really, in terms of scale, a few hundred or a couple of thousand is not going to be the same as 300,000 from Infosys. But there is a way to partner and make all of that work for the benefit of the client.

That's how at least we're looking at it for now. And there's a similar type of models existed, as you probably know well in the past when there were software companies, which have their own small services businesses. In terms of talent, first, we have already people within Infosys who are operating at the level of frontier engineers. And so we have put together a program to bring all of that together to make them at the same type of a global level. Then we have training for the people that we will recruit and build out to be like that frontier engineers.

And then, of course, we will look externally but the primary method is recruitment in college training and taking internal people who are doing some of that type of work and making sure they're fully deployed into the frontier engineer work.

So we feel that we have a decent start to it. It's not that we are going to, tomorrow morning, recruit 6,000 from the outside. But equally, we also have, as has been always the case with Infosys, the approach of training the people from ground up, so building out that skill set, which is slightly longer, and that's why I've sort of said it's not it's over a few years, we want to build it out and make sure that we support our clients in that.

Okay. Okay. That's clear. My follow-up on AI productivity. Can you just give us a sense of how much of your existing backlog has been repriced under the higher levels of good market productivity? I'm trying to understand how long the company may face outsized compression as you renew the installed base of work where there wasn't any meaningful GenAI-driven efficiencies before?

So as you can imagine, it's something we look at internally, but it's not something we share externally.

Next question is from the line of Vibhor Singhal from Nuvama.

Just two questions from my side. One question, Salil, on the -- basically the overall environment in which we are operating. Some of our peers have kind of called out, and I think it's kind of what is also the concept which is gaining traction is that more and more believe that enterprises might not just basically look to deploy the premier large language models for their enterprise needs and they might be now going more towards more like customized small language models, the which can be basically cater to their own specific needs.

And to that extent, more and more deals and large deals specifically are all basically making their way into the market towards the players -- is that also that we are also seeing our non-composition with the clients? Do we see some of those kind of deals on the horizon? And do you see that basically playing out over the next few quarters?

So there, I think the way you describe it, what we are seeing it is the large companies, large enterprises are becoming more sensitive to -- what is the foundation model like best equipped for and for the various tasks and activities and processes that they have inside the company, which model should be used for which thing? So can we use like a company might think like a less parameter model, also less expensive model like an even an older version of some of the big company models for some last and the most recent one for like some very specific, let's say, high-end type of task, which needs it. So that optimization is going on. And that's where we think what we have built in Topaz Fabric allows the company to do this in a very efficient way.

Then it also looks at companies also looking at, okay, I will use for the simpler task, a slightly older model or less expensive. Then let me also then look at the cost of token usage for that model. And even there, there's a way for the same effectiveness, you can get a lower token cost approach in the model this whole approach of this multi-model is critical for the task and the cost. At least we are seeing the large companies are being sensitive to that. And that's where what we have built and how we can work with them today, we are working in Fabric Topaz with 15 different models.

So let's say, you come as a large company, Global 100, and you want to do something, you don't even have to decide by looking at the task we will decide between the 15, where to put it and give you the most efficient outcome. So those are things like that will help the companies to do the things in a better way we feel.

Got it. Got it. So overall, this should basically -- I mean, if I were to, let's say, take a top few of this, this would mean that there is an increasing level of customization that or, let's say, a specific requirement that each client would require rather than more of a standardization to begin with?

It depends also a little bit like some companies might say, this is available. But some companies might say, look, I want Model X. I want to build deep capability in that Model X, like company X will have three models. They can go with an older model in the company X it's not like there's one answer, meaning people are all doing different things, but the flexibility exists today. So depending on how the company wants to do it.

Got it. Got it. Just 1 last question on the margin spend. Jayesh, if I could just bother you on that. In FY '26, we had the wage hike, which was spread over Q4 FY '25 and Q1 FY '26. So we just probably had a -- basically half of the impact of the wage hike in FY '26. In FY '27, we're able to give the wage hike in Q3 and Q4. So the entire impact is going to be absorbed by in this year itself, plus we have the acquisition impact, which you called out in the call. So are we looking at more headwinds this year on the margins than FY '26. I know we are in that same guided range of 20% to 22%. But vis-a-vis effect or dare we looking at more headwinds than FY'26?

So ever, if you look at FY '26, we had a full year impact of the wage hike that we gave in January as well as in April, right? Of course, whatever we gave in January, the flow-through of that was for 3 quarters. But whatever we gave in April, the full year impact of that came in, in the year versus in FY '27, we have only half year impact of whatever we do in October and 1 quarter impact of what I will do in January. So to that extent, the relative impact is going to be lower in FY '27 versus FY '26.

And of course, there would be a 50 basis point impact on account of the acquisition that we have called out on acquisition, but if you look at the tailwinds that I called out, there is a currency tailwind, at least as we stand today versus the last year, the project maximum is still creating value. We have seen pricing benefit a bit a little lesser than what we estimated at the beginning of the year. Utilization has gone up quarter-on-quarter significantly. Our on-site mix is going to go down. So I think there are puts and takes on both sides.

Next question is from the line of Bachman from BMO Capital Markets.

Good evening, good morning. I wanted to ask about your thoughts on head count growth trends through FY '27. And I'm not looking for specifics, but just generalities. Is head count going to grow, be flat, reduce as you look at the next 12 months. And even if you find on the next few years, how do you see the head count growth in relation to revenue growth?

This is Salil. So first, what we saw in the last financial year, as you know, is we recruited 20,000 college graduates for the full year. This year, we have a plan to recruit 20,000 college graduates. In the first quarter, we have recruited over 4,000 already.

Our plan is to continue to bring in talent, make them more and more AI, well verse and then have them work with our clients. What we are seeing with the 8% revenue of the AI is that to make many of these things work, it's a combination of foundation model, agents and people. Of course, there's more efficiency. So the same amount of work can be done maybe with a few people, but there's more work.

So overall, at least right now, we are seeing that. We don't have an exact external view on the India headcount, but we continue to look at recruitment. We think it looks like it will be part of -- the head count will be part of our future as our revenue grows as well.

Okay. Okay. And it will be interesting to see how I understand the recruitment process, it will be interesting to see how your net head count trends unfold. Can I go to the dislocation? You talked about 20% of your CCV was vendor consolidation deals. Could you provide some context on really the economics associated with those deals, what I mean by what was the leverage that enabled you to win those deals. In particular, you talked about price was a little more aggressive this quarter. How are pricing trends during the enabling you to win those deals? Just any kind of attributes that you could throw out such as was it more competitive? Or was price down? Anything along those lines? That's it for me.

I'll start, and Jayesh will add a little bit more to it. What we saw like in the reasons for winning a consolidation deal, typically, what we are noticing is there's a complex tech environment, and the clients are seeing that what we have done for them over the past in terms of delivering value is very significant, more reliable and that's typically when we are the beneficiaries of the consolidation deals. In terms of pricing for those specific deals, there's always productivity benefits because that is in the nature of the discussion in this period.

But the reason primarily for the wins are more about the depth of delivery, understanding of technology.

Just to add to this, what Salil said. On an aggregate level, all of these consolidated deals came at a very healthy margins even when you compare to our overall large deal portfolio. As I said earlier, we will compete aggressively in the market but we are not going to underwrite uneconomic productivity assumptions. And in those cases, we would prefer to not pursue those deals further when it doesn't make economic sense to us.

Next question is from the line of James Friedman from Susquehanna.

So well done piloting the company in [ dash ]. We look forward to working together. I had a bigger picture question back to the strategy Hexagon be interested in your perspective on the supply side, what sort of rising reskilling does that require? And on the demand side, Salil mentioned what you're finding is resonating most obviously, is performing well. Is there anything though that needs to be adjusted? So supply and demand question about the strategy at Hexagon?

Thank you for that. On the supply side, first, we have taken a view, and I'm sure you know that. We have not done any staff restructuring in the company, we have done essentially all reskilling. And that is a significant work for the company. But I think we see a benefit of that over time.

What we are seeing is -- and has another reason for doing the college graduate hiring because what we see from colleges up people coming in with a lot more native understanding of the AI landscape and the tool set. And then building -- like training them on our Fabric and Topaz is the next step after that and also training them on our tools, which are pre-AI so that we have a sense of how software development works.

So we think we will be able to manage a lot of that supply side with the people we bring in. But there are also specialized things where there will be some accelerations needed -- I mean a specific tool is very much in demand. And for that, of course, we have some recruitment, which is more lateral as well. Even there, we need a little bit of reskilling or training, but not massive. There's good understanding. But that, of course, is in short supply. So we will still rely more heavily on bringing in from college training, which is by design is a longer duration process.

On the demand side, we are now tracking each of the six areas pretty granularly as Jayesh mentioned earlier, we have good traction on the process AI side, it's going pretty well. On the AI engineering, it's going pretty well. meaning in terms of scale, all of them are growing very fast, but those things are pretty scaled already. The data AI part is going pretty well. And so the whole work of building agents doing the coding, doing the modernization, doing the data.

Those things are really scaling up, meaning have a decent scale today, and we think those will continue going pretty well.

Thank you very much. Ladies and gentlemen, we'll take that as the last question. With this, I now hand the conference over to the management for closing comments.

Thank you. So first, thanks, everyone, for joining. A couple of points to summarize from my side. Overall, in the quarter, we had neutral revenues, strong margins, strong free cash flow and very strong large deals. The more critical thing, AI services revenue, 8%, growing across quarters, Q-on-Q, double digit and becoming more and more of scale for us and showing us therefore, that there is a long-term relevance of what we are doing for our clients. And that gives us a tremendous benefit given the client connects that we have across the different industries and across the different markets. So thank you all for joining in, and we'll catch up at the next quarterly call.

Thank you very much, members of the management. And ladies and gentlemen, on behalf of Infosys Limited, that concludes this conference call. Thank you all for joining us, and you may now disconnect your lines. Thank you.

A very good evening, everyone. And thank you for joining Infosys' first quarter financial results. My name is Rishi. And on behalf of Infosys, I'd like to welcome all of you today. I would first like to invite our Chairman, Mr. Nandan Nilekani; and our Chief Executive Officer, Mr. Salil Parekh, for an important announcement, which will then be followed by our business updates. Kindly note, Nandan will not be taking any questions. Sirs, over to you.

Thankyou, Rishi. It's great to be here with all of you. I thought I would take this opportunity to make an important announcement. As you know, Salil has been CEO of Infosys for almost 10 years. He came, I don't know how many of us were here 10 years back, but he came at a time when things were slightly unstable. And he brought in calmness, focus [to the company] from $10 billion to $20 billion, completed the transformation for the digital era and started the [real differentiation in the industry]. [Salil himself asked to retire on] March 31, 2027, and Infosys has been looking at his succession. And today, I'm delighted to tell you that the Board has appointed his successor, our new CEO, who will take over on April 1, 2027. He is from Infosys. He's been somebody who is a true-blue Infosian. He has worked in Infosys for 31 years. He's worked in every part of Infosys, be it in delivery, be it in sales, be it in account management, starting a new DC in Bhubaneswar, everything.

And he's someone who I think everybody likes, respects, is an uncomplicated guy who focuses on what needs to be done. His name is Ashiss Dash. So Ashiss is based out of L.A. He's been there for some time. He will move back to India, and he will -- in the next 2, 3 months, he will get -- do some CEO coaching or whatever. And then from October 1, Salil will take him on as his mentee and prepare him for the role so that he can take on this role of managing a complex $20 billion company in a very transformational time. So I just wanted to let you know that Ashiss will be the new CEO. And I'd now like to request Salil to say a few words about Ashiss.

Thanks, Nandan. So first, welcome, everyone. This is an incredible time for us, as Nandan shared, I've known Dash for a very long time working closely with him. Huge congratulations to him and in making sure everything he does works well into the future. He's had an amazing portfolio, the way he's built it, the way he's crafted it in terms of the clients he's worked with, in terms of the people he's worked with.

And there's a tremendous set of opportunities from that on to the overall company, the learnings from that as we apply to the overall company. Ashiss Dash, also a very collaborative individual working well with all of the various components within Infosys and having been here for a long time, has made sure he's learned everything and also understood how all different parts of the company work. So huge, huge congratulations to him and looking forward to working with him as we do the transition over the next few months.

I now invite Jayesh to join Salil on stage to commence the quarter updates. As always, for this section, I will request one question from each media house. But with that, let me invite Salil for his remarks. Over to you, Salil.

Thanks, Rishi, and thanks, Nandan, for that. So good afternoon, everyone. Thank you for being here. Our revenue growth for Q1 was at 2.4% year-on-year and 1% quarter-on-quarter in constant currency terms. We had a onetime revenue impact of a client decision during the quarter. Our AI services revenue was 8.2% of overall revenue in Q1. Our large deals, $3.6 billion at 61% net new, operating margin at 21.1%, free cash flow at $955 million. Earnings per share were up 15% year-on-year in rupee terms.

We saw a strong acceleration in our AI work, as I shared earlier, with AI revenues at 8.2%. This is growing at double-digit quarter-on-quarter for the last several quarters. With this momentum, we see long-term relevance of our services for our clients, which are all driven through AI. From our delivery team, over 80,000 employees are working on coding tools such as ClaudeCode or Codex or several others for our clients, for our work inside. We see strong traction across the 6 areas of growth, the new growth that we see in AI, our Hexagon for AI strategy.

We see client work, for example, in building agents for processes, work on data, modernization and using coding tools. We are building a team of frontier engineers to support our client work. Our plan is to have 6,000 Frontier Engineers over the next few years. We have built a platform, Topaz Fabric that enables our clients to get the benefits of AI while keeping the sovereignty of their own data within their company. Our clients are able to work with any foundation model closed, open-weight or on the cloud on their own servers. Our clients are able to optimize token cost, which has become very critical now to make sure it's the appropriate for the type of work they're doing and not out of hand. Overall, we continue to see the macro environment remaining uncertain. With our Q1 results and a view for the rest of the financial year, we are changing our revenue growth guidance to 1.5% to 3% year-on-year growth in constant currency terms. Our operating margin guidance remains the same at 20% to 22% operating margin. Thank you. And with that, let's open it up for questions.

Thank you, Salil. We will now open for questions. The first question is from Ritu Singh from CNBC TV18.

I know you've asked for one question. But if I may, Salil, you've given us a big news in this quarter. To begin with, since you speak about how you brought in and Mr. Nilekani spoke about how you brought in calmness at a time when the company was going through quite a bit. Even now you're speaking of this global uncertainty because of which you've had to, again, pull down your guidance as well. Why decide to leave at a time like now instead of perhaps looking at an extension? I wanted to understand.

And with the new CEO coming in, any mandate for the new CEO that you could highlight for us more clearly? And perhaps that's something the investors would also want to know. And then on the earnings, of course, the reason for this revision downwards, if you could give us a little more color on what you're seeing in the environment, where is the weakness? Where is momentum picking up?

Some of your competitors like Tech M have been talking about irrational competitive pricing. Wipro has also spoken about that a bit. So what are you seeing in the environment? And with a 1% kind of growth in the first quarter, do we assume the second half will be meaningfully better if you were to reach that upper end of the 3% guidance you're speaking about? And just on AI, if you could update us how the revenue is moving? Is it proceeding as per what your expectations were? Any updates you could share on that front as well as far as revenue contribution from AI is concerned?

So let me start with the first one. I think you had that question collectively for some time now. We have the answer. As I look at it, I'm really delighted with the role I've played here. We've taken the business, as Nandan said, from $10 billion to $20 billion. It's working very well. The digital transformation, now the AI transformation is launched. So I'm really delighted working well with our clients and with an incredible team that we have inside. So that's what I would like to say on the first one.

On the second, I think what we are seeing is an environment where a little bit sort of combining the third piece as well, AI services is growing extremely well, double-digit growth, if you look at it like quarter-on-quarter, if you look at it over several quarters in the past. We see that those 6 areas that we have identified like the process, the agents, the data, the engineering, all of those are working extremely well with our clients. So we are now looking at revenue growth in each of those areas.

Our pipeline is even larger than the 8%, which is the revenue today. So we see good traction in that. Therefore, we feel there's a good long-term relevance of our services to our clients because this is going to continue to grow as we look out into the future. Now the question on the guidance, we had a onetime impact that I shared with a client decision. There are factors related to what is going on in the macro environment, which we talked about. There are factors related to the volumes in the quarter. But we look at the large deal number, $3.6 billion, 61% net new. So we see a lot of support in that. We see -- I think there are 6 of those deals which are consolidation deals that we have been the beneficiary in as an example.

There are 4 deals which are just under the $500 million range. So just like a mega deal. So we see really good traction. The pipeline there is looking good. So all that when we balance, we decided to look at our guidance in a different way. The upper end of the guidance was really based on if the macro was improving, we now see the macro, it may improve, but not at the level that we were thinking initially. And so that's how we really constructed the guidance. But we have tremendous view this is a good place for Infosys to operate with AI the way it's looking and all of the work that we're doing on large deals gives us continued traction.

[indiscernible] Question of why you didn't decide to stay on and what the mandate of the new CEO is, and If the second half [will be] better. If you could clarify all of those points.

So there I think, as I shared earlier, my sense is we've had a tremendous -- I've been fortunate to have a tremendous sort of opportunity and what we've done in Infosys over the last many years and having taken the business from about $10 billion to $20 billion. So it's been an incredible journey. And that with the team we have and with the client work we've done, that's been a fantastic sort of an outcome.

On the mandate, I think as AI strategy is, well, like, put together and Dash has been part of that. So our thinking is that strategy we want to execute on. Of course, there will be some things which we will look at in terms of fine-tuning but that's a natural course of evolution. But the strategy is very well in place to make sure that, that goes into the next phase, making sure the partnerships we have with the various models, the Topaz Fabric that we built today.

On AI, it's important that clients see that their own data remains sovereign to them. And the way we build Fabric, it allows for the clients to do that no matter which model they're using. And so that's a very big differentiator we have, for example, in AI. The token cost, that will be an important factor, we think, in the future. And we have built like Fabric in a way that, depending on the task you are using the foundation model for, it will use the right model. So you don't have to pay for the most simple task like an expensive token cost and so on. So we think we're in good position in that. In terms of second half, first half, I think we have the guidance for the full year. We expect the normal seasonality that will come. We're not expecting anything unusual there.

Competitive pricing in the market that some of your peers have spoken about.

Yes. So maybe they are seeing that you should check with them.

The next question is from Reshab Shaw from Moneycontrol.

Salil, if you could tell us your biggest achievement and what will you miss the most and what's next coming for you. On the performance -- quarterly performance, how has been the TCV conversion because that's a worry that investors have. And the second -- and the third question is two of your peers have highlighted that AI revenue is slightly lumpy, and it could be 1 or 2 quarters post which you'll have to go and get those deals again. So is that something that Infosys is also seeing?

So let me start with the second one, I'll come back to the first. I think the TCV conversion, we see a pretty good way of converting now. What tends to happen is like when you have a consolidation deal, the conversion comes a little bit quicker when you have a transformation deal, it's a little bit sort of spread out. But that's the normal sort of conversion we see. We don't see that it's suddenly changed like in the last quarter or a couple of quarters or so on.

On the AI revenue, I think it's moving so quickly that it is a bit up and down on a quarter-by-quarter basis. So our thought is -- that's why we're saying like look at over the last several quarters, we see that double-digit type of growth quarter-on-quarter. And we will see sometimes it could be a little bit faster but it's growing nonetheless, meaning if you look at the secular trend, we see that is pretty strong, and that gives us a little bit of the view that long term, there's a relevance of what we are doing on AI for the clients.

For me, I think I'm very focused on what we have to do here at Infosys. We have a lot of things to get done. I want to make sure we remain in the leadership position. We win in the market, we are leading in AI, and I get a smooth transition done. So that's really my focus. And after that, I'll see what else happens.

Thanks, Reshabh. The next question is from Mansee Dave from ET Now.

Salil, my questions are on client spending, large deals and competitive positioning. So talking about the client spending, client budgets remain selective across industries. Have you started seeing any improvement in discretionary technology spending? Or are enterprises still prioritizing cost optimization over transformation? Talking about the large deals, Infosys has maintained a healthy large deal pipeline. So how confident are you that these deals will convert into faster revenue growth?

Also, every global IT company today is talking about AI. What would you say is Infosys' biggest competitive advantage in this AI-led technology cycle? And please start with this one, which moment during your tenure best reflects the values and culture of Infosys?

Okay. There was a few so I'll start with -- the first was a conversion of the TCV discussion, I think. We see that the large deals, we see a good traction of those values over the last few quarters have been strong. This quarter was pretty good. We see the pipeline to be pretty good on the large deals, and we feel there is a benefit of the consolidation that we are seeing in some of the large deals, which is definitely helping us as we go through it. The conversion, whether it's faster or slower, I think it's at the same type of a level, and we will convert those into revenue with 61% net new. It already looks pretty strong in terms of the net new work, which we'll see. And obviously, the renewals are going pretty okay as well.

On AI, I think there is a huge differentiation that I find from what we are sort of working on. First, we have a very clear AI strategy with the 6 areas of focus. We are investing in it. We've actually taken and Jayesh has shared in the past, he'll share also today. We have invested in building out AI capability. We have, as I shared earlier, 8% revenue, growing double-digit Q-on-Q over the last several quarters. We have a good pipeline in that area. Then you look at some of the stats, we have 80,000 people working on the tools today for client work. It's not just training and so on.

Then what we built with Fabric, I feel is very differentiated because it allows clients to maintain control of their data, maintain control of what they want to do with the AI and still use the different models, use lower cost. We have a harness through which they can leverage what they want to achieve with the foundation model. So that is a significant move up in terms of differentiation we've seen there. I think in terms of values, my sense has always been Infosys has incredible values, and it's really been sort of a privilege to be associated with that and learn from it and contribute to it. So in many ways, it's a great sort of fortunate thing that, that could happen in the way that it has happened.

The next question is from Shilpa Phadnis from The Times of India.

Can you please give us some color on how your GCC portfolio is doing because some of your peers who are slightly late starters are catching up. They are already looking at $1 billion in revenue run rate. So I just wanted to understand from you how it's doing? I mean is there a milestone that you have touched? And secondly, there's also a concern with Vanguard and Daimler and a lot of other companies are chipping into the space. They are setting up their own GCCs. How much of that compression are you seeing in the market?

So in GCC, in fact, my sense is you might have seen we launched the, like, AI GCC concept some time ago, and that we had a client event a few months ago, where all the leading GCCs of the country, their leadership teams were here in Bangalore on our campus, and we did like a 1-day session sharing with them what the latest developments were in overall and also in the AI GCC. So our traction on GCC is looking very strong. We don't, like, externally share the milestone, but our revenue growth is good. Our work with them is good.

In the GCC, there's always a life cycle. So there are some which are expanding well. And there are some in the past where they have exited and we've sometimes participated in that and so on. And that continues with the overall GCC like work both within the GCC and like the work we are doing with them, I think both are growing pretty nicely.

I have 2 questions, sir. When do you think AI-led revenues will be material enough to offset productivity-led compression that customers are seeing in the market?

I think, my sense is the AI-led revenues are extremely significant at 8% already. And if you look at the growth trajectory and if we execute on that well, and the growth trajectory continues, we can see now long-term relevance of AI revenues to our clients from what we are doing. The productivity will also continue. But I think it's both of those things because when we share our strategy and that Hexagon, we had outlined like a $300 billion market opportunity, addressable market. So that's all new revenue. And also the productivity will happen when the significance, I think already we can start to see here.

And if I can just add, if you look at when we launched our Hexagon in February of this year, our AI revenue for Q3 was 5.5% of our revenue. Today, it's already at 8.2%. So it's already significant -- it's growing at a very fast double-digit over double-digit growth, right? And at that pace, it is already becoming a growth engine in a way. So that it's becoming a long-term play in the way.

This is not reclassification in any format, right?

No.

Okay. Okay. One last thing, sir. On the status of hikes, Infosys has not called that out yet. So where are you on that? And secondly, also on Forward Deployed Engineers, there's a lot of talk in the tech ecosystem about this. But how difficult is it for a services company to sort of plug FDEs into the existing workflows. There are several challenges that companies are facing.

Let me start with the second one. We'll come back to the first. On Frontier Engineers, we have -- now have a very good plan, which has been put in place some time ago to scale that up. We have a lot of capability within Infosys, which are doing similar work. We are making sure that it works in the way that the frontier engineer needs to work with clients today. We've set the objective of 6,000 to make sure that the teams can work with different clients to make the impact.

We feel we have a good understanding of how that works because the capability is really the engineering plus the business context. And that's something that Infosys was good at even before the AI wave of work had started. And we are making sure that, that becomes very much part of the future in that. On the compensation increases, we will roll out our compensation increases in October and January in 2 parts, and that's part of something internal that we have announced now.

Yes, with most of the employees getting an increase in October and the senior employees will get it in January.

The next question is from Avik Das from Business Standard.

Just 3 quick questions and one for Jayesh. You talked about how the macro perhaps hasn't sort of improved over the last 3 months that you perhaps would have wanted to. Just wanted to understand, which are some of those parts of the macro that led you to first to increase it between 1.5% to 3.5%, now you sort of cut it down to 3%. So which are some of those areas which did not really work according to our expectations?

Number 2 is that would INFY ever at all, at least in the near future, would you want the company to move into the infrastructure business, data center, something that HCL and TCS has already done? And the last question is, what would you classify at least in your tenure as the most challenging period? Was it the COVID, or was it the -- or is it the AI-led transformation for Infosys?

And Jayesh, one question on the margins. Once you obviously roll out the hikes and with the growth projections sort of tapered now, do you think you would be able to maintain the 20% to 22% band at least for this year? Just wanted to know that.

Let me start off on the first one. I think a little bit later, Jayesh can also add a bit of color. I think on the macro, it's more -- I mean, what we see in the environment, we had a sense that the macro was settling down. So we had a guidance where the upper end looked at maybe things would settle down in the second half. Things are a little bit more uneven. But at the same time, it's not -- it could easily stabilize over time. So we've kept the option and we always have that ability because tech spending, discretionary spending can also come back if that happens. So we are not -- meaning we are sharing more what we see today as opposed to like a prediction of what is going to happen exactly in a certain time frame.

On the data center piece, so in fact, we've internally reviewed what we want to do in terms of our balance sheet. We've had a discussion with the management team and also with our Board. And we have decided to not do anything in that space at this stage. What was the third -- I think my focus in that is making sure that we are very much focused today on what we need to do for this part of the work that I have to finish. I'm very much sort of enjoying that, and we'll come to that at the right time in terms of what was in terms of the tenure and so on.

On the margin, Jayesh will have it, but yes, we will hold the guidance.

So at this point in time, we have given a guidance of 20% to 22%. If you look at our first quarter, we are at 21.1%, right? If you look at puts and takes of where we are, the currency will be a tailwind at least where we see today, Project Maximus is working well. If you look at the last 3-year period, we have been consistently able to hold or improve our margins despite investment in business, whether it is AI, whether it is talent or whether it is sales and marketing, and we believe the project will continue to deliver value from pricing, from utilization, et cetera. So that given -- of course, we'll have a headwind coming from the compensation in the second half of the year. But we are very confident at this point in time of the guidance band that we have given.

The next question is from Haripriya Suresh from Reuters.

One is I wanted to get some color on each of the verticals as well within financial services. Retail has seen some sort of hit this quarter as well. Some of your peers have called out some percentage of AI deflation in their portfolio. I mean, obviously, there's growth coming from AI, but also existing portfolio see some sort of deflation. If there's any number you can provide for that? And also on -- is outcome-based pricing becoming a larger part of your portfolio? And are there certain deals that tend to see more outcome-based pricing than others? Is there any kind of quantification you could offer, that would be very helpful.

I'll start on the industries. Jayesh will add a little bit. And then let me address the other one, which is on what we see on the outcome-based pricing and the compression piece that you mentioned there. On the industries, what you see right now is, for example, financial services, we see the growth in that part of our business will be higher than the average growth within the company. In Energy, Utilities part of our business, we will see something similar. We still see, for example, in retail, some constraints in terms of the growth that we're not yet seeing the pickup in that. And there might be other things that Jayesh will add.

On the compression, we absolutely -- I said in the past, we do see that in some places across our portfolio, but we've not externally quantified that compression at this stage. Was there anything else?

outcome-based pricing.

On outcome-based pricing, we see clients have a stronger interest in that. But typically, it's not so much that it's become a large part of our activity, but there is definitely more discussions on it. And typically, when the investment needs are heavy for transformation, it becomes more part of that discussion. But it's not that we are like shifting massively to it, but there is definitely more discussion on it.

Are there some [kind of deals] that tend to have discussions?

There is no particular type. It's more, I think, a function of other clients going through a transformation. And is there a need for some upfront investment, which can then translate into a transformation and then the outcome gives a benefit of that transformation.

The next question is from -- sorry.

So just to add to what Salil was saying on segments. Financial services and insurance, both is going to -- both we expect to deliver higher than the company average going forward or for the rest of the year. Manufacturing, while we had an impact coming from one of the clients, which we had called out last quarter as well. Despite that Manufacturing has grown very well at close to 1.5% or slightly over 1.5%. So I think that's commendable considering the headwind that the sector has seen.

Life Sciences, we will see benefit coming on the back of the acquisition in Healthcare and Life Sciences. So only 2 segments that continue to see challenges is Communication and Retail from that perspective. And just to add on the outcome-based pricing, that's one of the specific tracks within Project Maximus as well. So there is a leader at the organization level, who is working with all the segments and driving outcome-based pricing. And we have a very specific focus on that.

The next question is from Beena Parmar from Economic Times.

Just a bit on the consolidation deals, the 6 consolidation deals, which spaces are these in? And how many of these are large deals? And secondly, Infosys has lost some of the existing renewals, at least 3 in the know. What are the factors that led to that? What are your reasons?

On the guidance also, if you could just extend a little bit on the color on why really the upper limit was reduced. Do you see macroeconomic environment further worsening? Or do you see that conversations have been a little different from last quarter? [indiscernible] acquisitions and investments and which spaces will these be in? And lastly, what next for Salil Parekh?

So on the first one, I think the consolidation deals, the ones I was referring to all in the large deals. So those are not the ones -- we were only saying, like, within the large deal, we see those many consolidation deals, we're not specifying, like, in which areas, but these are typically in the bigger industries that we operate in. And there's big companies who are looking to consolidate across partners. And that's where we've seen it. But we're not specifying like which one -- where we see that.

What was the other one, sorry?

You lost some renewals.

Yes. So we don't comment on any specific deals in the environment in any case. However, we are quite clear that our focus overall is to make sure that we're working with clients on projects and contracts that make economic sense to us. But no specific comment beyond that. So no other specific comment beyond that. We want to make sure that economically, it makes sense to us in some of these situations as well.

Guidance.

The guidance, I'll also request Jayesh. I've also said a few things that he'll add to it.

What we see is given where we were in Q1, which is the outcome that we had with one of the delivery client decisions that I shared. We want to make sure that we have a guidance that reflects all of that. And then looking at the changes, whether it's in volumes, whether it's in some level of pricing mix. That's how we built the guidance. As we go through the year, we typically reduce the band as well, so instead of 2 points, it's now like a 1.5 point band as we go through the quarters. And that's how we built the guidance. Jayesh will add to it to your other question.

I think for me, really, the attention is on what we are driving through for this year, making sure that we continue to lead in AI, making sure that we continue to win market share and making sure that we have an absolutely smooth transition. I very much enjoy what I'm doing, and I'm sure once all of this is done, I'll have time to focus on what's next. Acquisitions, we are continuing to look at acquisitions. We have a good pipeline in that. We did the acquisition on health -- Life Sciences, Healthcare. We did the acquisition on insurance. We have other areas that we have an interest in.

So we have a view in geography that we are looking at some geographies where we could do more work, and those are good geographies. We could do more in some of the other industries as well, for example, we've seen good -- we're not doing anything, but we've seen that there could be things we could do in Telco and Financial Services, a little bit more in Healthcare. There are areas that we could do, which are more service line oriented. We think there's good traction in where AI can be leveraged into processes and agent building. So -- but there's a pipeline and we will continue with the acquisitions.

Just to add to what Salil was saying, and I'll come to guidance in a bit. On the consolidation deal of the 6 deals that we have won, it's a $700 million of net new business that we have won. So we have seen positive impact coming out of the consolidation deal, and we have been on the positive side of the market share.

On the guidance, whatever happens in Q1 typically has a cascading impact on the whole year. While we will see benefit coming out of the acquisition that we completed in Q1. The one-off impact that we had in Q1, the softer-than-expected volume and price that we got in Q1 will have a cascading effect on the rest of the year in terms of guidance. In terms of the large deal that we talked about with the European client where we decided to not bid beyond the point because it did not make commercial sense or economic sense as Salil said, that will have an additional impact in Q4 as the deal comes to a closure in December. So that is also baked in our guidance.

And if you compare to last year, we have additional headwinds coming from the lower on-site mix, as I called out in the last quarter because of our conscious decision of derisking our business model the deals that we lost in the last quarter from the same European manufacturing client, and that impact, which was baked in the original guidance as well. So all of this cumulatively results in our guidance, there are multiple models that lead to the lower end and the upper end of the guidance, and that's how the guidance is baked in.

The next question is from Sanjana from The Hindu Businessline.

Just two questions. Coming to rupee depreciation, how much of a tailwind has that provided to your margins in Q1 or going ahead, how do you see that panning out? And the other one is, how is AI improving or what kind of impact does it have on your employee productivity? And how is this affecting the revenue per employee metric? Just these two questions.

I'll start on the second one and Jayesh will come on the first. So we have seen -- if you look at not this quarter, but the previous several quarters, we've had a good improvement in productivity -- revenue productivity. We, generally speaking, see overall that there is a benefit from that productivity coming. Having said that, we are recruiting. We have recruited last year 20,000 college graduates. This year, we have a plan to recruit 20,000 college graduates. We've already done almost 4,000 in the first quarter. But equally, we see that there is a productivity benefit, then that will continue to come through. Then, of course, you also have pricing issues within the market, so those sometimes balance out. But if I look back, not this quarter with the previous several quarters, we've seen a continuous sort of expansion of that.

And on rupee depreciation, every 1% change in the currency or depreciation in dollar typically gives you anywhere between 15 to 17 basis points on margin. But the important thing to note also is whenever dollar appreciates against rupee, it generally appreciates against most of the currency also. And we have roughly 45% of revenue coming from non-U.S. geography and that kind of offsets some part of the rupee depreciation benefit.

The next question is from Uma Kannan from Deccan Herald.

With the rise in security incidents around autonomous AI agents and recent breach at model hosting platform, it's about OpenAI hack. How are you updating your approach to safety and security, just adding to it. Using cross domain network, is not a risk for your client database as AI tools will have full access to it? And also tell us about the guardrails you have put in place for AI systems.

So on the cyber, I think what we have done is, mad sure that, for example, when there was a whole discussion some time ago with Mythos, we had worked with the previous model, OPUS 4.7, made sure that we got an understanding of some of the security protocols beyond that, and build an approach that enabled our clients to have an understanding of the vulnerability and how to protect against it. And that's some work that we are doing with several clients. So our approach across cyber encompasses that related to the point that you made. I think each client environment has to have that sort of a cyber defense build and we have a way to support our clients when we work with them on the cyber area beyond working just on the foundation model area.

Our own approach to cyber within the Infosys incorporates that as well. And then that translates to like when we do work for our clients or when we do work for our clients through our security operation centers and so on. So that's broadly the approach we have.

So just one more question. You spoke about acquisition plans. One of your peers has invested in Indian AI firm. So do you have plans to invest especially in Indian AI firms?

So, we, generally speaking, have a view on what we have, like, an innovation fund, which invests in companies which are in very early stage and where we don't have essentially majority interest, we have a small minority interest in that. More from the perspective of seeing if that early or new technology can be deployed across our client base or can be leveraged in some way.

So that's like the way the innovation fund is working. We have several investments into that over the past years, a lot into data and analytics, but now in many other technologies. So in that light, we will look at all opportunities that are there without specifically saying yes or no to what you're suggesting. But in that broad context of the innovation fund, we'll look at it.

Next question is from Rohit Chintapali from Businessworld.

Give us an idea about the large deal TCV was about $3.6 billion with 61% net new. How is of this -- how much of this pipeline was tied to Agentic AI and Topaz? And the second part of the question is how -- what's the typical time lag when it comes to converting this TCV signing to, kind of, AI-led deals, the recognition of these AI deals?

So what has happened today with clients discussions is almost every discussion has some element of AI and of Topaz Fabric because Topaz Fabric is like a foundational thing. Many clients come, use it here, experiment with it and are using it. and we use Topaz across all of the work we are doing. So it's not like the total TCV is for AI, but it is -- without that, you are not able -- we are not able to participate because that's integral to the work that we're doing.

The conversion is the same in the sense of when the deals are signed, typically, depending on the type of deals if there are deals where we have some level of transfer, consolidation that ramp up pretty quickly and there are some deals which have a transformation and that activity starts and then the deals ramp up. So it's not like one thing for all the deals, but it's the similar thing of what we have seen over the past several quarters, not like suddenly the TCV has come and the ramp-up has not happened so for a long period and so on.

Also, on the transition, of course, does this transition about -- all about strategic continuity? How should investors kind of read into it? What do you want to see?

So they -- we have well-defined AI strategy today. We've looked at like the Hexagon with the 6 areas of the addressable market. We are seeing good growth, the 8% of our revenue, the double-digit quarter-on-quarter growth. So that's the strategy we will continue with as we go through into the next phase. And then, of course, I'll work with Dash very closely on the transition as well.

The next question is from Poulomi Chatterjee from Financial Express.

Just a couple of questions. I mean, you mentioned just now that the new kinds of AI deals are also a mix of -- like the more traditional ones and pure-play AI. How do you see the margins of these -- the new buckets of AI deals essentially evolving? And also, I'm curious, like, I mean, Infosys had offerings for small language models, specialized models in banking and IT Ops, I think, like do you see -- how is demand for these models? And has there been an uptick, especially since enterprises are moving more towards a more mixed model kind of?

Absolutely. I think that's exactly what we are seeing for the small language model for the banking is getting good traction. It's based also on our Finacle product set. So a lot of the clients there, it's an easy way to leverage a small language model in the parameter set is smaller. The cost of running it is smaller, the token usage is more efficient and so on. The same for the IT ops. So that's all part of that scaling. On the AI deals itself, we don't comment separately on the margin in terms of the quantitative value, but we are quite comfortable with the margin we are seeing here.

The next question is from Jas Bardia from Mint.

So in response to a previous question, on the mandate for the new CEO designate, you said there were some things that you would fine-tune. Could you just shed some more light on what these things would be? Second, amid all this talk of rising data center demand and slowdown in mainframe modernization, are you seeing clients spend more on memory chips, GPU? And if yes, are you seeing that lead to some sort of a slowdown in the traditional infra management work?

If I may squeeze a third question in. When it comes to deals and the demand environment, are you seeing AI, kind of, make the market a little more competitive between the mid-caps and the large caps such as yourself?

So on the first one, let me say this. I think our AI strategy is well defined. We are focused on the 6 areas, and that will continue. We see good traction in that. We see good growth in that. It's now becoming a large part of our revenue with 8%. And so that will continue, and that is the driving part of it. The approach that we will take is always look at what's going on in the environment.

We see, for example, today, there's a tremendous attention to token cost. There's a tremendous attention to ensuring there's a sovereignty of data within a client environment. But the overall strategy remains the same. Those sorts of things, we will evolve as we go along.

On the -- related to the infra environment, the costs, as you mentioned, of memory chips and so on. I think in general, these are all areas, whether it's infra, other areas where there's always a need for efficiency. And that is the overarching theme that we see, whether there's productivity improvements, a lot of our large deals look at cost and so on, and that's primarily the environment that we are in. Having said that, we are still seeing tremendous growth that I shared earlier in AI, which is absolutely new things that we are driving toward.

There's a question on deals and demand environment.

We see a few companies where we compete given our client base. And those are the ones that we look at. Sort of essential differentiator on AI that I shared earlier, but also on the quality of delivery and the depth of delivery is massive, and it's at least in my view, very difficult for, sort of, too many, if any company to really match up with that.

The next question is from Rukmini Rao from Fortune India.

Salil, given that if you're looking at Microsoft, which recently launched their frontier company and Anthropic looking at Claude, with big tech getting into AI services space. Are they going to be competitors where probably you and your peers may someday become just vendors giving in your engineers who -- given that partnership that you have with many of them, where your training lakhs of people on these models, right? Is -- will IT companies end up -- Indian IT companies end up becoming subcontractors at the end of the day, if these guys get into the game?

Two, is that going to -- if that happens, will that rob you from, say, the bigger opportunities that all of you have been talking about in the AI space that the massive opportunity that all of you think is going to be? But if the big boys get into this entire services space, is the future opportunity that you're talking about getting squeezed?

And second one, in conjuncture with all the problems with -- in terms of the cybersecurity part of these LLM models, right? When large corporations are looking at their own agentic environment, are our -- given your conversations with clients, are large companies okay to have -- be under the umbrella of just one ecosystem, let's say, just a Claude Enterprise kind of adoption, which we saw. I mean what happened with SaaS given the problems that is with these LLMs, will they ever be like an entire let's say, Copilot environment in which any enterprise would be okay to work or just an OpenAI sort of environment given the cybersecurity problems that are cropping up at very nascent stage of adoption?

So first, on the first one, I think if there are companies that want to enter the services space, so that AI can be made to work. It is actually a huge positive for Infosys because that means that what we do will continue to be done because that's what we do every day. Our job is to make AI work as services for clients. It now so happens that we have over 300,000 people doing that. We work with some 1,800 clients. So the scale, the context that we have with our clients is completely different. So to me, it's a huge positive.

Of course, we have happy to work with other companies, partner with them. That goes on in many different ways across time. But the first big thing for me is, at least if someone new is entering services means there's a very good future for services that they can see and therefore we can see. On the cyber, I think, absolutely, not just cyber actually, the data part also. So many large companies and clients want to be mindful of how they look at what is happening with their own data or even beyond that, what is the essence of the company, how they're making sure it just doesn't go outside and they lose some of their competitive differentiation.

So one of the things we've done in Fabric, Topaz Fabric is enabled the large company client to keep that within themselves. It's not even with us in that sense on Topaz Fabric is not with the model -- the foundation model company. So that allows them to keep what is essential for them with themselves. And that, to me, is a huge differentiator for us, and I think may become even more and more important as time goes on.

Salil, just to sort of clarify, when you say great opportunity, is it like, again, the whole subcontracting vendor kind of opportunity that you're talking about or Virgin, probably big contracts that are Microsoft would end up winning if they are an AI services company and you end up getting like a chunk of it and everybody else goes about the same way now and then vendor consolidation deal coming in about 5 years later, is that what you say when you're saying that you're optimistic about the opportunity?

No, no. I'm more looking at it like if someone with a few hundred people or a few thousand people you can get excited about services. We with 300,000 people will be very excited about services.

[indiscernible] People where probably what [Microsoft] would be bidding for, you will also be able to bid for at a scale that they can do with their company?

So my sense is like where we have understanding of our client and the context of that client. I think we are extremely well positioned in those places. I would say, better than maybe anyone else.

Thank you. With that, we come to the end of this press conference. We thank our friends from media. Thank you, Salil, and thank you, Jayesh. Before we conclude, please note that the archived webcast of the press conference will be available on the Infosys website and on our YouTube channel later today. Thank you, and please join us for Hi-Tea outside.

I welcome the members to the 45th Annual General Meeting. Hope all of you are safe and in good health. This meeting is being held through video conference in accordance with the circulars issued by the Ministry of Corporate Affairs and SEBI. Members participating through video conference are being considered for the purpose of quorum as per the circulars issued by the MCA and Section 103 of the Companies Act 2013.

We have the requisite quorum present through video conference to conduct the proceedings of the meeting. Therefore, I call this meeting to order. Before we start the main proceedings of the meeting, I request my colleagues on the video conference to introduce themselves. Nitin?

Hi. This is Nitin Paranjpe. I'm the Vice Chairman and Independent Director of your company, and I'm calling in from the Netherlands. Salil?

Good evening. I am Salil Parekh, CEO and Managing Director, joining in from Mumbai. Welcome to the 45th Annual General Meeting. I hope all of you are well.

Sundaram?

Hi, good afternoon. This is Sundaram, Lead Independent Director and the Chairperson of the Nomination Remuneration Committee and Risk Management Committee. I'm joining the meeting from Mumbai. Thank you.

Mike?

Good morning, good evening. This is Michael Gibbs, Independent Director. I'm the Chairperson of the Stakeholder Relationship Committee and the Cybersecurity Risk Sub-Committee. I'm joining this meeting from Houston, Texas in the U.S.A.

Bobby?

Hi, good evening. I'm Bobby Parikh, Independent Director. I'm the Chairperson of the Audit Committee of the company, and I'm joining this meeting from Mumbai.

Chitra?

Hello. This is Chitra Nayak, Independent Director and Chair of the ESG Committee, joining from San Francisco, California.

Govind?

This is Govind Iyer, Independent Director and Chairperson of the CSR Committee, joining in from Mumbai.

Helene?

Good evening. I'm Helene Auriol Potier, Independent Director, joining in from France.

Diane?

Hello, and good evening. This is Diane Jurgens. I'm an Independent Director. I joined the Board in April. And today, I'm joining the AGM from Greece.

Jayesh?

Hi. Good evening. This is Jayesh Sanghrajka, Chief Financial Officer. I'm joining in from Bangalore. Thank you.

Mani?

Hi. Good evening, everyone. I am Manikantha, Company Secretary of the company, joining in from Bangalore. Thank you.

Apart from them, we also have key executives and senior management joining from their respective locations. Statutory auditors and secretarial auditors have also joined this meeting. The company has taken all feasible efforts to enable members to participate through video conference and vote at the AGM. I thank all the members, colleagues on the Board, auditors and the management team for joining this meeting over video conference. I now request Manikantha, Company Secretary, to provide general instructions to the members regarding participation in this meeting.

Hi. Good evening. Members may note that this Annual General Meeting is being held through video conferencing in accordance with the Companies Act 2013 and circulars issued by the Ministry of Corporate Affairs and SEBI. The notice of the 45th AGM and the annual report for the financial year ended March 31, 2026, have been sent electronically to members whose e-mail addresses are registered with the company or with the depositories.

In addition, physical copies of the annual report have been sent to members who have requested for the same. Further, the company has sent a letter to shareholders whose e-mail addresses are not registered with the company or depository participants, providing them web link for where the annual report can be accessed on the company's website. The facility for joining this meeting through video conference is made available for the members on a first-come-first-served basis.

The company has also provided a webcast facility to view the live proceedings of this meeting on the company's website. The register of Directors and key managerial personnel, the register of contracts or arrangements, certificates as required under SEBI share-based employee benefits and Sweat equity regulations in 2021, and other documents mentioned in the AGM notice have been made available electronically for inspection during this AGM. Members seeking to inspect any of these documents can send their requests to the e-mail at [email protected].

As the AGM is being held through video conferencing, the facility for appointment of proxies was not applicable, and hence, the proxy register for inspection is not available. The company has received requests from a few members to register them as speakers at this meeting. Accordingly, the floor will be open for those members to ask questions or express their views. We will facilitate this session once the Chairman opens the floor for questions and answers. Members can also post their views or questions on the Ask a Question tab on the video conference screens before 4:30 p.m. IST. It may be noted that the company reserves the right to limit the number of members asking questions depending on the availability of the time at this AGM.

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Members may note that this AGM is being recorded. Please do not disclose any sensitive personal information or personally identifiable information belonging to you or any other person that has no bearing on this meeting. Thank you very much.

I now request Nandan Nilekani, Chairman, to address the shareholders.

Dear shareholders, welcome to the 45th Annual General Meeting of Infosys. On behalf of the Infosys Board of Directors, I appreciate your support for the company, and thank you for taking the time to join us today.

Fiscal 2026 has been a year of disciplined execution and resilience for Infosys even as the external environment continues to evolve. We delivered USD 20.2 billion in revenues, growing 3.1% in constant currency while maintaining a strong adjusted operating margin of 21% and generating USD 3.7 billion free cash, which is 112.6% of net profit. This is the second consecutive year when we have generated free cash flows of more than 100% of net profit.

Large deal TCV for fiscal 2026 was at USD 14.9 billion with 55% being net new. This reflects the strong trust our clients have in us and relevance of our strategy and provides a robust foundation to build on in the months ahead. For fiscal 2026, the Board has recommended a final dividend of INR 25. Along with an interim dividend of INR 23 that is already paid, total dividend is INR 48, which is 11.6% growth year-on-year. The total payout for FY '25-'26, including the recently completed buyback will be 113.9% of free cash flow. With this, we have returned 82.1% of free cash flow cumulatively for 2 years under the capital allocation policy.

Nitin Paranjpe, who is an independent Director, has been appointed as Vice Chairman of the company effective April 30, 2026. During fiscal 2026, no directors or KMP were appointed. However, post fiscal 2026, based on the recommendations of the Nomination and Remuneration Committee, the Board appointed Diane Jurgens as an Independent Director effective April 22, 2026, for a period of 3 years till April 21, 2029. The Nominations and Remuneration Committee has also recommended the reappointment of Helene Potier for a second term of 5 years. Accordingly, post fiscal 2026, the Board approved a reappointment as an independent director from May 26, 2026, to May 25, 2031.

Both the appointment of Diane Jurgens as an independent Director and reappointment of Helene Potier as an Independent Director for the second term have been approved by the shareholders via the recently concluded postal ballot.

On the business front, the industry is going through a major technology transition and whenever there is such a transition, questions are asked about our relevance, leadership or ability to maintain growth and margins. Given that AI is a much larger and disruptive technology transition than ever before, the questions are louder and the doubts are more insistent. Moreover, the existential question that is being asked of us is, if coding becomes automated, then why are we needed at all?

Now more than 3 years after Gen AI's launch, Infosys is more relevant than ever before and well positioned for the decade ahead. While we embrace the best coding tools and improve our productivity, there's much more to do in the software development life cycle. Enterprise context is paramount. Solutions must complement existing investments. They demand rigorous testing, resilient architecture and foundational cybersecurity. Data governance must reflect an organization's own obligations, not the convenience of any external platform or provider.

The AI deployment gap in our large enterprise clients is real and closing that gap is where the work is. AI will not replace companies like ours. It will amplify those who move with purpose and adapt with speed. The AI revolution has made legacy modernization urgent in a way nothing else has, and clients are moving to retire the technical debt accumulated over decades. The preference will be to build versus buy for software. All this creates even larger opportunities for us.

The defining opportunity lies in integrating intelligent AI systems with mission-critical enterprise platforms. The greatest value will come from combining the world of models and agents with traditional transaction systems that continue to underpin enterprise operations. That convergence is where the next wave of opportunities will emerge. Our clients trust Infosys to bring hard-earned learning to help them navigate the complexities of enterprise AI. Infosys is fully prepared to deliver on that trust and help our clients navigate the next. We're already collaborating with 90% of our top 200 clients on their AI journeys.

Increasingly, they see Infosys as a trusted partner to unlock AI-led value across growth, efficiency and innovation. The strategic investments we have made and continue to make in Infosys Topaz position us well to guide our clients as they navigate this structural shift in technology. Combined with the cloud strength of Infosys Cobalt, we are enabling clients to scale AI with speed, confidence and enterprise relevance.

We recently unveiled our AI-first value framework to help global enterprises unlock value -- AI value at scale. This positions Infosys to tap into an AI-first services opportunity of USD 300 billion to USD 400 billion by 2030. Continuous learning and talent transformation have been core to Infosys for many decades. The AI era requires fresh learning and new mental models.

We are systematically preparing our talent for this new era while redeploying those released to productivity gains towards new areas of growth. We recruited over 20,000 college graduates this fiscal year and ended with a workforce of over 325,000 employees. During the year, Infosys was recognized as a global top employer in 20 countries for best-in-class HR practices. We were also named one of India's Best Employers among nation builders 2025 by Great Place to Work.

We have built a strong AI partnership ecosystem spanning compute and cloud platforms, model developers, data and analytics providers, applications and security technologies. This enables best-in-class AI solutions with the flexibility and resilience required for AI-native agent-driven enterprises.

During fiscal 2026, we completed 2 acquisitions: MRE Consulting Limited, a leading energy and business consulting firm based in the United States; and the Missing Link Group, a cybersecurity service provider based in Australia. During the year, the company also entered into definitive agreements on 3 strategic fronts. Infosys will form a joint venture with Telstra acquiring a 75% stake in the Versent Group, Australia's leading digital transformation solutions provider and a wholly owned subsidiary of Telstra Group Limited, delivering cloud and digital transformation services.

We also agreed to acquire Stratus Global LLC, a leading insurance consulting and technology services company focused on guidewire services and headquartered in the United States. And Optimum Achieve Holdings, Inc., together with subsidiaries, including Optimum Healthcare IT, LLC, a leading health care digital transformation and consulting company headquartered in the United States. Both these acquisitions are now complete.

Long-term success must be responsible, inclusive and sustainable. Our ESG vision for 2030 reflects that conviction through positive climate action, inclusive and equitable practices and earning stakeholder trust through ethical governance. We have achieved carbon neutrality for the seventh consecutive year across our global operations through reduced consumption, renewable sourcing and high-quality carbon offsets. Renewables now account for 81.8% of our India operations, and our campuses recycle 100% of wastewater through large-scale rainwater harvesting and demand side efficiency measures.

11 campuses have achieved true zero waste certification, reflecting the scale and consistency of our circular economy approach across geographies. At Infosys, our purpose is to amplify human potential and create the next opportunity for people, businesses and communities. We continue to expand our social impact program through Infosys Foundation, Infosys Science Foundation, Infosys Prize and Infosys Foundation USA, addressing education, skilling and livelihood training, health care, women empowerment, science and research and environmental sustainability.

During this year, in India alone, Infosys Foundation undertook 200 projects impacting 7 million lives. We have reached 15 million people through digital skilling initiatives anchored by Infosys Springboard, our flagship digital learning platform. We have also been recognized as the world's most ethical company for the sixth consecutive year by Ethisphere, a reflection of our continued commitment to responsible growth. We have been ranked as the fastest-growing IT services brand over the past 6 years by Brand Finance. Infosys is a natural choice as an AI transformation partner.

It is said that to anticipate the future, we should skate to where the puck is going. In this case, the puck is coming to where we have already positioned ourselves. On behalf of the Board, I want to thank our employees, clients, co-founders and governments of the countries and states where we operate for their trust in us and generous support. To all our shareholders, it is your encouragement that drives us to deliver our best every day. Our heartfelt thanks to you all.

I now request Salil Parekh, CEO and Managing Director to address the shareholders.

Thank you, Nandan. Good evening, shareholders, and welcome to the Annual General Meeting. Over the next few minutes, I will share with you some of the highlights of the financial year and what we are looking at as we go ahead.

As we look at the next slide, the safe harbor provision, then the next slide. Financial year 2026 was a strong year for us. First, we had a revenue of over $20 billion. Constant currency growth was 3.1%, adjusted margin -- operating margin of 21%, very strong free cash flow, employees now at over 325,000 across the world.

One of the key elements there was that we recruited 20,000 college graduates across India and in some other parts of the world as well as we continue to scale in this new environment as we do more and more work within AI. Our clients with revenues of over $100 million were at 41 as we closed the year. As we look at the next slide, if you look at the financial performance, we have shared this in this slide in rupees. In many of the areas, we had a nice positive movement from the last year.

In terms of cash flow, we had a positive movement, which was reflected after you adjust for some of the tax refunds that we got in the previous financial year. As we look at the next slide, we have now returned over INR 55,000 crores over the past 2 years through the capital return policy, both in the manner of dividends and also with the buyback that we completed. This continues with the approach we have for our capital return policy, which will be across a block of 5-year period where we return 85% of our free cash flow.

Our balance sheet remains extremely strong. It's debt-free. There's no debt. In fact, it's very liquid with a strong balance of cash and cash investments, which we continue to maintain even as we provide the capital return to shareholders, and we continue with some acquisitions.

As we look at the next slide, one of the most critical areas we have focused on in this past year has been to launch our AI approach within the market. Internally, we've been working on this for a number of years. We have built internally something which we refer to as Topaz and Fabric, which allows us to make very strong AI capabilities available to our clients in partnership with AI companies.

As you look at the next slide, this is the approach that talks about how we go to market with all of that AI capability. We have seen today, there are 6 broad areas in which clients are looking to use AI to improve their business for growth or improve their business in terms of the quality service levels or improve their business in terms of efficiency and cost.

The first area refers to really AI engineering and strategy, where we build agents across different platforms and tools. The second to data, which is a critical element of putting AI together. The third is process where a lot of new work is being done to first make the process more efficient and then use agents to make that process work better. The fourth is really modernization of technology using agents. This we see as one of the largest areas today that our clients are looking to Infosys to help them with. The fifth is the physical AI, which is you look at a real AI in manufacturing and put the software into those manufacturing elements where the products are there, whether it could be in medical, whether it could be in automotive or any of the other areas. And the sixth is the AI trust where we look at how do you make sure that it is secure and is also responsible AI.

And when we look at this as a collective group, we see that this is approximately $300 billion of addressable market overall in those 6 areas, which is from today on to 2030, so over the next 5 years. And that's what gives us a real focus on how we drive the growth there.

In this slide, we show what are the different clients that we are working with in each of those 6 buckets today. So these are actual projects. These are not the proof of the concept. They are large-scale programs, which our clients are trusting Infosys with to make sure that we deliver this sort of work for them today.

On the next slide, we talk about as an overall journey, how are we helping our clients to move from where they are today to the future, which is really very much AI-driven because we have this really deep understanding of their environment, what is in a client environment, what is in a large enterprise environment? How is the technology set up? How does it interact with the business? What is the architecture landscape, what is the data landscape? That domain knowledge is really the value that we are bringing and which is why we are seeing a strong connect that our clients are having with us to make the AI successful.

We also have extremely good engineering talent. We have shifted a lot of our training on to the AI training, and we have more and more of our employees ready and certified on the different foundation models, coding tools, compute platforms that are available for the AI. And then we have built our own platform in IP, which is the Topaz Fabric, which allows us to work with any AI foundation model for the benefit of the client. In doing that, we have built a very strong partner ecosystem. So all of the big AI foundation model companies, the compute companies are working with Infosys very closely to make it available for the clients based on what the situation is, which industry, what type of work, different foundation models become relevant for that. And we have a very strong partnership approach to driving that.

As we look in the next slide, here in Q3 of last year, we had shared this data that approximate -- that 5.5% of our revenue was in AI services, which is approximately $1 billion annualized. And this is growing at a quite fast pace we had given that when we shared it in Q3. So we reconfirm that, that is how we are driving this, and we continue to see good growth in this AI services revenue.

And then on the next slide, we show that also on the thought leadership, meaning how is the analyst community looking at Infosys. In any of the groupings, there are 16 areas across these 6 buckets where we have the leadership rating for AI, which Infosys is being recognized for.

Then I move on the next, there are 2 big foundational elements of AI. The first is the cloud. And here, we have built Cobalt over many years, and we have a very good first capability, then partnership and then the ability to use the cloud compute platform to make sure that the AI is working well and make sure that the migration is working well. A lot of the different foundation models are working on multiple cloud platforms, and that's where the strength comes of Infosys having had that skill and capability from a long time.

And the second is the data. As you look at this slide, there is data within the enterprise, which is structured, which is unstructured. How is it? How can we make all of that become available for the AI model because the value for a large enterprise is to take its own data and make it populated in the model so that it becomes more intelligence for the company to benefit, for the enterprise to benefit. And we then ensure that the data is also secure and trusted so that it's not something which that the enterprise may feel not dependent upon, and so they can continue with the differentiation, which is coming from their own knowledge, their internal data and knowledge that comes together.

And then we are now bringing enterprise -- enterprises are bringing customer and supplier data also in addition to their own, which is enhancing how the models are working within large enterprises. Then as we look inside the company a little bit, we have been focused very much over the last several years on our own efficiency because we want to maintain and as you saw in the previous financial year, we increased our operating margin. We want to make sure despite the environment outside, we want to have a very strong operating approach.

And there, we have driven a lot of the cost efficiency with the automation, with the pyramid, with the productivity where we are ourselves are using the AI in many places, for example, in finance, in marketing all of our internal functions, of course, in coding as well, which is giving us productivity benefits, then improving some certain portfolio elements and then reducing our indirect cost to make sure that we have the foundation for a good profitability.

The strength of Infosys really comes, which I've always felt from a very much leading delivery organization, where we have excellent training and very well-driven teams that make sure that what we are committing to our clients, we are able to deliver and now more and more in multiservice offerings, in complex programs, where there's a lot of trust from our clients and now in the 6 new areas of the AI, where we put even more attention and focus.

Then on the brand, we have done, I think, quite well where our brand is recognized more associated on AI, top 3 most valuable brand globally, one of the fastest-growing IT services brands, top 100 of any brands in the world in the last financial year and good perception with AI for Topaz and for cloud with Cobalt.

Then we also took some time at the acquisitions. We had finished a few in the financial year. A couple of them got done just after the financial year, but before today, one was on health care side, one was on the insurance side. So we want to make sure in the areas where we see a good opportunity and where we can scale up, we are doing more and more of those type of acquisitions, which we are then able to integrate into our business quite well.

Then we wanted to share a little bit with how we are working across all the communities we are in the part of. We have created a lot of impact within India with the contributions the company is making, 200 projects, 7 million people with Springboard, which is a training online capability, which we provide for free, over 10 million people worldwide have benefited.

And one example where we have worked with making sure that the water capacity in lakes within different parts of India is enhanced by providing sustainable solutions. All of this comes within the area of supporting the communities in the CSR work we are doing. One of the biggest difference -- ways we are approaching the market is how we work internally as one Infosys, whether it's with the service lines, in the industries, in the geographies, making sure that the best capability of Infosys is available to every client and all of the teams inside are continuing to work well together.

In conclusion, I would say it was a strong execution on the financial year. We have a good AI approach and strategy and already starting the execution. We already see approximately annualized $1 billion of AI services revenue that we shared in Q3 and growing at a very good pace. Very strong AI partnerships. The foundation model companies are also approaching us, and we are working strongly with them, a good, stable organization, the One Infosys and a continued trust of our clients. So with that, I will conclude. Thank you once again for all your faith and trust in us, and we look forward to the coming year to be more and more AI-driven into the future.

Thank you.

Thank you, Salil. I now request Manikantha, Company Secretary, to provide a summary of the auditor's report.

Thank you, Nandan. The statutory auditors, Deloitte Haskins & Sells LLP and the Secretarial Auditor, Makarand M. Joshi & Co., have expressed unqualified opinion in their respective audit reports for the financial year 2025-'26. There were no qualifications, observations or adverse comments on the financial statements and matters which have any material bearing on the functioning of the company.

The statutory auditor's reports on the stand-alone and consolidated financial statements are available on Page # 226 and 307 of the integrated annual report. The secretarial auditor's report is enclosed as Annexure 5 to the Board's report on Page #91 of the integrated annual report.

Thank you.

Thank you, Mani. As the notice is already circulated to all the members, I take the notice convening the meeting as read. Before we proceed, I am pleased to bring to your notice that as required under the Companies Act 2013, the company has provided you the facility to cast your vote electronically on all resolutions set forth in the notice. Members who have not cast their vote electronically but are participating in this meeting will have an opportunity to cast their votes through the e-voting system provided by NSDL. Members may please note that there will be no voting by show of hands.

We now take up the resolutions as set forth in the notice. We will open the floor for any questions by members after all the resolutions are tabled. Accordingly, I will now only read out the resolutions. Item #1 of the notice, adoption of the financial statements. The financial statements of the company, including the consolidated financial statements for the financial year ending March 31, 2026, including the reports of the Board of Directors and auditors, have already been provided to the members.

Item #2 of the notice, declaration of dividend. To declare a final dividend of INR 25 per share for the financial year ending March 31, 2026. You would recall that an interim dividend of INR 23 per equity share has already been paid for the financial year ending March 31, 2026.

Item #3 of the notice, appointment of Nandan M. Nilekani as a Director liable to retire by rotation. The text of the resolution is provided in the notice circulated to the members. Item #4 of the notice, approval of the proposed amendment to the Infosys Expanded Stock option ownership program 2019, the amended 2019 plan and grant of stock incentives to the eligible employees of the company under the amended 2019 plan. The text of the resolution is provided in the notice circulated to the members.

Item #5 of the notice, approval for a proposed amendment of the Infosys Expanded Stock Ownership program that is 2019, the amended 2019 plan and grant of stock incentives to the eligible employees of the company's subsidiaries under the amended 2019 plan. The text of the resolution is provided in the notice circulated to the members.

Item #6 of the notice, approval of the request for reclassification of certain members of the promoter and promoter group of company to public category. The text of the resolution is provided in the notice circulated to the members. The members may note that in accordance with SEBI regulations, the applicants and the persons related to them shall not vote on this resolution.

If any member desires to ask any question pertaining to any item on the notice, he, she may do so now. Members are requested to keep their questions brief and specific. To avoid repetition, answers to all the questions will be provided towards the end. Members may also note that the company reserves the right to limit the number of members asking questions depending on the availability of time. While members are queuing up to ask questions, may I request the team to play short videos of Infosys.

[Presentation]

Dear shareholders, thank you for joining our 45th AGM today and for taking time to participate in the proceedings. Before we go live with the Q&A, here are some points to note for your convenience. When your name is called, and you are projected on the screen, please mention your name and location from where you are joining and proceed to ask your question. Each shareholder will have 2 minutes for the questions. To avoid repetition, the Board will respond to all questions at the end. Once you have asked your question, you can switch to watch the proceedings. The Board will be taking questions from shareholders in 2 or 3 sets depending on the number of questions on video.

With that, I'll request the first shareholder, Mr. [ Dharav ] to proceed with the question.

[Foreign Language] I must say greetings to respected Chairman, Board members and all the stakeholders of my company. It is indeed a privilege to attend this meeting. My name is Dr. Dara Vipul Jamadar from Surat Gujarat, a proud shareholder of our company. Firstly, heartiest congratulations to all the stakeholders for such a robust performance consistently year-on-year.

Respected, sir, inevitably, these are some very challenging times, which not only our company, but the whole industry worldwide is going through. Exomatically, that exists. So for many, which questions are very existence, but investors will have to have some patience as Rome wasn't built in a day. We too will create a competitive moat in the coming times like always we have done. So I fully understand and support my company in this daring and adrift times.

Certain questions which I would request our respective Chairman to address are: First, last year, despite many disruptions, we ended FY with an all-round robust performance, but the industry as a whole is either growing negatively or in a lower single-digit range. So have we gone past those glory days when there was a double-digit growth rate? Are there any signs that the industry is out and now in order to regain the past glory, we need something very path breaking. Even in terms of our margins and ROCE, the path looks a bit hazy as even during such times when our currency has been persistently and significantly getting depreciated, we have not been able to convert those in margins expansion and increasing our ROCE. What are your views on these 3 aspects?

Second, there have been disruptions of all kinds from technology to geopolitics from east to west side of the globe. Each sector is getting severely impacted. So turning to geographies and industries, which geography and industry we serve will be the most stable and grow at a robust pace and which one will be facing the most disruptions in the coming times?

Third, in regards to global and national level macros, which are turning dynamic and volatile, some of them highlights out are El Nino happening this year, fear of economy entering into higher interest rate cycle, rising inflationary pressure, highly volatile energy prices, currency persistently and significantly getting depreciated and much more. How do you see an uptick in public and private CapEx for IT services. Which counter of deal wins metrics will experience maximum growth and which one will see drag in this FY?

Both our free cash flows and ROCE have always been industry-leading. But can you please elucidate on how are we planning to fund our next or exploring segments like AI data centers, quantum computing and much more as it requires lots of capital and worldwide, companies are raising lots of debt via leveraging debt. So will our growth or the future funding of the growth will be highly leveraged? And how will our capital structure look like? What will its impact be on our dividend distribution policy and ROCE?

Fifth, supposedly due to our large size, we are unable to transform or we take a bit more time and expand at a significant rate in AI. Will it be wise enough to somehow invest in global AI giants or even take M&A routes for some -- kindly share your views on the same.

Lastly, our nation has lately secured many FTA packs with many developed nations worldwide. We already exist in many developing as well as developed nations globally. How do you believe a company like us will be taking its advantage? Furthermore, if you were to ask for some new relaxations or regulations for our industry from the government, what would they be? Thank you, sir, for providing this opportunity. It's an honor.

Thank you, Dr. [ Dharav ]. We'll move to the next shareholder, Mr. Vipul Kumar Shah. Mr. Vipul, kindly go ahead and ask your question.

Good evening to Chairman sir, Board of Directors and my fellow shareholders. So my first question is regarding the extension of tenure of our CEO, Mr. Salil Parekh, who has done a wonderful job since last so many years. If I am not mistaken, his term is coming for renewal next year. So is Board more seized off the matter. Is Board considering extension or Board is looking for any another candidate? This is an overhang on the company, which needs to be cleared as early as possible. So I would request you to add your views.

My second query is regarding we give guidance since decades. I am the shareholder since IPO. Of course, the intention is noble, but it has unintended consequences like too much volatility in the stock prices for minor bits or minor misses in particular quarter where one contract revenue may slip into another contract. So I would request the Board to seriously reconsider whether guidance is necessary. According to me, guidance should be scrapped because our larger peer is not giving any guidance. And I find that volatility in their stocks after results, albeit is generally less. So this is just my own view. So I request Board to consider this matter as well.

And second, what was our revenue contribution from AI-related offerings for last financial year. And what type of growth we should expect from that offering? And what is the margin difference between AI-related services and normal services? That is my third query.

And lastly, on Analyst Day, our Chairman, sir, Mr. Nandan Nilekani, on his opening remarks, had made one very interesting comment, which I found very interesting that in AI world, opportunities are endless, only risk is execution. So I would request, sir, to elaborate on his comments and how we are moving in that direction. Thank you and all the best, sir.

Thank you, Mr. Vipul. Now I'll request the next shareholder, Santosh Kumar Saraf. Sir, kindly go ahead and ask your question.

Yes, yes. Good afternoon, Chairman and Board of Directors and also those who are attending. I am Santosh Kumar Saraf from Calcutta. [Foreign Language].

Yes, sir, we can hear you.

Sir, I want to know Infosys successfully closed $20 million revenue milestone. What are the top 3 strategies that will help company reach to $30 billion revenue and while maintaining industry-leading margin, creating superior shareholder returns. That is my one question, sir. Nothing to ask, and wish for financial year 2027 to all our Chairman, Director and employees, healthy, wealthy and good year.

Sir, I also wish to our moderators for good service. Thank you, sir.

Thank you, Mr. Santosh. Now I'll request the next shareholder [ Bharat Shah ], unmute yourself and ask the question.

[Foreign Language]

Thank you, Smitha Shah and Bharat Shah. Now I'll request the next shareholder Om Prakash Kejriwal.

Myself, Om Prakash Kejriwal, equity shareholder from Calcutta. Thank you, sir, for providing the platform for me to speak something for you. Thanks to our secretary department, especially Manikantha for calling me and taking my know-how. This is my fifth AGM only due to virtual.

So if possible, please follow this virtual AGM in next year also so that more and more investors from different parts of the world could join our AGM and express their views and company could take benefit from their views. So many, many thanks to your people for increasing our dividend from INR 43 to INR 48 on face value of INR 5. It is very good distribution, sir.

Sir, there is just saying, [Foreign Language] our share price is falling every day. Today, it is almost INR 1,030, 12-month low. Sir, do you know why it is falling, because we are not investing in futures. And so foreign investors are dumping our shares. Today, market cap of Google is $4.5 trillion, more than our whole Indian capital market.

Sir, today, investors are looking for growth and growth will come from your investment in future. You can see the growth of Taiwan and South Korea. These 2 small country capital market cap is more than our country's capital market cap. It is only due to investment in future. Sir, this is a wake-up call not only for our company, but also for Government of India. Government is investing huge money as well as man hours in conducting SIR, though it should invest in skill development. Sir, today investors do not like buybacks. You can see the position of our company shares and with pro shares after buyback. Sir, you people have destroyed INR 1,800 crores on buyback.

At the time of buyback, I sent 3 mails for rectification in buyback. If you follow my suggestions, our capital could be reduced up to 80%. You please go through my mails. From this buyback, no long-term investors, including promoters benefited. Sir, I think I hold so many shares in our family members' accounts, but I did not participate in this buyback because our balance sheet would be destroyed if we participate in this buyback.

[Foreign Language] sir, I respect you very much. you gave to our country at the time of Congress, which is today used widely in DVT schemes. Salil, sir, I respect you very much, you gave new software to our income tax department. So please invest in futures. Please invest in skill development. [ Forces ] my company, and so I'm always thinking for its betterment. Please maintain your smile and be cheerful. We are always with you as a long-term investor. Thank you.

Thank you, Mr. Om Prakash. Now I'll request the next shareholder, B. Ram Kumar. Mr. Ram Kumar, kindly go ahead and ask your question. I'll move to the next shareholder. Dinesh J. Bhatia, Mr. Bhatia kindly go ahead and ask your question. I'll request the next shareholder, Mr. Krishan Lal Chadha. Mr. Krishan Lal, if you are on, kindly go ahead and ask your question. I'll move to the next shareholder, Mr. Reddappa Gundluru. Kindly go ahead and ask your question. Mr. Reddappa Gundluru, we can hear you.

Respected Chairman, Mr. Nandan Nilekani, Honorable CEO; and Mr. MD, Salil Parekh and all other directors and my company secretary, Mr. Manikantha and my fellow shareholders, good afternoon to everyone. [Foreign Language]. Sir, myself, Reddappa Gundluru, and I am joining this AGM as a proud shareholder from Hyderabad.

First of all, I would like to congratulate the Chairman of the Board, management team and all the employees of Infosys for the another year of the resilient performance amidst global economic challenges, uncertainties, my company is doing very good. The annual report presentation is very clearly reflect the company's commitment to the excellence, innovation, governance, the long-term value creation. Chairman sir, Nandan sir, Salil sir, your speech is very wonderful, sir.

Mr. Nandan, your visionary leadership continued to strengthen my company, Infosys position it as one of the India's most respectable global technology companies. Under your guidance, Infosys has been maintained high standards of the corporate governance, transparency and shareholder engagement. Mr. Salil, congratulations to you and your entire team for delivering the good steady growth, strong client relationships and operational excellence.

My company focus on AI, digital transformation, cloud services and next-generation technologies and helping Infosys to remain a trusted partner to the global customers. I would like to appreciate the company for the consistent corporate transparency, world-class corporate governance, ethical business practices and also CSR activities meaningful, the planned triphathi activities benefiting the education, the IT, health care, sustainability and community development.

The rewarding the shareholders through the healthy dividend, the long-term value creation, so legacy around continuing to maintaining a strong balance sheet and the global reputation. Special thank appreciation to Manikantha, the Company Secretary and entire secretary team to ensuring the smooth conduct AGM, meaningful through high standards of shareholder communication. I would like to also especially thanks to Mr. [ Rakesh ] from the CS team, always reachable excellent support.

Sir, I have few questions. Sir, what are the company, the key growth -- the priorities for the 2 to 3 years. I would like to know, especially in the areas of artificial intelligence and the generative AI?

Second question, sir, how does Infosys plan to improve the revenue growth and deal conversion into the current global economic environment? Third questions. What opportunities does the management see from the increasing the digital transformation, spending by growth enterprises? Fourth one, we have, only 5, last couple of sir. Can the management share the outlook on the employee retention of the talent development, skill development, emerging technologies?

Final question, sir, is there a money company considering the new strategic acquisition and strengthen its capabilities in AI, cybersecurity and cloud services? Thank you, sir. Before I conclude, once again, congratulate the Chairman, Board, management team and all the employees of Infosys for the outstanding effort. I support the resolution placed before the meeting, Infosys to greater success, to growth and continued leadership on the global technology industry.

Sir, finally, we have faith in Salil and Nandan sir. all the Board of Directors. I pray God to give more wisdom, strength, power to entire Board of Directors and Company Secretary. Thank you for giving the chance to meet, Reddappa Gundluru. I have very good memorable photographs. Nandan sir. Thank you, sir.

Thank you, Mr. Reddappa. Now I'll request the next shareholder, Mr. Bharat Raj. Mr. Bharat, please go ahead and ask your question.

Yes, very greetings, Mr. Chairman, entire Board of Directors. I'm from Hyderabad. Mr. Salil, I'm very happy around 7 plus years. I hope you complete the tenure also. And thanks for the dividend payout. And Mr. Salil, my leadership, never received any bonus. So what is your plans on bonus, liberal bonus. Mr. Salil, what is your plans regarding the ASF? Recently, your price has come down 10% regarding ASF, so how you face this challenge.

Global changing now. AI, ChatGPT, a lot of issues are coming. So how do you sustain in coming market. And that is my only request. I thank Manikantha for sending me link. So I'm traveling here. I'm present in airport. Thank you, Mr. Manikantha for giving me this opportunity. And can maybe send me link once again, Mr. Nandan. I request you one more request. I request you to receive Mysore, you given sanctions. Now it is fiscal. It is fiscal Mangalore campus. All speaker shareholders please arrange a Mangalore campus so that we can go and see. That is only request from my shareholders. Thank you once again. I'm Bharat signing off from Hyderabad.

Thank you, Mr. Bharat. Now I'll request the next shareholder, J Abhishek. Mr. Abhishek, kindly go ahead and ask your question. The next shareholder, Mr. Sham Sundary sorry, P. Sham Sundary, please kindly go ahead and ask your question.

Good evening, respected Chairman, Managing Director, Board of Directors, Secretary and his team and my fellow shareholders. Sir, I am a joint holder. My name is P. J, along with my assistant, P. Sham Sundary. Sir, can you hear me, I audible?

Yes, sir, we can hear you. Please continue.

First of all, I congratulate the management on the eve of this 45th AGM on its wonderful performance. I request the management to be cost effective by minimizing the expenditure. The corporate governance is good. The CSR activities are good. I request the management to consider the bonus issue. If not the rights issue, it's the right time to reward the shareholders, which is long pending due, sir. I hope the management will not let down the shareholders who stood behind it thick and thin. The shareholders' blessing is also very important, sir. Please kindly consider and the share price slightly falling, sir, down Q-on-Q, please kindly look into the matter, sir.

Sir, how are we going to withstand the tough competition in coming future? What are our future plans to enhance our business? I hope the management consider conducting the physical AGM in the coming future. I hope the management -- I thank the management for giving the opportunity, especially Manikantha. Thank you very much.

Thank you, sir. Now I'll request next shareholder Mr. Abhishek. Mr. Abhishek, kindly go ahead and ask your question.

First of all, I congratulate the management on the eve of Annual 45th Annual General Body Meeting. So trust all is well with you and your family in this challenging situation. Our company deserves much more respect than the current market cap after completing more than a decade of successful operations, profitability and becoming one of the strongest brand in the respective segment.

First of all, I would like to know what are the new plans and new innovations that our company is bringing and which are our new projects and which are the next states that we have been focusing on? And our company has built a very large extent of Infosys campus in Pocharam at Hyderabad. So what is the present scenario, sir? Are we expanding that? Or it is being fully functioning or it has not yet started because I have a property there. So I'm just interested in that particular business, whether the company has started and what is the upcoming phase that is being going on.

And as of now, how many employees have been deployed over there, I would like to know from you. And most of -- our company secretary is always reachable, so I don't have any further questions and kindly try to give an opportunity to the shareholders, the relatives who are really eligible for job opportunity in our company and nothing much to ask. I wish the company and the Board of Directors a great success and prosperity in the coming future. And thank you for giving this opportunity. I hope to see you in the upcoming hybrid AGM next year. Thank you very much.

Mr. Jaideep, please go ahead. Please go ahead with your question.

Yes. Very good evening, Chairman, MD and Board of Directors. Myself, Jaideep Bakshi, connecting from the city of Kolkata. First of all, I convey my thanks to our Company Secretary, Manikantha for giving the opportunity to express my view and presenting a detailed and informative annual report and to the entire secretary team for keeping in touch with us.

Sir, initial speeches -- both the initial speeches was very much informative, shared about our company's happens with facts and figures and congrats once again goes to everybody involved for the good performance and the dividend we have passed on to us. Sir, we are the leaders in providing the AI consultancy and technology service to unlock the value. What are the thoughts for future use of this growth strategy and our growth strategy, share our vision for building a global organization in this competitive market and what is our revenue growth prospects in the coming years.

Kindly share about the attrition rate and how are we nurturing the talent for our future success. And what is our thought process for the cybersecurity? And that's all from my side. I wish the company all the best. And once again, congrats for the CSR activities, which we have done, and thanks for the opportunity. Thank you, sir, and continue with the VC in future so that we can get easily connected.

Thank you, sir. Now I'll request the next shareholder, Mr. Atanu Saha, kindly go ahead and ask your question.

I, Atanu Saha, Limited, Chairman and Board of Directors and all of our shareholders of our company Secretary and our CFO, and all our shareholders present in this around globe. It's -- we are organizing its 45th Annual General Meeting, which is going on 23rd of June 2026. It's great for me that chance to speak. My previous shareholder raised their queries and their grievance. Thank you very much to every of our shareholders, they have beautiful questions.

So introductory presentation is really very good and very interesting. Sir, one thing, sir, what our future plan with artificial intelligence. Infosys is collaborating with 90% top 200 clients on our AI journey and more than 4,600 AI projects underway. As a shareholder of an AI world company, how long we have to wait for to get a profit from such a huge operation cost expenses?

As far as I'm coming to our company, is it sustainable, it is slowdown really, but its revenue, its growth is declining anyhow, and operating profits is before depreciation, interest and tax, it's depreciating. But sir, one thing that matter of Page #52, whereas that AI, our employees is 84%. And employee satisfaction score is 79%. My query is that why not it's more than 84%, it is the book is unlocked -- already unlock our book, which is in 2015, '16, whereas it is published through our company annual report, why it is written invoices and paying more.

Before our speech today is bad. But day after tomorrow, it's host, but day after tomorrow, it's sunshine. I wish you a good year ahead, good result and good dividend and good health to everybody also who are connecting with us, connecting with our -- also thanks to our all MSME. Thank you very much. I Atanu Saha, give permission to speak and thanks to our moderator and also our Company Secretary.

Now I'll request the next shareholder, Mr. Santosh Chopra.

[Foreign Language].

Now I'll request next shareholder, Gautam Nandi. Gautam Nandi, kindly go ahead and ask your question. I'll move to the next shareholder, Vasudha Dakwe.

Very good evening, respected Chairman, sir, Board of Directors and my fellow shareholders, myself Vasudha from Thane. The opening speech given by the Chairperson is also very informative and excellent. I will also thankful to our company secretary and his team for helping me a lot to join this platform very smoothly. Most of the question was asked by a previous shareholder. I will not repeat it again. Only one question I would like to ask. Why our attrition rate is so high and what steps we are taking to maintain it as in spite of all over the performance, our employee rate is -- why it is not less than other company. Thanking you. Wish you all the company for next coming financial year. Thank you very much, sir.

Thank you, Madam. I request the next shareholder, Kaushik Sahukar.

Respected chairman, esteemed Board members and fellow shareholders, good afternoon to all. It gives me immense pleasure to interact with you once again this year. I am deeply grateful to our CS, Mr. Manikantha for granting me the opportunity. I sincerely wish everyone good health and continued success. Coming to query, with rapid adoption of AI and generative AI across industries, current revenue is linked to AI-enabled service and solution. And gotten the management target contribution from AI-related business over next 3 to 5 years.

Suggestion, I would like to provide a humble suggestion imposed by expanding its AI-led managed services and subscription-based digital platform for small and medium enterprises globally. This could create a recurring revenue stream, deepen client relationship and reduce dependence on traditional project-based revenues.

On a lighter note, Infosys has automated so many business processes globally. Perhaps the next innovation could be an AI-powered AGM assistant that tells shareholders exactly when their turn to speak is approaching.

Before I conclude, Chairman sir, I have returned to you on several occasions seeking your guidance and support. I would be grateful if my request could get your consideration. If possible, kindly share the email ID of our GM, CFO or concerned official who may be able to evaluate my proposal or advise the concerned team to collect with me as our company is one of India's most respected company and is also known for its CSR activity.

I remain hopeful that some guidance or support may be extended to help me continue my professional journey. Thank you for your patience and consideration. I wish the company, its viewership employees and all the stakeholders continued success, good health and prosperity. Thank you very much. I look forward to meeting you next year again. Thank you, sir.

Thank you, Mr. Kaushik. Now I'll request the next shareholder, Satish Shah. Kindly go ahead and ask your question. I'll move to the next shareholder, Mr. Yusuf Yunus, kindly go ahead and ask your question.

Speaking from Mumbai. [Foreign Language]. You've given a INR 25 dividend. Very good, very excellent on the face value of this INR 5. Sir, very good. Sir, why it is so coming down, sir, what's the reason I would like to know. Sir, annual copy, our company secretary print very good. And I'm thankful to our company share department for calling us. Your number is coming on our phone. This shows how our company are caring for the shareholders.

Sir, there are very less company share, I would like you to arrange a factory in Bangalore, sir? Can you call me? Chairman sir, I would like to meet you, sir. I'm very proud of you, sir. You are one of the excellent Chairman, sir, and your work is world famous. For example, foreign institute, shares will go up, today market rate is down, not to worry. [Foreign Language]. We will have a good flower in hand and we will declare the next 5 years as 58 years. How are we celebrating. [Foreign Language] Flower just like a signing, but a smile will be set there. I'm smiling, sir. keep smiling, sir, not to worry. This is up and down, sir, nothing to worry. We are with you, sir. I will join with you, sir. My full family, atangala, all our shareholders, all people are giving good wishes, sir, and they pray for our company, sir.

Thank you, Mr. Now I'll request the next shareholder, Hariram Chaudhary.

Now I'm opening my video also. Chairman and my name is Hariram Chaudhary. I'm speaking from Sakush, Bombay. Mr. Mani, you are the father of Adarka System. Now Reliance is calling, not artificial intelligence, Reliance Intelligence. Intelligence can be called Infosys Intelligence and you are the father of Adarka, you can do that.

Now Mr. Chairman, I give the compliment to sari for giving the very informative presentation and also the Company Secretary, Manikantha ji for bringing out a voluminous report under the guidance of Chairman and Managing Director. Mr. Chairman, the secretary staff, including Rishita Puja also needs to be mentioned.

Now Mr. Chairman, about the CSR, we are doing very good CSR activities and my compliments to them. Let us know who is the Chairman of the CSR Committee and who are the members of the CSR Committee. Some very mild suggestions are there. Next meeting may be also online so that we from Bombay can attend that. And second suggestion is have a get together of speaker shareholders in Bombay. Many shareholders are from Bombay only. So please hold this get together in Bombay itself.

And now dedicated mobile phone may be in the secretary staff so that we can send fest from the time to time throughout the year, and we can maintain the personal relationship. And Mr. Chairman, about water harvesting we are doing, what about solar energy, that also we should do that, whether are we using this? And who is your model officer? Are we helping those who are going for shares and dividend have gone to IEPF. So who is the model officer, kind of let us know that.

And with that, I thank Chairman, Nilekani ji, Niraj and our best employees and ethical companies. Compliments to them. Thank you very much. My name is Hariram Chaudhary.

Thank you, Mr. Hariram. Now I request the next shareholder, Mr. Dileep Jain. Mr. Dileep, kindly go ahead and ask your question. Yes, sir. Please go ahead with your question.

[Foreign Language].

Thank you, Mr. Dileep. Now I'll request Mr. Shanik Mehta to kindly go ahead and ask your question.

Company Chairman, Mr. Nandan Nilekani, Board of Directors, MD and CEO, Salil Parekh, Company Secretary, Manikantha and his esteemed employees, my fellow brothers and sister shareholders. First of all, as a shareholder, myself, Shanik Mehta from Port City of Jamnagar Gujarat, 873, religion Jain. First of all, as a shareholder, I'm quite happy with the performance of the company for the March ending '26. No complaint as far as working is there, dividend policy is there, no problem. [Foreign Language].

We as a minority shareholder need your service as a company Chairman and Salil Parekh as our CEO and MD and Mr. Manikantha as our Company Secretary. So please don't think of retiring before 50th year, [Foreign Language] I sold about 10% of my holding of Infosys. I could not sleep for 2 nights because I had sold 10% of Infosys. Again, I repurchased those. After that, I'm able to sleep. So I love that much Infosys company. I convey my sincere thanks to all of you for giving me an opportunity to speak at the 45th AGM and wish you a happy year ahead March '27. Thank you, sir.

Thank you, Mr. Shanik. I'll move to the next shareholder,. I'll move to the next shareholder, Kamni Jain. Kamni Jain, kindly go ahead. I'll move to the next shareholder, Heera Nond Katwani.

Mr. Chairman, to all those who are listening to me, though he may be any nationalist. It is a great pleasure to join you. It is a great company, setting 45-year journey. But certainly, this market is not at a growth-oriented or increasing. some appreciation in the mind, Mr. Nandan. Please clarify because you are visionary, you know how the future will be at a difficult environment, how the company will cope with again, the new markets apart from the U.S.A. Is the company tapping rest of the world, particularly there's a trouble in Middle East, how do you tackle that? And how the Europe and other market companies are going to take to sustain the growth. So how the prosperity will remain? It is a billion-dollar question, not $1 million. Please narrate. Thank you and best wishes.

Thank you, Mr. Heera Nond. I'll request the next shareholder, Shweta Kamalia to kindly go ahead and ask your question. I'll move to the next shareholder, Prakashni Jeeshnoy. Kindly go ahead and ask your question. I'll move to the next shareholder, Pankaj Manjani. Pankaj, if you are on kindly go ahead and ask your question.

Thank you so much for providing me an opportunity to speak at this AGM. I have only 2 small questions. First one is, sir, in light of workforce rationalization measures undertaken by several companies in the IT sector due to automation and AI adoption, has the company assessed the potential impact of AI on its employee base? And does management foresee any material workforce reduction in the near to medium term? And the second question is, sir, given the rapid adoption of AI across the IT industry, what specific measures has the company taken to train and reskill its employees for AI-enabled roles? And how does management plan to equip the workforce to adapt to technological changes while maintaining long-term employee availability? Thank you.

Thank you, Mr. Pankaj. Now I'll request the next shareholder, Mohammad Iqbal. kindly go ahead and ask your question. I'll move to the next shareholder, Pratik Sharma. Mr. Pratik Sharma, kindly go ahead and ask your question. We can see you kindly unmute yourself and ask question. We'll move to the next shareholder, Sachin Singhal. Mr. Sachin, kindly go ahead and ask your question.

[Foreign Language]

Thank you, Mr. Sachin. Now I request the next shareholder Susan Modak. Susan Modak, kindly go ahead and ask your question. I'll request the next shareholder, Sam Patel. Madam, kindly go ahead and ask your question. Mrs. Patel, if you're on, kindly go ahead and ask your question. I'll move to the next shareholder Manjit Sandip. Manjit Sandip, kindly go ahead and ask your question. I'll move to the next shareholder. Palani Swamy. Mr. Palani, if you are on, kindly go ahead and ask your question. I'll move to the next shareholder Ashish Bansal. Mr. Ashish Bansal, kindly go ahead and ask your question. I'll move to the next shareholder, Suneet Bhatt. Suneet Bhatt, kindly go ahead and ask your question.

Good evening, respected Chairman, [Foreign Language] Mr. Nandan Nilekani sir, CEO and MD, Mr. Salil Parekh sir, distinguished members of the Board and fellow shareholders. Good evening to all. I'm Suneel Bhatt, speaking from SISI Karnataka, and I'm joined this meeting today as a proud retail shareholder of Infosys Limited.

I want to thank Mr. Manikantha sir for organizing this smooth, compliant and transparent virtual platform, allowing us to participate seamlessly. Looking to the annual report for the financial year 2025-'26, I want to express my sincere happiness and satisfaction with the company's performance. Despite a challenging global macroeconomic environment, Infosys has demonstrated remarkable resilience. The consistent revenue growth, strong deal pipelines and deep integration of advanced AI and digital capabilities show that our company is not just navigating the future, but leading it.

As an investor, I'm also deeply grateful to the Board for maintaining a robust capital allocation policy and declaring the final dividend. It reflects your continuous commitment to rewarding the faith of retail shareholders. Furthermore, your unwavering focus on strong corporate governance and high ESG standards makes us incredibly proud to be associated with this enterprise. I would like to state my full support for all the resolutions listed in today's Annual General Meeting notice, including the adoption of the audited financial statements and reappointments on the Board. I extend my heartiest congratulations to the entire leadership team and dedicated Infosions across the globe for an excellent year. You have my absolute confidence for the journey ahead. Thank you for giving me an opportunity to speak.

Thank you, Mr. Suneet. Now I'll request the next shareholder, Mahesh Kumar Bubna to kindly go ahead and ask the question. Mr. Mahesh Kumar Bubna, kindly go ahead and ask your question. I'll move to the next shareholder, Rudya Kumar, kindly go ahead and ask your question. I'll move to the next shareholder, Priya Sahukar. Priya Sahukar, kindly go ahead and ask your question. I'll move to the next shareholder, Fatima Rangwala. Fatima Rangwala, kindly go ahead and ask your question. I'll move to the last speaker registered shareholder, Yunus Rangwala, kindly go ahead and ask your question.

Thank you all, the speaker shareholders. With this, we conclude the question session from all the shareholders. Now I hand over back to the Chairman.

Thank you for all the questions. While we provide the answers to the questions shortly, I would request the team to display the questions received on the webcast and play videos which showcase the work done by Infosys during the last year.

[Presentation]

We will now begin the answers to the questions. In this round, we are answering the questions that were raised in the web chat. And after one round of web chat questions, we will then come back with a round of questions from the video and audio questions that were asked just now. I will start with my questions. I have a total of 5 questions.

First one is from shareholder Valpari Kishida Ramesh and others. What -- please let us know your plans for issuing bonus shares? Answer is Infosys has a rich history of rewarding shareholders with bonus shares, issuing multiple bonuses since listing. The last bonus was given in 2019. We do not have any announcements in this regard as of now.

Second question from Navnit Dandapani. What are the Board's strategic priorities for driving the next phase of growth? And how are we differentiating ourselves to maintain a competitive edge in the market? This question was also asked by Mr. Sudhir Shah, Mr. Jairaj and Mr. Puneet Singhal.

Our strategic priority remains to help our customers navigate the next and unlock their AI value. We believe we are well positioned to do that with our deep client relationships and our delivery capability. Our differentiators include the AI suite Topaz Fabric and our collaborations with AI disruptors to deliver both AI-first and AI augmented services. Our platforms are designed to ensure that AI solutions are relevant and tightly linked to business outcomes.

We are also expanding in sales and marketing in different geographies to expand our total addressable market. And where we find strategic fits, we are also doing mergers and acquisitions. And of course, we are doing a complete talent transformation to prepare our people for this new world of AI.

Question number three, what are the risks you foresee to the current expectations that integrators like Infosys are more relevant than before because enterprise AI implementation requires client-specific and accounting-specific execution, which AI platforms cannot do without integrators like Infosys. So that's a question from Srinivas Jayaraj.

The AI deployment gap, as we said earlier, both Salil and I spoke about it, creates large opportunities for us. We see an addressable IT spend of close to $300 billion by 2030. In any enterprise implementation, the context is paramount. Tools are accelerators and are great to amplify our potential. Our biggest strength and opportunity lies in combining the new world of agentic software with the traditional transaction system that companies have and make it AI useful and relevant to the clients' business.

Question #4 from Ramesh Gola. What is our road map on various items and of course, a request to visit the campus? Answer, many questions have already been answered in the ESG road map for the coming year. We'll continue to shape our ESG Vision 2030. Our employee count today is 328,000 as of March end, and all these details are in our annual report. Our CSR efforts, including Tech for Good, job creation and other efforts, including employee volunteering, health care interventions and women's empowerment.

Question number five, Ramesh Gola. CSR activities done by the company. Once again, the annual report and the foundation report and the interior annual report all have details about our CSR activities, which focus on digital skilling, health care and environmental sustainability. We have many important programs like Infosys Springboard for digital learning, Cogna care programs as well as lake rejuvenation and agroforestry projects supporting water conservation and climate resilience. All the information is there in great detail in our annual report.

With this, I now hand over to Salil to take his questions.

Thanks, Nandan. There are a few questions I have from the web chat part. And then as Nandan mentioned, we'll come later to the video and audio part. First question is from Shamala Raowijuka. What are the future plans of Infosys? Is there any new projects for the upcoming year?

So here, the big plans for us as we look ahead in the financial year '27 and even beyond is in the AI services area. We continue to see outside of that competitive intensity and also the productivity impact on the revenues. With all that put together, we have given a guidance of 1.5% to 3.5% growth for the full year when we gave the guidance in the April results. For the long term, we are extremely enthusiastic about the AI services opportunities.

What we shared earlier of the 6 big areas of AI services that we see, the building of the agents or the modernization or looking at data and others. And that's an opportunity of around INR 300 billion of addressable spend in the -- going into the year 2030. Second question is from Navinta Krishna Nandapati and also Nitya Mehta, similar question.

Given the rapid evolution of AI, particularly agentic AI capabilities, could the Board elaborate on the company's strategic road map for leveraging these technologies and how they expect to drive productivity, cost optimization and long-term competitive advantage. Additionally, how is the Board benchmarking our AI maturity and adoption against industry peers and what metrics are being used?

What we had shared in Q3 around the time just after Q3, the data for Q3 was AI services is coming up with 5.5% of our revenue at that stage. Then we look at some other metrics, 90% of our employees are AI aware. We also mentioned that of the 200 largest clients, again, 90% are where we do work, which is related to AI using Topaz, using Fabric. We're currently working on over 4,800 AI projects, and we built over 600 agents.

We are also scaling up a team, which is of forward deployed engineers, which team then works very closely with clients on making sure that AI is deployed into those client activities. We also have very good partnerships with foundation model companies, with tool companies and with compute companies across the entire AI ecosystem. And all of this then gets reflected in about 16 leadership rankings that we have within the AI ranking approach of all the analysts.

Next question is from Srinivasa Raokhilaro. Dear, sir, many analysts say that Indian IT companies are just service companies that do not cater for R&D. Indian IT companies just distribute cash and dividend through buyback and Indian IT companies are not investing in meaningful research. What do you say about Infosys in this regard? What is the future vision of the Infosys management, where Infosys may lead in the next 5 or 10 years?

Here, we have a very structured approach in terms of innovation where we have a center for emerging technology and solutions. A lot of the new technologies of AI, in fact, previously machine learning, digital, cloud and today, also new technologies of quantum are being incubated in this group, and that's where we see the earliest use.

As a company, what we do is we take the new technologies that are coming and we build the capabilities in skilling our people and then deploy them on to large clients so that deployment becomes easier for our clients to use. We have also created something called the Infosys Living Labs, which is global innovation hubs with clients and partners and sometimes even start-ups and academic institutions where we can jointly develop some of the technologies.

For example, on AI, we have a joint work with a leading university in the U.K., a leading university in the U.S., where we are doing big work on AI innovation. Then we are doing work, which is ensuring that what we distribute through a dividend or buyback is based on the capital return or capital allocation policy of the company that is being described.

Next question is from Sudhir Dulerajshah. What is the strategy of the company for the development in Gujarat. So what we have done across India is we've had many innovation hubs, nearshore centers, digital design studios and partnerships also with AI and GCCs in different cities in which we are operating and our clients are operating. We've also built a hybrid model where people can work flexibly from different locations even today where they come in for some of the days and are working flexibly from their home locations for the rest of the time.

With this strategy, we've set up location -- centers in cities like Ahmedabad and making sure that, that gives a big support within Gujarat and also in many other places, for example, in Hubballi, for example, in Visakhapatnam, for example, in Noida. All of those areas are being developed across the company.

Next question is from Soham Ketan Kanandikar. Over the next 3 to 5 years, as Gen AI-driven productivity improves, software development efficiency, how does management expect economic value created by these productivity gains to be distributed among Infosys, its employees and its clients? So simply, do you expect AI to be margin accretive, margin neutral or margin dilutive?

So here, what we are seeing is there will be a lot of productivity improvements that are realized through AI, which will enable our clients to get some savings, which they are typically investing in additional or new IT spends in different ways, which is expanding the addressable market that we see. We've also had our own internal project for margin attention and expansion, where we've seen the revenue per employee is increasing over the last 3 years. Our revenues, therefore, have grown at a faster pace than our headcount.

This helped us to improve our margin if you look at the previous financial year '25 by 50 basis points. And in the financial year '26, even with all the different macro negative environments, we were seeing that we were able to maintain our margin even as we put some more investments into sales and marketing. And our guidance for this coming year -- financial year 2027 for margin is 20% to 22%. In our medium term, with all of this activity and what we see in productivity benefits, our endeavor is to improve margins from the current levels as we go ahead. Those were the questions that I had. I will now request Jayesh to take his questions.

Thank you, Salil. The first question is from Mr. Muruk. When can we expect Infosys to grow double-digit growth? Can we expect to double the shareholder value by 50th AGM?

As you know, we delivered a strong performance in financial year 2026 despite a challenging environment. We had a growth of 3.1% for the year in constant currency terms despite lower third-party revenues and higher offshoring, which are headwinds to our revenue. On an organic basis, we have grown faster than our peers for over 7 years now.

On other parameters, we had a very strong large deal wins at $15 billion with 55% net new. We generated $3.7 billion of free cash flows and all of that with a stable operating margin despite investing in S&M and AI and talent-related investments. The overall demand environment continues to be soft, and we see cautious behavior by clients due to macro concerns with growth also impacted due to AI inflation. As the clients shift from siloed AI adoption to enterprise-wide AI adoption in the medium to long term, we expect them to increase the spend across 6 new AI value pools, which should lead to expansion in addressable markets by $300 billion to $400 billion.

Our guidance for the current year remains at a revenue guidance of 1.5% to 3.5%, excluding the Optimum acquisition that we completed during this quarter and at an operating margin of 20% to 22%. We do not give guidance for the future years.

The next question is from [ Aakash Sukheja ]. There are multiple questions: How are we going to utilize our excess cash on our balance sheet for future growth? Can we expect acquisition of major AI companies, likes of which we saw at HCL investing in Sarvam AI? Second question is, can we please start reporting AI revenue separately? This will help investors in this fearful market where every news flow causes panic. And the third question is, how would you measure -- how would you reassure small shareholders who are scared now looking at the market performance?

The utilization of excess cash, we have a very structured capital allocation policy as per which, effective financial year '25, the company expects to continue its policy of returning approximately 85% of free cash flow cumulatively over a 5-year period through a combination of semiannual dividends and our share buybacks or special dividends subject to applicable laws and requisite approvals, if any. Under this policy, the company expects to progressively increase dividend per share.

We have a very disciplined approach to our M&A and focus on tuck-in acquisitions, which will help us bridge white spaces in terms of capabilities or segments in which we operate as well as accelerate growth through synergies. This systematic approach and M&A has worked well for us over the years. We have a strong balance sheet and a clear cash allocation towards M&A, which puts us in a very advantageous position when it comes to making quick decisions on the acquisitions.

On reporting on AI revenue separately, we disclosed the AI revenue in Q3 at 5.5% of our revenues, approximately $1 billion annualized, and growing faster than our company average.

On how would you reassure shareholders? We will not be able to comment on share price at this point in time. Our aim is to focus on our business and create value for our clients and therefore, our shareholders. We have the right ingredients and reflect strong delivery capabilities, deep client capabilities, multiple AI recognitions and trained employee base to deliver on the same.

The next question is from [ Chiradeep Acharya ]. Overall stock returns have been very poor for shareholders over the last 5 years despite good dividend. There also has been no bonus issue in the last 8 years. Further, last buyback was at a time when individual tax returns on buybacks were very unfavorable. How does Infosys propose to enhance shareholders' value in the next 5 years, especially in an environment where IT services are being written off due to AI?

As I mentioned earlier, we have a well-defined capital allocation policy, which gives predictable returns to shareholders for the current block of 5 years from FY '25 to FY '29. The policy is to return 85% of free cash flows through a combination of semiannual dividend or share buyback or special dividends. The company also expects to progressively increase annual dividend per share. The company has also announced multiple bonus issues. However, there is no announcement in this regard at this point in time. The currently concluded share buyback of INR 18,000 crores resulted in EPS accretion to the shareholders.

On the second part of the question, we believe that there are new 6 areas of the AI first services opportunity that will be around $300 billion to $400 billion of opportunities by 2030. We are investing in various areas, including sales and marketing, deepening our AI capabilities, growing our partnership ecosystem, et cetera, with aim to grow ahead of the market in the long term and execute on our strategy.

The last question is from [ Ms. Mamta Rajesh Shah ], why cash flow, both operating and free, have gone down as compared to the last year? Our operating and free cash flows are lower by approximately INR 1,400 crores in FY '26, primarily due to the higher income tax refunds in FY '25. These refunds are on account of orders received under Sections 250 and 254 Income Tax Act for certain assessment years relating to years prior to '25.

With that, I will pass it on to Manikantha. Thank you.

Thank you, Jayesh. The first question by [ Valpady Krishnadas Bhat Ramesh ], when are we starting physical AGM?

The response: Ministry of Corporate Affairs and SEBI have allowed the companies to hold the AGM through video conference without the physical presence of members at a common venue. We will evaluate and keep the shareholders informed on the physical AGM, if any, in the future.

The next question by shareholder [S. Mangayarkarasi ]. The question is, how to buy Infosys' shares in the USA market?

The response: Infosys ADRs are listed in NYSE. Members who intend to purchase these ADRs can contact the authorized bankers and brokers or the depositories following the due process for foreign investments.

With that, I hand it back to the Chairman.

Thank you, Mani. And now we will come to the second round of questions. These are questions that were asked in the video conference, and we'll do it in the same order. I'll start with my questions. I have three questions. First question, [ Mr. Vipul ]. Sir, can you elaborate on your statement that there are no gaps in the opportunities available? The only limitation is execution risk.

Yes. What I said was that the opportunities are very large because of the many new things that are possible with AI. So we do see a lot of work coming down in the coming years. Execution risk is our ability to reorient our service offerings to AI to offer AI-first services and AI-augmented services, to get our sales team and delivery team to be aligned with that, to do the talent transformation, to look at new models of pricing, including outcome-based pricing, and many other things that we have to do, which we have -- which are required to achieve the goal of getting the best possible business from the new AI work. So that's what we meant by execution risk.

Second question is, how can CSR proposals and suggestions be sent to the company? This is from [ Dilip ].

CSR proposals can be sent at [email protected], or submitted through the CSR grant application available on the Infosys Foundation portal. All proposals are evaluated by the foundation based on alignment with focus areas and impact potential.

Last question is, can the company consider increasing the work it is doing to adjust the water issues, including in Jamnagar? This is from [ Mr. Shreyak Mehta ]. As a responsible corporate citizen, our Water Stewardship program extends beyond our operational efficiency to create a positive impact in the communities where we operate. We have taken up 11 large lake rejuvenation projects, creating additional capacity of 4.2 billion liters, making the total capacity of 10-plus billion liters for these lakes. These lake rejuvenation projects enhances water table, improving water access to communities. We'll continue to do this, but this would happen in areas where we have operations. So I want to keep that in mind.

So with that, I hand over to Salil for his questions.

Thanks, Nandan. I have a few questions. I'll read them. The first from [ Mr. Gaurav Vibhu ]. Last year, there was robust performance, but the industry going through issues. We are now facing the low growth. When will we go back to high-growth? Despite ForEx depreciating, we do not see the increase in margin, disruptions in geopolitical issues, which industry and geography will grow? And which industry will be a laggard? Do you see CapEx and OpEx spending change in public? New growth areas like AI, quantum computing. Is CapEx planned for these areas? Will we have a new dividend policy because of this?

So the last few years, we have seen that a lot of the changes we have come with the changes in the macro environment and the interest rates, which have also led to some of the changes where the discretionary spending was affected with our clients. Now we had a strong performance in the financial year 2026, where we crossed $20 billion in revenue overall and grew at 3.1% on a constant currency basis. One of the things we also mentioned in one of the answers, which was given by Jayesh, that over the last 7 years, we are, on an organic basis, the fastest growing amongst our peers.

On FY '26, the communications manufacturing verticals and the Europe geography grew more than the company average significantly. In FS, Financial Services, and the grouping that we have, which is Services, Utilities, Energy, Resources, we grew above the company average in constant currency terms. In terms of the outlook, we expect there will be an acceleration of growth in Financial Services. In Energy, Utility and Resources and Services grouping, those verticals will see that acceleration in the financial year 2027.

Our margins, we have had them remain stable despite several changes in the past 3 years. There are some constant currency, which becomes sometimes negative. There was, of course, the situations where we've seen changes in the pyramid, and we've also had some acquisitions, which overall reduced the weighted margin, which comes into effect as the overall operating margin of the company.

In terms of our capital allocation policy, it's well defined, and we will keep that policy as it has been defined over the next 5 years. So 3 more years are remaining in that grouping. And we have clearly 85%, which we return to shareholders in different forms, and the remaining 15% is available as we choose to do some strategic acquisitions to improve parts of our business. We are not -- there is no change on that capital allocation policy.

The next question is from [ Santosh Kumar ]. What is the company's 3 priorities to reach $30 billion on revenue? A similar question was also asked by [ Mr. Bharat ] and [ Ms. Smita Shah ], [ Mr. Vipul ] and [ Mr. Bharat Raj ].

As AI adoption is growing, we will see that becoming more and more dominant into the revenue of our future. The current pace of change of that AI technology is also fast, and we look ahead, we see opportunities which are related to growth opportunities related to productivity improvements. And our objective is to make sure we leverage those growth opportunities and grow at a good pace. We also have good AI partnerships and a strong employee reskilling, which helps us to become part of the AI journey of our clients.

In terms of AI services, we have sort of outlined 6 new areas, and those areas where we see the most impact. One of the examples of that 6 is what we see, for example, in modernizing a lot of the technology estate of our clients.

The next question is from [ Mr. Reddappa ]. And a similar question was from [ Mr. Jaideep Bakshi ] and [ Mrs. Vasudha ]. Can management elaborate on the steps taken regarding talent retention?

So first on attrition, last year, we were at 12.6%, which was in terms of overall numbers and a very good outcome for the company. In the previous year, it was 14.1%. And the year before that, it was again 12.6%. For us, nurturing the talent is a critical point for future and continued success. Our employee value proposition is focused on providing employees with career, with rewards, with recognition, learning and development and wellness. So our total reward approach is sort of benchmarked into the competitive industry, and we have long established paths for employees for the upskilling, for the reskilling and for the career growth. We believe with all these measures and also the way we are ensuring that there's a flexible work environment for our employees, that helps us to make sure that our attrition numbers are low as we had in the previous year. and we plan to have those sort of measures on the future.

Next question is from [ Reddappa ]. What is the company doing to increase its deal conversion?

So in the deal conversion last year, we had approximately $15 billion of large deals, of which 55% were net new, and that was up by 24% from the previous year. So in addition to large deals, we have a portfolio of clients where many are medium and many are small deals as well. And even with all the changes in the macroeconomic headwinds, we see a distinct uptick in the IT spend, especially on AI services and on the modernization opportunities. Those are fairly large into our pipeline. And there, many of our clients are moving well beyond AI sort of pilot or small projects to really whole enterprise-wide AI project deployment. What we see there is that people are deploying large projects, IT projects, but they're also very cost efficient and making sure they're deployed wisely. Here, we also see a lot of change on the GCCs, where there's a lot of activity on AI-first GCCs where we have a good impact with our clients.

The next question on the potential -- from [ Mr. Pankaj Manjani ]. Potential impact of AI on the workforce and what are the measures for the reskilling the workforce and equip the workforce in the new environment?

So here, what we are seeing is that as we have more and more changes of AI coming in, we will also have agents that will be working with what we do as humans. And the overall work we expect will expand. So what we did last year, for example, with recruiting 20,000 new college graduates, we have a similar plan for this financial year, to increase the number of people that we will bring in. And that's how we will focus on different types of work using agents, but also using the humans.

AI adoption is still in a very early stage in many of our clients and industries. And so we will see a lot of expertise being developed, both human and agent base, which are related to a deep understanding of the domain, and that's where we will see the benefit of the experience we have.

One of the things we have done in terms of reskilling is making sure that we have employees who are AI aware, who are AI builders and who are AI masters. And then we're collaborating with our partners who are foundation model companies and compute companies and tools companies to make sure that all of that latest learning is built into what our people know into the market.

That's all the questions I had. And now I request Jayesh for his part.

Thank you, Salil. I have three questions. But before I get to the questions, I would like to thank the shareholders for the deep appreciation on the quality of annual report, CSR activities and the services provided by Manikantha and Secretarial team.

Coming to the questions. First question is from [ Mr. Vipul ]. Whether the guidance is necessary according to being -- giving guidance should be -- should it be scrapped?

Our guidance reduces, in our mind, asymmetry of information between management and stakeholders. It is a global best practice that the company has adopted for years for the benefit of shareholders to provide an anchor for the market expectation and to give a view to shareholders on current plans and likely performance.

The second question is from [ Om Prakash Kejriwal ]. What is the plan to invest in our future and our skill development as our share price has gone down because we are not investing in future?

The company has taken multiple initiatives to stay ahead of competition with respect to the ability to leverage AI for better outcomes internally and for clients. We have invested in developing an industry-leading comprehensive solution, Infosys Topaz Fabric. We've also invested in building one of the best and most competitive partnership across the AI ecosystem. We are making significant investments in continuous learning and skilling to enable our workforce to stay ahead of AI-led transformation. Overall, we have a very comprehensive approach to gain market share in this AI opportunity.

The third and the last question is, why is company share going down after buyback?

We will not be able to comment on the share price movement. However, the recently concluded tender offer buyback of INR 18,000 crores has resulted in EPS accretion for our shareholders and increasing return on equity while returning cash as per our capital allocation policy.

With that, I'll turn it over to Manikantha. Thank you.

Thank you, Jayesh. There was one question in this round. The question was from [ Hariram Choudhary] . The details of nodal officers for the purpose of IEPF were asked. And also, what are the initiatives taken by the company with respect to IEPF?

With respect to the nodal officer, the Board has designated me as a nodal officer for the purpose of IEPF. Therefore, the shareholders who have any claims for claiming their shares, which have gone to IEPF, can write to us. And there are detailed steps, which as mentioned on our website, of how to claim the shares. Further, the shareholders can write to [email protected], and we will help them out how to claim the shares.

And with respect to the initiatives taken by the company, the company sends out periodical intimations to the shareholders to encash their unclaimed dividend and update their bank account details either with the RTA or with the depository participants.

The company also publishes unclaimed dividend and corresponding shares information on the website of the company. So therefore, the shareholders can look at these details and get to know if their shares have gone to IEPF authority. If it is so, it can reach out to the company for helping to claim those shares.

In addition, the company also has an initiative to receive the information from depository on updating bank details by a shareholder for processing the dividend directly without any specific request from the shareholder. So these are some of the initiatives which is taken by the company.

Those were the questions. And with that, I will hand it back to the Chairman.

Thank you, Mani. Members may note that e-voting on the NSDL platform will continue to be available for the next 30 minutes. Therefore, I request members who have not cast votes yet to do so within the next 30 minutes.

The Board of Directors has appointed B. Hemanth, Practicing Company Secretary, as a scrutinizer to supervise the voting process. Further, I hereby authorize Manikantha, the Company Secretary, to declare the results of the voting and place the results on the website of the company at the earliest. The resolutions as set forth in the notice shall be deemed to be passed today subject to the receipt of the requisite number of votes.

We had 326 members participating in today's 45th Annual General Meeting. Thank you for attending the meeting. I hereby declare the proceedings of Infosys Limited's 45th Annual General Meeting closed. Thank you, and see you next year.

Ladies and gentlemen, greetings, and welcome to Infosys Limited Q4 FY '26 Earnings Conference Call. [Operator Instructions] Please note that this conference is being recorded.

I now hand the conference over to Mr. Sandeep Mahindroo. Thank you, and over to you, Mr. Mahindroo.

Thanks, everyone. Welcome to this earnings call to discuss Infosys Q4 FY '26 financial results. Joining us on this call is CEO and MD, Mr. Salil Parekh; CFO, Mr. Jayesh Sanghrajka, along with other members of the leadership team.

We'll start the call with some remarks on the performance of the company, subsequent to which we'll open up the call for questions. Please note that anything we say that refers to our future outlook is a forward-looking statement that must be read in conjunction with the risks that the company faces. A complete statement and explanation of these risks is available in our filings with the SEC, which can be found on www.sec.gov.

I'd now like to pass on the call to Salil.

Thanks, Sandeep. Good afternoon, good evening, good morning to everyone. Thank you for joining in. We delivered a strong performance in the financial year 2026. We had a growth of 3.1% for the full year in constant currency terms. Our Q4 revenue growth was 4.1% year-on-year in constant currency terms.

We had strong growth in financial services, in the communications industry and manufacturing industry and for the Europe geography for the full year. Large deals were strong. For the full year, we had $14.9 billion of large deals. This is a growth of 24% over the prior year. And for Q4, we were at $3.2 billion, a strong showing for the quarter. We shared our AI strategy during our AI Investor Day a few weeks ago. We see a large addressable market for AI services across 6 areas AI strategy and engineering, data, process, legacy modernization, physical AI and trust.

With our Topaz Fabric platform for AI, our COBOL platform for cloud, we have differentiated capabilities to serve our clients across the 6 areas of AI. Some examples of the work we are doing for a consumer products retail company, Ralph Lauren, we helped build a conversational and personalized AI tool that led to converting customer interest into a shopping experience. This resulted in an increase in the revenue by 12% and customer engagement by 50%.

For a large transport company, Hertz, we helped with a legacy migration to bring 3 million lines of COBOL code to a modern micro services environment using AI foundation models. The cost was 60% lower. The time line was 60% quicker than how they would have done it without AI. For a large energy company, BP, we deployed 50 AI agent initiatives across trading, supply chain, sustainability and core operations to transform the software development, knowledge automation, legacy modernization and digital decision support. This resulted in 95% payment accuracy, 50% faster contract validation and 18% improvement in IT operations efficiency.

We have strategic collaborations with emerging foundation model companies such as Anthropic and OpenAI, which help us support our clients' transformation for software development, legacy modernization and agent building. We also have established strategic AI collaborations with Google Gemini, NVIDIA, Microsoft, AWS, Google Cloud and Intel, among others. We've deployed over 30,000 developers on GitHub Copilot.

As we look ahead to financial year 2027, we see large opportunities in AI services, continued competitive intensity and AI productivity impact. With a clear AI strategic road map and real-world toolkit of Topaz Fabric, we are well positioned to support our clients' transformation, technology and operations objectives. Our revenue growth guidance for financial year '27 is 1.5% to 3.5% year-on-year in constant currency terms. We expect acceleration in growth in Financial Services and the Energy, Utilities, Resources, Services vertical from financial year '26 to '27. We expect H1 to be stronger than H2, consistent with our normal seasonality. Our operating margin guidance for financial year '27 is 20% to 22%.

With that, let me hand it over to Jayesh for his update.

Thank you, Salil. Good morning, good evening, everyone, and thank you for joining the call today. Financial year '26 performance demonstrates our ability to maintain financial discipline and operational excellence in a challenging and evolving business environment. Client spending is guarded with greater focus on cost optimization engagement as against growth-led transformation programs. We are seeing increasing momentum in AI-driven initiatives, particularly around productivity, automation and platform-led modernization initiatives.

Let me start with the key highlights for the year and the quarter. FY '26 revenues crossed $20 billion and grew 3.1% in constant currency terms within the upgraded guidance band given in January. This was after lower third-party costs, which was down by 1% as a percentage of revenue and 0.7% reduction in on-site mix. Acquisitions contributed about 70 bps on full year growth. For FY '26, Communication, Manufacturing vertical and Europe geography grew more than double the company average, led by ramp-up of the large deal wins. Additionally, FS and EURS grew above the company average in constant currency terms. Volumes for the year were flattish. Growth was led by increase in realization, thanks to Project Maximus.

Adjusted operating margin was stable at 21%. Gains from currency and Maximus were reinvested in talent, AI investment and sales and marketing. Q4 revenues grew by 4.1% year-on-year. Sequentially, revenues declined 1.3% in constant currency due to seasonality and slower decision-making in the month of March. Growth in Q4 was broad-based across major geographies. Communications, EURS and LS verticals grew well above the company average on a year-on-year basis in constant currency terms. Q4 operating margin stood at 20.9%, down 0.3% sequentially adjusted for the labor code impact in Q3.

On-site mix further reduced to 22.8% from 23.1% in Q3. Utilization, excluding trainees, was 83% in Q4 and 84.4% in FY '26. Utilization, including trainees, was at 81.1% for FY '26, reflecting the investment made towards creating future capacity. Strong focus on collections aided by technology interventions helped us reduce DSO, including unbilled net of unearned to [ 78 ], which is the slowest in 7 years -- which is the lowest in 7 years.

Reported EPS in INR terms grew 23.8% Y-o-Y in Q4 and 11% in FY '26. EPS adjusted for income tax orders and the labor code grew double digit for the year at 13.9% in Q4 and 12.1% for the full year in INR terms. Free cash flow adjusted for the labor codes and income tax refund stood at $3.5 billion for FY and $882 million for Q4. Adjusted free cash as a percentage of net profit continued to be well above 100% and 106% for FY '26 and 111% for Q4. We had a strong large deal wins in financial year with a TCV of $15 billion with 55% net new. Large deal pipeline continues to remain strong. Our $50 million-plus clients increased by 3 and $100 million-plus clients also increased by 3, $400 million by 2 in financial year last year.

Headcount at the end of the year was over 328,000. Voluntary attrition reduced by 1.5% to 12.6% for the year, reflecting continued softness in our interventions toward talent retention. We onboarded more than 20,000 freshers in FY '26 and expect to hire a similar number in FY '27. We will continue to calibrate the overall requirement depending on growth expectations and attrition trends. Operating margins for Q4 declined by 0.3% to 20.9% sequentially. Major components of the changes are as below. Headwinds of 50 basis points impact from past acquisition on account of additional amortization of intangibles, 30 basis points for normalization of last quarter's one-off gain, 20 basis points from compensation-related costs, offset by lower variable pay.

This is partially offset by tailwinds of 40 basis points for currency and 30 basis points for Maximus comprising of value-based selling, lean and automation and critical portfolio. Q4 yield on cash and investments balance was at 6.2% and 6.7% for the year. ROE stood at 31.6%. Consolidated cash and investments were at $4.5 billion after returning over $4 billion to shareholders in FY '26, reflecting our strong cash generation. We signed 19 large deals during the quarter with TCV of $3.2 billion. This includes 5 each in financial services and manufacturing, 4 in retail, 2 each in Life Science and Communication and 1 in EURS.

Region-wise, we signed 11 deals in Europe, 5 in America and 3 in the Rest of the World. In FY '26, we signed 96 large deals with TCV of $15 billion, 55% net new. This includes 3 mega deals for the year. Tax rate for the quarter is lower due to reversal of prior year tax provisions as a result of favorable tax orders. We expect effective tax rates for the financial year '27 to be in the range of 29% to 30%.

In line with our capital allocation policy, Board has proposed a final dividend of INR 25 per share, which will result in a total dividend of INR 48 per share, an increase of 11.6% over last year once the final dividend is approved by the shareholders. Coming to verticals, Financial Services for FY '26 grew above company average at 4.4%, led by ramp-ups of large deal wins and continued momentum in AI-led transformation, legacy modernization and vendor consolidation. Overall market sentiment remains positive, resulting in continued consumer spending across U.S. banking, capital markets and Europe.

CY '26 budgets are expected to grow in U.S. We signed a large GCC deal for a regional bank in the U.S. an industry first and a large AI-first GCC deal. We are strategic AI partner for 18 out of the top 20 clients in this vertical, significant large deal closures and a new account opening in FY '26, along with a strong large deal pipeline will drive growth acceleration in FY '27.

Clients in manufacturing remain cautious amidst softer demand, particularly in automotive and parts of Europe. This is continued -- there is continued uncertainty on account of tariffs and ongoing Middle East conflict, which is resulting into delayed decision-making in pockets. Discretionary spending remains constrained, while clients prioritizing cost optimization and operational resilience. Large deal pipeline comprises of infra outsourcing, AMS, S/4HANA rollouts, et cetera. Near term and FY '27 growth will be impacted due to low revenue from one large client.

Across EURS segment, demand environment remains constructive, supported by a strong large deal pipeline. Clients continue to prioritize cost reduction and operational efficiency, which is driving vendor consolidation. In Energy, we see increased outsourcing leading to healthy deal momentum. Utilities demand is structurally higher, driven by grid constraints, renewable integrations and acceleration electricity needs for data centers. 80% of the large deal TCV of FY '26 was net new, which will help growth and acceleration in FY '27.

In retail segment, clients are operating in continued uncertainty from supply chain disruptions, geopolitical conflict and shifting trade policy. Consumer demand remains muted across the sector and budgets are tightly controlled with discretionary spends under pressure. Clients expect savings from AI-led productivity to do more with the similar budget. We will see higher demand for AI-assisted legacy modernization. Topaz Fabric and AI Next platforms are helping clients in ideation from concept to deployable stage with the right cartridge for privacy, [ ethics ] and control.

In Communications sector, growth for FY '26 was led by large deal ramp-ups. Overall environment remains cautious amid macro uncertainty and margin pressures for clients. Budgets are flat to negative, which is impacting discretionary spend. Nondiscretionary spend are selective and increasingly AI-led. There is a shift from generative to agentic AI with clients consolidating IT and BPM cuts. We are strong -- we see a strong uptick in AI deals in areas like IT operations, software replacement and mainframe migration.

As we enter FY '27, we continue to see a measured and selective approach to enterprise budgets amid macro and geopolitical uncertainties, higher interest rates, rapid technology shifts and high competitive intensity. We expect FY '27 growth to be 1.5% to 3.5% in constant currency terms. The FY '27 guidance includes contribution from Stratus, which we closed earlier this week, but excludes Versent JV and Optimum Healthcare acquisitions that are yet to be closed.

Reduction of 0.75% to 1% due to a lower revenue from one of our large European manufacturing clients. This was due to reduced client spend on account of challenging macro environment, along with our conscious decision to not pursue a certain deal that were not aligned to our return expectations. Further reduction in on-site mix by 0.75% to 1%. We expect third-party costs for FY '27 to remain at similar levels as FY '26. Our operating margin guidance for the year is 20% to 22%. This assumes headwinds from wage hikes, productivity pass-throughs and AI investments offset by initiatives under Project Maximus. The impact of Optimum Healthcare strategy and Versent on operating margin will be approximately 0.7% on a full year annualized basis post closure.

With that, we can open up for the questions.

[Operator Instructions] First question is from the line of Yogesh Aggarwal from HSBC Securities.

Just a couple of questions. Firstly, Salil, can you talk about the push-pulls for the guidance like at the lower end, at the upper end, what are you assuming?

And secondly, you guys had a very successful Project Maximus, the quality of business, the revenues has also improved. But the entire INR depreciation, which is very significant, has not impacted the margin outlook. So I was just curious which are the areas where all the INR depreciation has been invested? And if you can talk a little bit about that.

Yogesh, this is Jayesh here. At the lower end of the guidance, we have assumed higher deterioration in the environment. And at the upper end, we have assumed improved environment. Like similar to what we've done in the last year as well. In terms of margin walk, I did give you a broad margin walk. But largely, we have invested all the benefit that we got from rupee as well as from Maximus back into the business, whether it is sales and marketing cost, which has gone up by 40 basis points on a full year basis, the AI talent and the AI partnerships, et cetera, that we have. So I think all of that has been absorbed in the margin in the financial year.

And just a quick follow-up. You mentioned productivity pass-through impacted margins. I was just wondering why should that be the case if there was productivity improvement?

So Yogesh, market is competitive, right? As I said, the competitive intensity in the market has gone up and the productivity will get passed back to the client largely.

Next question is from the line of Ankur Rudra from JPMorgan.

I noticed you've chosen to guide in a 200 basis point band versus a slightly wider band in the last couple of years. Is your visibility better this year versus the last few years?

And furthermore, if you can dig a bit more into the guidance as a follow-up to the previous question. You're guiding for a 2.25% organic at the midpoint approximately, which appears to be a bit of a slowdown versus the 2.5% or 2.4% organic in fiscal '26. Can you maybe talk about what are the puts and takes of the outlook? And if you can especially elaborate on if the slowdown is because of a, demand environment; b, structural AI deflation; or c, the impact from that one large account, which is ramping down this year?

Yes. So Yogesh, if you -- sorry, Ankur, if you look at the guidance, last year, we gave a 3-point guidance because the whole environment changed pretty much very close to the time when we were giving guidance, right? And we had no -- we had very little clarity in terms of how that environment changed because of -- on the back of tariff, tariff changes is going to impact the client behavior, et cetera.

Where we stand today, I think there's a better clarity in terms of what's happened. The environment has been like this for last few quarters. And we know how clients are behaving at this point -- at least at this point in time. Of course, if things change, the client behavior will change. That's given always. But at this point in time, from a comparative perspective, we have a better clarity and better handle versus the last year.

Ankur, on the -- like the construction of the guidance, what we are seeing positive where the changes are. Jayesh mentioned many of those points, I'll elaborate. We are seeing the growth on AI services. We are seeing very good traction on that. We are seeing -- we've started a program where we are working with large companies with a smaller footprint that Infosys has, we are expanding that quite nicely. Then we saw the large deals, the net new was 55%. So that will contribute for the next -- for this financial year in a significant way.

And then on the other hand, there is the productivity benefits that are coming through which our clients are looking for with AI on the existing portfolios. Then Jayesh shared a couple of situations with manufacturing, Europe, with on-site mix, sort of some technical factors. So those -- if I sort of add and subtract is where we came on that guidance.

The environment, I find is good. Our large deal pipeline is good. The way we had done it on that AI at Investor Day, we had sort of said, look, there's a growth side with what will be the AI. We have a couple of other growth drivers. And then there's the compression side, and that's the balance that we are seeing. In the past year, with 3.1%. And if you adjust for the one-timers, the onetime from the prior year, we had a growth rate, which was more than the compression we were seeing. And this coming year, the guidance that we have started with also sees that. And then we'll see, as Jayesh said, on the environment, how it changes, improving or not improving and then see how the year goes after that.

If I could -- just a quick follow-up. What would need to happen for you to see an acceleration at the midpoint on an organic basis?

These are things which are always sort of more difficult to estimate, as you know well, Ankur. However, the view emerging is that the situation in the Middle East may find some sort of a good out resolution. Then the underlying economic trends are pretty good in the markets where we are large. So that could give sort of rise to a more stable macro environment. Our AI traction and partnerships are good.

So if those things, the first and the second accelerate, then we will see some good outcomes. But it's more of going in -- we see the environment today. It's not -- we've not seen some big change to give us a view that we have to do a 3-point range and so on at this stage. And overall, we see growth, which is more than compression.

Next question is from the line of Bryan Bergin from TD Cowen.

I wanted to ask on the AI productivity that you're seeing here. So with the AI model advances happening as fast as they are, has the amount of productivity during compression that you're seeing changed in the current contracts relative to what you may have been seeing, say, 1 or 2 quarters ago?

And can you just mention maybe the mix of the business that is directly exposed to the productivity pass-throughs versus maybe the mix of the business that is more insulated?

So on the first one, we have not -- with the models and the technology is moving with great innovation. We have not seen in 1 or 2 quarters the change that you referenced. So what we are seeing is the competitive intensity is pretty high. So every now and then, we see a competitor doing something which looks outside the range of what we think the models can do today. So that sort of thing we do see. But not just the tech in the last 2 quarters, meaning over the last 2 years, of course, there have been changes.

In the terms of expose, I think we have not like shared that data, but I think we have shared very clearly what our service line data is, and you can make some estimates with that, I think.

Okay. And then my follow-up is on kind of how you're thinking about the overall business and headcount, hiring intentions for fiscal '27, I think I heard you say roughly targeting the fresher -- target of around 20,000 again. But do you envision a scenario where, I guess, the total headcount could ultimately be down in total when the year is over?

And also, if you can help talk about the subcontractor intensity that you're anticipating in the year ahead?

So on the overall headcount, first, as you pointed out, we will recruit 20,000 college graduates. That's our plan today. We have a model which does some of it at a one particular time and the rest of it throughout the year. So we have like a variability built in if we see some changes. But what we see today, we think 20,000 looks like a good place to start.

We still have at least now if I look out for this quarter, next quarter, very good demand for people, which are coming at higher levels, lateral recruitment. So I think that will continue. I don't see that our headcount is going to be -- like we don't have a plan that the headcount will be less at the end of the year. We'll see how the demand environment plays out, but it's not a going in sort of a view that we have. Of course, we have -- we basically look at Q1, Q2 and the rest we build out on the models we have.

Subcon...

Yes. And on the subcon, Bryan, if you look at last few years, our subcon as a percentage of revenue has come down. Obviously, it's also a factor of the growth. So typically, we use subcons to meet the demand, which comes in immediately. We don't have the requirement skills, et cetera. And then we backfill that through the employees, and that's a cycle that goes on.

So we don't really expect subcons to significantly change from these numbers. Over a medium-term period, we expect to maybe go towards the lower end. I mean, to slightly go down from the current level. But at this point in time, not significantly changed.

Next question is from the line of Gaurav Rateria from Morgan Stanley.

My first question is on the construct of growth. When I look at that, there are broadly 3 factors that comes to my mind. The first is the macro, compared to last year, it appears that the headwinds related to tariff, et cetera, are not there. So there is slight improvement, which is reflected in 40% of your portfolio that you talked about.

The second factor is AI services, which probably has become larger than the last year and growing faster, which again is a tailwind. And the last factor could be the deflationary impact on existing business on account of productivity savings.

So the fundamental question is that the first 2 tailwinds look better than last year and the growth rates in organic terms does not look better at the midpoint of guide. Is it that the deflationary impact assumed in your guidance at the midpoint is slightly higher than what you have seen in the last year?

Gaurav, this is Salil. I think what you described is the way it starts off, which is we see very strong activity on AI services. On the macro, as the year progressed last year, the situation of the tariff got better and better understood, as you know. Then when the war started, that again had a little bit of a constraining effect on the macro. There's a general view that there's coming to a resolution, but it has not happened. So while some of the economic indicators are forecasted in a better way, it's not yet into the system in that sense. So we'll see when it actually comes in.

Then if you look at the couple of things that Jayesh shared on the specific -- on the manufacturing Europe, on the specific, on the on-site mix, when you put all that together, we see actually something which looks stronger in that sense to what we saw last year.

Now the compression is definitely there, but it's not -- I don't know if I have a sense that it's more than last year. We are definitely seeing a compression, but we're also seeing the growth, and that's how we are sort of dissecting it, if you will. And Jayesh might have something to add.

So Gaurav, maybe a couple of points in addition to what Salil said. If you look at last year, we started with 0% to 3%. And as the visibility improves, every quarter, we either tightened the band or improved the guide from where we are. The idea of guidance is to reduce the asymmetry and provide a view as to where we see -- what we see today. And this is what we see today. We do have a client in Manufacturing in Europe, where we have stayed away from a deal where it did not make us make -- meet our return estimations.

There's some ramp downs on the clients happening because the client is going through a challenging macro environment. So that is baked in. We have also baked in the on-site mix that will impact in the guidance. The exit trajectory of on-site mix is already pretty much 40 to 50 basis points from the future year perspective. So that is baked in, in the guidance already. And the result in this 1.5% to 3.5% guidance that we have announced. Of course, if the visibility improves as we go through the year, we will relook at the guidance.

The second question is on the new AI services, would it be fair to say they come at a relatively higher revenue productivity than the core business and also better gross margins or not?

Lastly, Jayesh, any color on when would the wage hike cycle kick in during the current financial year?

So Gaurav, generally, the AI projects come at a better pricing, and therefore, it reflects in a better margin. Of course, it also has a higher cost compared to the regular project because the talent is a premium talent at this point in time.

So it's always a factor of how much ahead of the curve you are in terms of benchmark, and that's what will define the premium that you'll get in the market, right? If you are at the benchmark level, you wouldn't get a premium. If you are ahead of the curve, you do get a premium. And at this point in time, if you look at the numbers in terms of deals that we are winning, we have won $15 billion deals that kind of talks about our positioning in the market. You did see on the AI Day, everything that we presented in terms of our capabilities and what clients are saying in terms of our AI capabilities. So I think that kind of gives us the comfort and confidence that we are in the right direction, and it's also reflected in the pricing and the margins on the [ energy ].

In terms of wage increases, we haven't really decided the timing at this point in time. We do take multiple factors when we decide that in terms of the level of attrition that we have, when did we do the last wage increases, what the market scenario, what's the inflation, et cetera. We will take all of those decisions into consideration and decide.

Next question is from the line of Sumeet Jain from CLSA India.

So Salil, firstly, I wanted to check in the last 2 months with the latest launch of Anthropic models, have you seen increased productivity demand from the clients? I mean you mentioned in the press conference that nothing material has changed in the last 3 months. Can you just specify what kind of client conversations are you having around productivity?

So there, the sense I have is the need for productivity is similar. There is some level of competitive intensity, which is higher, which then leads to more sort of demand. There are some cases where it's way outside the bound where there is not a lot of engagement then that is something which we don't see a way of getting to. So we are not going down those paths. But those are very infrequent.

If you look at the vast majority, we see -- not just like something is complete -- big changes has come literally in the last 2 months or so at this stage. Now things are moving fast, productivity over time, which is over multiple quarters, year, that has changed. But it's not that something suddenly is like a step change in the last 2 months that we've seen.

And, can you also help throw some light in the new deals what you have signed? I mean, are the productivity levels with usage of AI tools similar to what you are in a way passing on in the existing business? Can you give some -- because the order book looks pretty strong on a Y-o-Y basis for the full year. But that is not translating into your improved organic growth in FY '27. So is it like the base business is seeing a much higher deflation than what each one of us were expecting? And with the improvement in AI models, can it actually further accelerate in the coming quarters? So can you show -- throw some light as to how you are seeing the market?

So there -- I mean, we are not, let's say, sharing the specifics on what we are seeing in the portfolio, in the growth compression side as opposed to what we've shared, which is our overall guidance with some of the points that Jayesh mentioned, the on-site mix, the manufacturing, et cetera.

So I think we see with that solid growth outlook where we're keeping pace, making sure that what we are seeing in the AI services growth, some of the other areas of growth that we see is growth, which then manages the compression that we see on some of the other parts of our business. So we don't have a way of sharing that this is the compression, this is the gross growth and then this is a net sort of a growth, if you will.

Got it. Got it. I think that's always a difficult thing to quantify. But also, if you can just flag in terms of any quantification you can give the impact of the European Manufacturing client sort of ramp down or maybe some competition kicking in there?

And I guess, Jayesh, you also mentioned that the shift to more offshore will have a 40 to 50 bps impact in FY '27. And I guess there were some articles around Vanguard in-sourcing. So if you can quantify these 3 things, how much is the impact on your guidance in this year?

Yes. So, if you look at what I said earlier, 1% impact of -- so 75 bps to 1% impact will come from the European client, which is a combination of a deal which did not meet our returns expectation and the ramp downs in this client through the year as the macro environment is challenging in that sector. The 70 basis points is a reduction in on-site mix we are expecting. 40 to 50 basis points is already visible in the exit trajectory, and we do -- as we see forward, we still believe there will be even further improvement on the on-site mix. So that will also impact the revenue growth from that perspective.

Next question is from the line of Jonathan Lee from Guggenheim Partners.

Percentage of net new deals came in at the lowest level we've seen in recent years. Can you help unpack whether that's a function of capability set, AI pressure potentially impacting demand environment or any other factor there?

And can you walk us through your expectations for net new deals for the year given what you're seeing today in the pipeline?

Jonathan, sorry, can you repeat the question?

We're seeing percentage of net new deals come in at the lowest level we've seen in recent years. So can you help us unpack whether that's a function of capability set or AI pressure impacting the demand environment or any other factor there?

And can you walk us through what you expect for net new deals for the year given what you're seeing in your pipeline today?

So Jonathan, if you look at the combination of net new and the renewal is what percentage of deals are coming into -- coming in for renewal and what percentage of deals are in the pipeline from a net perspective.

For the full year, if you look at, we did sign $15 billion of deals, 96 of them pretty much 55% net new in that. So I think by any stretch of imagination, that's a strong performance. It's a 25% -- almost 25% growth on a year-on-year basis.

Got it. And as a follow-up, can you help us understand what transpired over the course of the quarter and how that may have tracked relative to your internal expectations? I'm hoping to get a better understanding of when you may have started to see some of the outsized deflationary impact or some of the downtick in revenue realization or any other dynamics at play there?

I mean we don't really give a visibility in terms of what were we setting as goals or looking at plans in terms of net large deals and performance against that. I think in our view, $3.2 billion is a strong performance. Yes, we do see in some buckets, some slower decision-making in March. But I don't know if it has got a significant impact on -- in the large deal sign-ups. I wouldn't call that at this point.

Next question is from the line of Vibhor Singhal from Nuvama.

Two questions from my side. The first question, Salil, is basically on the AI deflation or the compression part that we've been discussing a lot. So just wanted to get some color as to where do you think we are in that revenue depletion cycle. So let's say, if I were to compare it to the last digital cycle, we had revenue compression, which kept kind of increase and then we reached a trough.

And from there, basically, that has started coming down. And along with we had incremental revenue coming from the digital business. I would assume the cycle should pretty much follow the same order. So while our GenAI revenue and which is for the other companies also is reporting very strong growth, the revenue compression continues to be quite substantial at this point of time.

So do you think we are already at the trough of that revenue depletion cycle? If not -- I mean, I know it's difficult to quantify the time line. So basically, are we still away there is more deflation that you think that might come in? Or do you think we are basically done with the worst is behind? And the deflation will still continue, but it might be not as much as, let's say, going forward as it was before? And then I have a follow-up for Jayesh.

So this is Salil. On that, what we are seeing is there are different sort of dimensions to the compression, meaning -- we are now working with clients where some of the productivity discussions were baked into the deals over the past year or so. And then you have a multiple year outlook. So all of that has not happened on the first year. It goes through it.

So the actual compression will be dependent on the mix, first deal, second deal and so on. We have not -- we've not got a sense of where we are on that path, but we have a sense of like what the foundation models and other tools are able to sort of support and use that as a basis for what we are doing with forward deals like 3-year, 5-year deals and so on. But on that sort of a scenario, we don't have a view we can share on like where that path is. But we are definitely very clear on where -- like when you're working with the foundation model and tools, what is possible, where is it effective, different models or different tools are more relevant for different parts of the AI work that we are doing with clients. That we are very, I would say, close to.

Got it. Got it. If I may just extend a bit on that. So let's say, the deals that we are signing at this point of time, you mentioned many of them have that productivity benefit already baked in or, let's say, built into the original deal. But as the cycle evolves, are we also seeing, let's say, deals which we had signed, let's say, maybe 6 months ago or 12 months ago?

And there, the client has come back and asked for incremental productivity benefits to be passed. I'm talking about the recent deals, not the earlier deals. I'm sure the earlier deals are seeing that kind of a response from clients. But in recent deals also, are we seeing that kind of a movement in our kind of conversations?

So Vibhor, I don't think we have seen scenarios where what we signed a few months back, a client has come back and asked us different productivity to be baked in again. What Salil was talking about when a deal comes up for bid or when you're bidding for a new deal.

Got it. Got it. Sure. Just one last question for you, Jayesh. In terms of the margins, I think this quarter had a very good tailwind from INR depreciation. Now we know that for a long, the industry has moved mature to a state where the rupee depreciation doesn't lead to much of margin expansion over the medium to long term.

But we have generally seen a temporary quarterly bump up in margins because of INR depreciation. Has that benefit also kind of stopped trickling in because not just for us, but for most of the players in the industry, we're not seeing any kind of a margin expansion. Is it that -- in this quarter specifically, is it that those benefits are being invested somewhere else? Or is it that those benefits have stopped accruing at all and those are being passed to the client immediately?

So 2 points there, Vibhor, generally, I mean, you do have rupee benefit that sometimes gets offset by -- or most of the times gets offset by cross-currency headwinds, right? Because when U.S. dollar appreciates, it depreciates again. Most currencies and that kind of offsets each other.

And your portfolio of non-U.S. as it goes, that offset becomes larger and larger across us and across the industry also, you would have seen that. I mean there were times when the U.S. dollar used to be 70-plus percentage or U.S. used to be 70, 75-plus percentage. That obviously has gone down significantly. And therefore, the headwinds from the other currencies come in.

If you look at this quarter specifically for us, as I called out in the margin box, there was close to 50 basis points of headwind that we got because of amortization of one of the acquisition-related intangibles. Last quarter, we had a 30 basis points gain. So in a way, these 2 went into 2 different directions for us in terms of margin impact, both became a headwind. And then 20 basis points on account of employee-related costs. So all of those were headwinds that were offset by 40 basis points from currency and 30 bps from [indiscernible].

Next question is from the line of Abhishek Pathak from Motilal Oswal.

So I had a question around the deals that we left on the table. We saw a similar comment from one of your sort of peers as well. So just curious sort of what is happening over here? Are we being disrupted by, let's say, leaner sort of more AI native sort of companies who are pricing the deals very low by the delivery model changing? Or is this a race to the bottom from traditional vendors who are just essentially sort of creating a pricing -- creating irrational pricing. So very curious as to what's happening here?

And over the next 2- to 3-year period, do you think the industry needs to find newer leaner models to sort of price the deals? And how much is sort of possible to kind of change over here in the short term?

So there, it's not that this is something widely prevalent. We do see sometimes a particular sort of competitor doing pricing, which seems sort of unusual. But this is something that's happened over the course of the years for different reasons. Just now, it may be linked with the clients' mind to AI productivity.

In other times, it's got other things. So I don't see that it's something which is sort of across everything. At the end, we had 96 deals with close to $15 billion in large deals for last year. So it's very sort of broad-based robust outcome, plus the pipeline is pretty good. But there are anecdotal things where some of the productivity thing looks out of the range that we see with what's possible with what we have understood with some of the foundation models. So it's more that sort of comment, not -- at least we don't see that as being a sort of trend of some sort.

Next question is from the line of Keith Bachman from BMO Capital.

I had 2 questions. The first question is related to pricing. And I wanted to understand the context of how pricing competitiveness has changed. And you started the answer on the last question and really, a, is it more competitive today than it has been over the last couple of years? But b, the spirit of the question is my understanding when some of your competitors are getting more aggressive on pricing, they're introducing cost curves associated with the deployment of AI that may have more uncertainty surrounding those cost curves because this is new technology and we're -- I think everybody is trying to figure out what it can and can't do at the current level.

So does that introduce incremental risk in how you're philosophically thinking about pricing? If you could just talk a little bit about pricing dynamics with the introduction of AI. And I do have a follow-up.

I'll start on that pricing sort of point. The way we are seeing it is the point you made about competitive intensity, we do see there is increased intensity. If you look at last financial year, we had a growth, some other players had negative revenue. So one can sort of imagine some of that sort of a scenario.

In pricing, it's actually, Jayesh will talk a little bit about it. I think overall, our realization is better in the year than we have seen before. So maybe the execution is better and the portfolio, at least we feel, is less risky in that sense. So I don't think we have what -- if I understood well what you were describing.

If I can just add to what Salil was saying, if you look at a little elevated level, despite the softer volume through the year, most of our growth came from the realization. That reflects in what we have been able to get on the back of AI that reflects in the value that we are creating for our clients. And to some extent, that also reflects the contribution from Project Maximus through the lean automation, value-based savings and all of those tracks, right?

So that is given. If you look at -- despite the competitiveness in the market, despite all of that, we've been able to maintain our margins for the year. We've invested back in the business. 50 basis points -- or 40-odd basis points in sales and marketing, the AI talent that we are building, the AI capabilities that we are building, all other AI-related investments. All of that has been absorbed in the margin while keeping margin constant.

Okay. Let me ask my second follow-up question, and it also speaks to or questions the growth algorithm. And I'm trying to understand how the growth algorithm may change from a volume perspective given the AI efficiency gains on the supply side. And the way I think about it, and I've had -- we've had this conversation with one of your competitors, if you're trying to grow at 3% in the past years, you might have to grow volumes by 5% or 6% to get to 3% growth.

And one of your competitors suggested that, that volume variance may need to double because of the efficiency gains to get to the same revenue growth trajectory. And I just wanted to see if you could think about over the -- how is the growth algorithm on a volume basis different today because of those AI efficiency gains as you look out over the next 12 months versus what it's been over the last couple of years?

So Keith, the reality is we do see -- as Salil was saying earlier, we do see some deflation from our existing services, right? And largely part of that is getting offset by the new services and new AI-driven services.

Overall, at this point in time, the volumes for the last year has remained flattish. And as we go forward, we continue to see volumes to remain flatter or marginally positive as we -- what we have baked in the guidance at this point in time, which is reflected in the lower end. On the upper end, as I said earlier, we have expected better macro environment, which should reflect in better volumes.

Next question is from the line of Apruva Prasad from Franklin Templeton.

Any comments on the direction of the on-site mix? I'm trying to understand if the AI compression or just AI embedded in services and contract structures, is that impacting the delivery mix?

No, Apurva, I think it's multiple factors, a little bit of the environment, a little bit of the visa situations in some of the countries, a little bit of our own initiative to deliver more from offshore. So I think it's a combination of all of that.

So [indiscernible] that third party...

Sorry, just to add, the discretionary spend has also come down, which generally needs higher on-site.

Okay. And for FY '27, the on-site exit should be similar and third-party cost, I think you said will be similar next year versus this?

Third-party cost, I did say that earlier, we expect it to be in the same similar range. FY '27 exit, it's difficult to project. At this point in time, as I said, the FY '26 exit itself gives us approximately 40, 50 basis points of lower on-site mix, and we think this trend will continue to some extent. But it's very difficult to predict what will be FY '27 exit.

Ladies and gentlemen, we'll take that as the last question. I'll now hand the conference over to the management for closing comments.

Thank you. First, thanks, everyone, for joining. I just want to share a quick summary. We had a strong FY '26, 3.1% growth, 21% margin, very good large deals close to $15 billion. We have a growth guidance for the coming year. We have a mix of growth drivers and compression, overall growth guidance and adjusting for some of the one-off technical factors, a larger growth like-for-like basis. The AI services approach and strategy, I think we've laid out is resonating with our clients very well. We see all of the 6 areas in our pipeline, very good partnerships with the AI foundation model companies and other tool companies.

With all of that, we look ahead to a strong successful year in this coming year and look forward to seeing all of you -- catching up with all of you in the next quarterly call. Thank you. Take care.

Thank you very much, members of the management. Ladies and gentlemen, on behalf of Infosys Limited, that concludes this conference call. Thank you for joining us, and you may now disconnect your lines. Thank you.

A very good evening, everyone, and thank you for joining us today at our fourth quarter financial results. My name is Rishi. And on behalf of Infosys, I'd like to welcome all of you. Once again, apologies for the delay. As always, we request one question from each media house, but I know we are delayed. So we may accommodate a little more. We don't know. But with that, let me invite our Chief Executive Officer, Mr. Salil Parekh for his opening remarks. Over to you, Salil.

Thanks, Rishi, and thank you all for being here. Sorry, we are late. We delivered a strong performance in financial year 2026. We had growth of 3.1% for the full year in constant currency terms. On Q4, our growth year-on-year was 4.1% in constant currency terms. We had strong growth in financial services, in communications, in manufacturing from the industry side and Europe as the geography side.

Large deals were very good, $14.9 billion for the full year, $3.2 billion for the fourth quarter. The full year was 28% larger than it was the previous year. We shared our AI strategy during the AI Investor Day a few weeks ago. We see a large addressable market for AI services across the 6 areas that we mentioned: AI strategy engineering, data, process, legacy modernization, physical AI and trust.

With our Topaz Fabric platform for AI and our CoBolt platform for cloud, we have differentiated capabilities, the capabilities that are operational today and that are working with our clients across each of these 6 areas of the AI landscape. As we look ahead to the financial year 2027, we see large opportunities in AI services. We also see continued competitive intensity, and we see an AI productivity impact, a combination of these things.

With a clear AI strategic road map and a real-world toolkit of Topaz Fabric, we are well positioned to support our clients' transformation, technology and operations objectives. Our revenue growth guidance for the financial year 2027 is 1.5% to 3.5% growth year-on-year in constant currency terms. We expect acceleration of growth in financial services and in energy utility resources and services vertical. Our operating margin guidance for financial year '27 is 20% to 22%. With that, let's open it up for questions.

Thank you, Salil. Joining Salil is Mr. Jayesh Sanghrajka, Chief Financial Officer, Infosys. The first question is from Ritu Singh from CNBC TV18.

Salil, first, on your guidance itself, 1.5% to 3.5%. If you could break up for us, there are a bunch of acquisitions you've made at the end of the quarter. By when do you expect them to close? Will it be sometime during the course of FY? And if yes, how much of that is baked into these numbers? And especially on the discretionary spend environment because we've heard from your peers like HCLTech, for instance, talking about how there were 2 large U.S. telecom clients that had cut down on spends.

There were cancellations of 2 SAP projects and so on. Wipro again, giving a similar sort of commentary. So what are you seeing from your clients in some of the verticals you had highlighted the last time that we're seeing weakness? What sort of guidance you have there? Secondly, on your margin, 21%, if you could break up for us, how much was the tailwind from currency, et cetera? What portion have you reinvested?

What the philosophy there is? And Jayesh, 20,000 was the figure you gave us for hiring for the last fiscal. What's the plan for this year? What are the wage hikes that you've planned and the time period for that? And Salil, if I may, there's been some speculation about your tenure here at Infosys. Your current term ends in March next year. Has there been a discussion at the Board level about a potential extension? And would you wish to continue for a full term? What's been the talks around that?

So let me start with the industry view on the guidance of the revenue. Jayesh will give a little bit of the color with that acquisition, what you mentioned, what the way we have made the guidance and some other market outlook. So what we are seeing right now is financial services, we are seeing an acceleration of our growth next year. So we had growth in financial year '26, we're seeing more growth. In energy, utilities, services, resources vertical, similar, good, more growth there.

What we are seeing in terms of projects, we see that at the AI Investor Day, we shared that our AI services revenue was growing nicely. We see on the large deals, the net new is pretty large for the full year at 55%. So that gives us support for growth. And we see the compression that we mentioned in that AI Investor Day and earlier just now as a combination. We are not seeing something that has unusually changed from that last quarter to this quarter.

In the sense, these are the scenarios we were seeing. It's not either become more or less. It's that sort of a scenario. Good growth on those industries I mentioned, good growth in the AI and compression and there's competitive intensity. And all that put together with a little bit of like a color on the acquisition is where the guidance comes out. And then on margin also, Jayesh will give some view and on the...

On AI, for instance, you told us in your investor briefing that 5.5% of the revenue in the third quarter came in from AI. The total addressable market is about $300 billion to $400 billion. In the fourth quarter, is there a number you could provide us, annualized, what is the number you see, if there's more clarity you could give us? And -- or what market share do you target from this $400 billion figure?

So we are targeting a very good market share from that number, which was for 2030, what we had given the addressable market from an external study. The growth in AI services is very strong, but we have not disclosed that revenue number externally yet.

5.5% [indiscernible] third quarter. Is this roughly the number?

5.5% is that, yes.

Yeah. Was it similar in the fourth quarter?

No, it's growing. It's much more growth in the -- but we're not giving the number, but it's growing very nicely.

So, it's higher than 5.5%.

Yes, yes.

Okay. If you give us a comment on your tenure as well.

I'll let Jayesh answer the other questions.

Yes. So if you look at the revenue guidance, and I'll just maybe come back to the Q1 -- I mean, full year revenue numbers. The 3.1% growth was after absorbing lower third-party related revenue, which was 1% and the lower on-site mix, which was 70 basis points. So we should look at the revenue numbers in that context. Both of that impacted the revenue from the overall revenue growth perspective.

In terms of the guidance for the next year, we had 3 acquisitions -- 2 acquisitions and a JV that we announced last year. The acquisitions with an insurance company, which is Stratus, which is already closed and it's baked in the guidance. What is baked in the guidance is approximately 25 basis points or 0.25 point of the guidance.

The other acquisition was Optimum, which is not baked in because we have not closed it yet. We are still awaiting certain regulatory approvals. And once that is closed is when we'll bake in. The third one is a JV with an Australian client of ours, which is also pending regulatory approvals right now. So we have not baked in both of that in the guidance at this point in time.

So only Optimum is 25 basis points.

The Stratus is 25 basis points at this point in time.

The margin breakup and the hiring plans.

Yes. So if you look at the margins, the full year margins is at 21%. The quarterly margins also 20.9%, very close to 21%. If you take the -- if you look at the puts and takes of the margin walk from the last quarter, we got 50 basis points impact from an acquisition-related amortization that we absorbed.

There was a 30 basis points of one-off benefit that we got Q3. So when you compare, that's a headwind and 20 basis points on account of comp-related matters. That was partially offset by 40 basis points of currency benefit and 30 basis points came from our Maximus performance.

I think you had the question on tenure.

Yes. And your last question was hiring. The last year, we had announced 20,000 for FY '26, and we have hired more than 20,000 freshers from the market. This year also, we are expecting at least 20,000 freshers to be hired.

On the tenure, I think, Salil.

No comment on that.

Right. Thank you, Ritu. We'll now move to Mansee Dave from ET Now.

My first question is on the margin sustainability. The margins have remained resilient despite multiple headwinds. So what gives you confidence in sustaining the same going forward? And the next question would be on the global uncertainties, which we have seen these days. So global uncertainties like the geopolitical tensions and cautious client spending, let's say, what early signals are you seeing for FY '27? Do you expect the growth acceleration or another year of consolidation moving ahead?

Let me start on the margin. Jayesh will have much more color. I think some time ago, Jayesh started the program on the margin expansion or margin protection. And that is one of the main reasons why the company has been able to remain resilient on the margins. So we have been fairly consistent across the last number of years. The program is very strong and is being executed well.

We will continue to see there are also great pressures, but we are confident with the guidance that we have given this year for the margin between 20% and 22%. And then Jayesh will give a little bit more color, but on the geo -- that environment, what you asked. I think what we are seeing there is at the start of this year, we were starting to -- the start of the calendar year, we were starting to see the global environment, the growth, especially in our strong markets, looking good.

And even in the markets where we are now making a bigger movement, for example, Japan and all was growing quite nicely. Now with the situation with the Iran war, there was a change in the economic environment. Now from what we are seeing, there seems to be path towards things stabilizing. We hope everyone sort of gets there. From then, what we understand, like just talking to people in the market and the clients is that the underlying resilience of some of the economies where we have the big markets is pretty good.

The economies are doing well. There's good investments. AI is growing well, and we have a good strategic approach on AI services. So my sense is that will definitely help, but we'll see how it plays out. So we have given the guidance of the growth based on what we are seeing today. We'll see whether some of this comes through or some of these changes as the year goes.

Yes. If you look at the margin program, and like Salil was saying, I think it's done well. In the first year, we expanded margins by 50 basis points. This year, while we have maintained margins at 21%, I think we have absorbed a lot of headwinds, and we have also invested a lot in the business, right? Our sales and marketing cost has, for instance, gone up by 40 basis points.

We have invested in all the AI-related capabilities and the AI partnerships. We have invested in talent. So I think we have absorbed all of those and delivered 21% margin. That is what gives us confidence of way forward. But at the same time, there are going to be headwinds, right? There is competitiveness in the market.

There is acquisition that we have done, the acquisition-related costs will impact margins by another 60 to 70 basis points. So those are the headwinds that we will have to absorb while we talk about the margin program. And our endeavor is to improve margins on a medium- to long-term period. But this year, we are confident of delivering 20% to 22%.

The next question is from Chandra Srikanth from Moneycontrol.

Salil, you mentioned BFSI and energy and utilities a couple of times. I just wanted to understand what is giving you so much of confidence there. And as Ritu pointed out, some of your peers have spoken about client-specific issues and how discretionary spending -- spends continue to be a challenge. So what is working for you in terms of the normal business as well as AI business? And AI also, because you mentioned last time that it's now 5% of revenues for you.

If you can give us a sense of where things stand now, it will be really useful. In terms of acquisitions, do you see opportunities in AI start-ups, is that something that you will look at? And how do you see Mythos impacting your business, if you can give us some color on that? Jayesh, some details on the wage hikes for this year, how you're thinking about it? And I think after 5, 6 quarters, we've seen employee count actually declined by over 8,000. So why have the number of employees declined?

So let me start on the financial services and that sort of environment, what you mentioned. So what we are seeing is -- and some of this we shared in that AI Investor Day, like if you look at many -- all of our industry groups with our largest clients, we are already the AI partner of choice, and that's giving us a lot of traction. Now you look -- I mentioned financial services, energy, utilities, but you look at manufacturing, you look at telco, some of the work we are doing in those industries, there are large programs in the pipeline for things which was within that 6 grouping.

So take an example of building agents, take an example of legacy modernization. We are also seeing a lot of discussions with clients, which are a combination of tech services and operations, the tech and ops type of businesses. And there, again, we are in a good position, which is in the pipeline. So that is giving us a feeling that this is looking similar to where we were, like it's not something has suddenly changed in that sense in that -- at least with our client base and so on at this stage, what we see here.

Then I think on acquisitions, you've seen we did 2 acquisitions. The thing with that is the pipeline, again, we have Jayesh and Shyam looking at a very strong pipeline, but we have a very careful approach, strategic fit, cultural fit, value fit. So it has a lot of -- an integration like we have to know how it's going to integrate into where and so on. So all that keeping in mind, we could see suddenly a lot, but suddenly, it could be 3 quarters of nothing also. But we are in it, meaning we are looking.

And what we did on acquisition was like health care. Health care, we see a good market. We have a good business. We think we can do more. So it was a good way to expand. And I think it's a good company there in the sense of we will be integrating and culturally, it's aligned. Same on insurance. That's a company which is working with the Guidewire platform package. So that is something which we are very keen on expanding. So like that, acquisitions will continue.

On Mythos, I think there are multiple things. So the -- what -- because -- not everything is released to everyone, but we have some, let's say, good relationships with the company to understand a little bit from the outside. It will -- it is exposing more vulnerabilities than one thought possible previously. However, other models are also exposing vulnerabilities. It's a question of running that -- those models in that way.

My sense is it may also open up opportunities for work for Infosys, which is to help clients who say, look, how can we make sure that you don't succumb to that vulnerability. So we are looking at it in both ways. And my -- I mean it's early, very early discussions, but my sense is if we build a good like capability in that, we could help our clients to say, look, let's make sure that your vulnerabilities are better and quickly protected.

AI revenue.

AI revenue, yes, exactly.

[indiscernible].

Meaning we are not sharing the number, but it's growing.

[indiscernible] sharing because last quarter you disclosed it for the first time. So why are you not disclosing it?

So what we did was in the AI Investor Day, it was a strategic sort of outlook. So we want to just make sure that we communicated that it is in a material way and it is growing nicely. At one stage, we will, but today, we are not sharing.

Has it touched double digit of your revenue? Like is it now 10% of Infosys revenues?

Is it 10% or 15%, but we're not sharing the number.

I think a couple of questions for Jayesh.

Yes.

So if you look...

[indiscernible] net employees.

Yes. So if you look at the headcount, our headcount sequentially has gone down by 8,000 employees. But if you look at on a year-on-year basis, it's still grown by 5,000. There's always some quarterly seasonality, but if you keep that aside for a moment, headcount is a function of the number of people that you have, the utilization that you have, the volumes that you see.

This quarter, the volumes were softer and that equation is what we will end up net hiring, plus the fresher that you have in the system. So I think it's all on the demand-supply equation, and that will -- that's how it will play out. The output is a result at the end of the day, in my mind. So that's how the headcount will play out.

We don't really think it's going to be a sequentially number which will keep going down at the end of the day. It's one of the things. I think the way you should look at it is a full year basis where we have still grown 5,000 as a headcount. On the wage, we haven't really made a decision at this point in time in the quantum and the timing of it. Once we decide, we will let you know.

Thank you. Thanks, Chandra. The next question is from Shilpa Phadnis from the Times of India.

If succession planning at Infosys is a slow build-out, the archetype of the reinventor CEO is going to look very different, AI native, consulting-led. You have some of the internal contenders for the next leg of succession, some of them are in the room. Previously, you disbanded the President structure. Do you think you're going to reintroduce that just to hot up the internal slate for the succession planning?

No comment on that.

Okay. Sir, also, if you can talk about -- if you just revisit your deal pipeline today, what part of it lends itself to AI deflation? And how are you going to offset those, especially when clients are very demanding when it comes to productivity gains?

So there, the -- what we shared in that AI Investor Day is how we are looking at it, we have really 3 areas which we see like a growth area. So one was we talked a little bit about the AI services, which are growing quite nicely. One, I mentioned the large deals and the net new part of the large deals, which gives us the expansion, the next year revenue of that.

Then the third, which we have been working on internally and is growing well is we are expanding into clients where we have a smaller presence today, but which are very strong relationships of Infosys. So not -- so this is different from the large deals, which are with more larger presence. And there, we are seeing a very good growth. What Jayesh mentioned, there are investments we've done, especially on AI and on this program where we look at large companies where we have a smaller presence.

So those are the 3 areas of growth. And then what you mentioned is the AI productivity, which is what clients are looking at and where we are participating, we have, because of what we have built with the Topaz Fabric, a very good idea of what is doable now, what is doable in the future. And a lot of the tech and ops deals bring that to play right away. Typically, we are also seeing in those -- not all, but in many of those deals in the pipeline, there is -- given the credibility of Infosys and trust, we see something adjacent, which gives us an expansion of scope.

So while it's a productivity improvement in some, but overall scope expansion or what they call the consolidation. So based on all of that, first, we grew in last year. And if you -- sort of Jayesh's points, there were some additional things, like-for-like grew even more than 3.1%. With that, we are going to grow in terms of our forecast for next year. And that shows us that while there is compression, the growth part of our work is larger today than the compression, which is why we are growing.

Sir, and one last thing on your Daimler account, if you can help us, that was one of your flagship accounts. With that winding down, if you can help us understand what's the assessment largely around the capability gap there? And how would you look at backfilling those revenues? And was that factored in your guidance, which is slightly broad-based for the current financial year?

So I have no specific comment on any specific client. But maybe on the manufacturing, you have something on the guidance?

Yes. So manufacturing per se is going to be -- going through a challenging environment, especially the European automobile sector. And within that, we do have certain headwinds from a particular client, which will wind down towards the end of the year. That is baked in, in the guidance right now. So our guidance is 2 points generally, and that is baked in already in the guidance. It's not an expanded guidance per se.

Thanks, Shilpa. The next question is from The New Indian Express, Padmini.

So how is BFSI adopting to AI agents? Are they facing any hiccups because the regulations are tighter there? And is AI beginning to compress the traditional IT services model? Can you quantify it? And which current revenue streams of yours are at risk by being cannibalized by AI?

So in financial services, what we are seeing is clients are moving very quickly to adopt AI. So as an example, if you look at a bank, if they're doing the KYC process, AML process, there's a lot of agents being built for that process, which is growing our revenue and helping them by doing that work with AI. If you look at things on credit, we are doing something with AI there. If you look at building out new capabilities, AI is being used.

If you look at legacy modernization, again, in banks, meaning some technology, which is on an older generation of technology to bring it to current generation, a lot of that is being done with the foundation models. So financial services clients are adopting it quickly. We have partnered with the foundation model companies and other AI leaders, and that is giving us an advantage into that market.

We see the growth is actually accelerating in that industry for us, our business. That is also including the compression. I mean there is compression because of the points we shared earlier on the productivity that clients are looking for and some other areas, which can be more easily used in AI work. So it's a combination of those. But despite that, we are seeing the growth of the financial services.

Is it compressing your traditional IT services model, AI and any particular revenue stream that is being cannibalized?

So there -- yes, no, it is definitely -- so the compression is coming on some of the services and the growth is coming on other services. And the compression is typically in the areas where the AI foundation models and some of the tools are very efficient on that. So you can see that in some of the tech services work, you can see that in some of the BPM work and so on. But it's combined with the growth that we are also seeing. And that balance is where overall, we see growth and in financial services, we see growth.

Thanks, Padmini. The next question is from Shristi from The Economic Times.

So this quarter, we are seeing a sharp contraction on a sequential contraction as far as TCV is concerned. So is that a factor of clients cutting back on their discretionary spending? Or is it the AI-led deflation that we're seeing this? And secondly, Jayesh mentioned that there are regulatory delays as far as closing the Versent acquisition is concerned. So could you give us a bit more color on why these delays are happening because it was supposed to be closed by this financial year?

On the -- when you say TCV must be large deals, I thought we had a good large deals at $3.2 billion for the quarter. So -- we didn't see -- I would say, nothing unusual in that the large deals are always a little bit variable. So it's -- and the $3.2 billion is a large number for large deals for the way we look at it, larger than $50 million deal value. And we had a large -- the number of deals was good. The overall year at $14.9 billion is much larger than what we had last year as well. So we didn't see something change so much in the actual large deal value for us.

But we do see a sequential contraction as far as large deal for quarter 4, I mean. So is that because of...

So yes, if you look at last quarter, we had a mega deal with one of the U.K. clients that we had. And that kind of increased the overall number. If you take that deal out, the numbers are comparable. And the mega deals is always lumpy. It happens. It doesn't happen every quarter, right? So you always have that variability because of mega deal in the large deal equation.

But as Salil was saying, we've delivered $15 billion of large deal for the year, 55% net new. On a year-on-year basis, it's 24% increase. So it's a very healthy performance from that perspective. And on the Versent acquisition, I think these are regulatory approval matters. There are questions or queries that we have received from the regulator that we have responded to. So it's a process that at times is unpredictable.

So, if you could give us a bit of commentary on what the direct impact of the geopolitical conflicts that are happening. Are clients talking to you about any kind of delays in decision-making that they're having?

So there, I think typically, we see -- there's no specific view in that, except that overall, the thinking is to sort of see how it plays out. Now as we are seeing in the current situation, it looks like things may stabilize. So with that, the mindset now is that underlying many things in some of those Western economies are quite good. What they call it, they're resilient. They've been the way that people have described it. And if that continues, we will see -- that always has some correlation to tech being supported. So my sense is, if that happens, we will see some more of the tech spend there.

The next question is from Sai Ishwar from Reuters News.

So just 2 things. If you -- if I just look at North America's revenue contribution, it's been constantly falling from 57% to I think, 55% and Europe is growing. I just wanted to know, like, is there a specific trend there? And also, I wanted to ask on how other geographies like top geographies are playing because you've given some color on -- based on business segments, but how is the U.S., Europe market like in terms of growth, in terms of opportunities?

The U.S., Europe [indiscernible].

See, if you look at Europe, we have had multiple large and mega deal wins in Europe. That is pretty much contributing to the faster growth in Europe. If you look at, for example, one of the largest manufacturing deal that we signed a few years back is from Europe. The NHS deal that we signed is from Europe. There are a few other -- Liberty Global is a deal that we signed is from Europe. So I think those are the mega deals that we have -- that has contributed a better growth in Europe compared to the U.S.

And in other geographies, I mean, first, there are -- within the U.S., there are pockets where we're doing extremely well as well. Some of the industries I mentioned before, we have a smaller business, but like some of the newer geographies like Japan, we are doing quite well. So there are things -- even in Europe, what Jayesh was mentioning is if we look at some of the Nordic markets, we are doing quite well and growing nicely. So it's different places where we put the investment and there's an environment, which is also the local sort of economic environment is good. We see the growth is quite okay.

Thank you, Sai. The next question is from Avik Das from Business Standard.

Two quick questions. Salil, if you can just throw some light on the GCC business, specifically considering the fact that have you seen an increased number of, let's say, mid-market GCCs who have sort of failed to attain the desired level of maturity, carving out certain businesses, brownfield businesses or operations and actually giving it to the service providers like you or the other ones. Have you seen any heightened pace? Just wanted to get some light on that.

And Jayesh, if you can also tell me that when you talk about no wage hikes immediate announcements right now, last year, you followed a normal April to March cycle. Again this time, it's sort of a little distorted. I wanted to understand, this has been going on for the last 4, 5 years. Is there any chance over the next 12 months or 15 months where you see this movement, this volatile movement actually stabilizing? And how much do you see this being a little challenging for the morale of employees going forward?

So let me start on the GCC, the -- first, we have a robust business with the GCC clients. In fact, we have an event tomorrow, which is sort of a large event with all the -- I mean, almost all the GCC leadership in India, where we want to share some insights. We've done something quite special on sort of GCCs built for AI. We've recently had some good success with clients in that. I think your point -- it depends. I don't see a trend like that, but there are some examples. I think those are very much in the public domain.

So there are some examples of that. But in general, there is a -- it's a very strong area of activity for companies, global companies and for us to partner with them, both outside and in India to support them in their different ways from like starting it, scaling it, the BOT type of model, how we make sure the AI skilling is right there at the beginning so that what we think is really working even better is this AI sort of driven GCC, which is where the new attention is with most of our clients.

On the wage, whenever we have decided about the wage or when we consider about the wage, there are various factors that play out, right? What is the performance of the company? What are we expecting in the next few quarters? What is the industry practice? How is the industry expected to grow, what the other peers in the market has done, inflation in respective markets. And all of these -- and of course, the employee morale and all of those factors. We consider all of those factors, and we decide the wage, right? And then we will decide it accordingly. I mean all the factors are always considered.

Thank you, Avik. The next question is from Sanjana from The Hindu Business Line.

So how is Infosys recalibrating to navigate this era of uncertainty that has persisted for a few quarters now? If you could expand on your strategy. And also going ahead, will you take up large transformation programs like legacy modernization, for example, that may be initially margin dilutive? And also some brokerages have pointed out that visa costs may have emerged as a headwind for you this quarter. If you could expand on that, on whether it's offsetting cross-currency benefits due to rupee depreciation? Yes, that's it from my end.

So the first was on, like, how will we navigate and what our strategic approach. I think there what we are seeing is the AI approach that we have shared is really resonating with our clients. The 6 areas, whether it's AI strategy engineering, it's legacy modernization, the process work, the work that's on trust, all of those are something which we can see activity with clients in, in partnership with the foundation model companies with the tools that are being built on the foundation models with the large tech cloud players.

So that, I think, is one of the core elements of the direction. It's a big AI transformation that we are seeing over the next several years within like our work. Outside of that, I think we are building big focus on making sure that the productivity benefits that are available are something that the clients will receive.

Hopefully, we'll keep a little part of it to make sure what we discussed earlier, the resilience in our margin will continue with that. So the first part is more for the growth. The second part is more for the margin. And we see essentially the road map we've laid it out. We've started the execution and the early steps are in a good direction.

Large transformation programs.

Will we take some -- we will absolutely take large transformation programs, but we are very clear that it has to be with an economic profile we can manage. Now having said that, we have a large business. It's a portfolio of activities. But in the portfolio, we want to make sure that we can manage the commitments we are making and the objectives we have internally. But of course, we will take on large -- and we are doing them. Some of the legacy modernization programs. A lot of them become self-funded because there's one example, we are doing a program with a transport company.

There the work is to take from an older technology on to a microservices architecture. The work is going well. The way the estimates or the cost has come, it's 60% lower than what they would have done before the AI approach. And the time is also that much less. And we are part of that program working with a partner to get it done. So I think there are many examples -- in fact, that's one of the -- like in our pipeline, there's a lot of those sorts of things, and there's a few that we are executing also today.

The visa costs offsetting.

Sorry, what is the question, if you could repeat?

Headwinds that are offsetting cross-currency benefits.

No. So I mean, visa cost for us has remained stable. We have not really increased our visa cost. The H1B visa in the new regime, we have not filed it. So our visa cost has remained stable.

The next question is from Uma Kannan from the Deccan Herald.

Now that AI is part of every project, so I want to understand, are clients asking you to cut down expenses. This includes people as well. So are you finding it hard to retain business from existing clients given current uncertainties? Are you seeing any project ramp-downs?

So there, every discussion, as you said, is -- AI is part of it. There are some which we call it this AI-first service, which is the new work in the 6 areas that we have laid out. And then what we've also done is all of our work, we call it AI augmented services, meaning everything we do, we have now infused the AI into it. So every client discussion has got this AI now in it.

Most like there are some work which we do, which is oriented to growth. So we did a project for a consumer products company where we build something which the person who was buying can use on an app and that increase the connect with the customer and increase their sales and so on. So that is not a cost program. But the ones that are more cost, they always -- the clients will always look for the productivity improvement.

And because of these tools and what we have built in the Topaz Fabric, we are able to like create that for the clients. But on balance, we have the growth and the compression. And like last year, the growth, we had 3.1% with all of the variations much higher. And even in the forecast, we have a growth. So we are getting the growth more than the compression at this stage.

Just one more question. You have partnered with AI companies and recently, you announced partnership with OpenAI. So how these are actually helping your clients? You did speak about it, but I just want to understand, are these -- are you seeing projects moving from pilots to production?

There are like a number of projects on production, like large-scale products. Again, if you look at the 2 that I just described, transport and consumer products, those are large programs. There's not a pilot at all. Like in the AI Day, we described about 12 or so projects, which are actual large projects with clients. The partnerships, so you mentioned, we just announced the OpenAI partnership yesterday, we announced the Anthropic partnership a few weeks ago.

The way these are working is they have some good technology on the foundation models, with that, in any of those 6 areas of our AI services, we can take that as a partner and work with our clients. So even in what we shared in the AI Day, we showed some examples of clients and where they are on that hexagon to say how we are partnering with someone and how we are going to that client to actually create revenue for Infosys and more activity for Infosys.

The next question is from Poulomi Chatterjee from The Financial Express.

Just a couple of questions. So I just wanted to understand the reason behind the decline in -- the quarterly decline in headcount. And also, like, as there's new lines of AI services emerging and you're hiring freshers in that regard, like how is the composition of freshers like in terms of coding or consulting in these newer roles? And also like how has pricing evolved so that you've been able to capture value adequately from these AI-led services?

Let me -- do you want to start on that first?

Yes. So if you look at the headcount, as I said earlier, the headcount is a function of what is the growth that you're getting in terms of volume, the utilization that we have and so on. And that's how we derive at the number of people that we need to hire laterally or et cetera. If you look at this quarter, the volumes were softer and that is where -- and utilization was lower. That is where our resultant headcount is lower. But ideally, you should look at it a little longer term.

And if you look at the full year basis, we have added 5,000 people on the headcount. So that's what I would want to say. In terms of pricing, I think pricing environment for us has remained stable. On the contrary, actually, most of our growth this year has been pricing led because the volumes have been softer. And that, in a way, corroborates with the fact that the AI revenue are coming at a better pricing.

And in terms of the people -- one, just on the Q4 a little bit, the seasonality that's what Jayesh was saying. So it's every year, we have this scenario where in the Q4 or Q3 is a little bit like -- second half is a little bit less than the first half. It's just the nature of our activity.

On the people that we are bringing in, so there, in fact, our HR team with Shaji and Sushanth have built an amazing model of how we are skilling them and how at different levels we are bringing them. So we are not only bringing people with one type of skill set. We have different starting compensation for people who are coming with different skills who are more attuned to AI.

Then we are building the forward deployed engineer team, which is being done to make sure that we can do more work directly with clients on business and tech, which is AI tech to make the AI solutions. So both of those are getting developed quite rapidly. And the skilling has gone on. I think over 90% of our people -- yes, about over 90% of people are now getting skilled on different types of the AI platforms.

The next question is from Jas Bardia from Mint.

Three questions. The first one, multiple brokerages have pointed out that the 3 acquisitions you all announced last fiscal would contribute around 200 to 225 basis points of growth in FY '27. Considering that has not been factored into the guidance, if we factor the contribution from those acquisitions, that translates to the fastest growth for the company in at least 3 years. How do you see this going forward?

If you can help me understand the growth trajectory in that sense a little bit more, considering your peers have called out AI-led deflation, multiple clients pulling back their tech spending, that's one. Second, on Board oversight of AI. So how is Infosys' Board actually overseeing the way AI is used for clients as well as internally?

A peer -- one of your peers is giving incentives to executives for passing on productivity gains to clients and many other such measures. So what is Infosys doing in that sense? And lastly, if you can throw a little more light on the kind of acquisitions you will be looking at going ahead. So yes, that's it.

So on the first one, I think -- so Jayesh shared that like the one acquisition that has closed, we have already put that in. I think the estimates -- meaning when we announced the acquisition, the revenue number is known and so on. So what you're describing, I'm guessing is based on that analysis. It's just a function of like which date it will close. Sometimes like it may take a week, it may take a month, it may take 2 months.

It's not going to take 5 years. So it will get sorted in this thing. My guess is -- so what we are thinking -- there's no -- like we are not trying to give a guidance assuming like it will come in. But as soon as it comes in, we will obviously put that in and do it. I think the math, what you're saying on a full year basis is approximately correct. So that's not a problem on that at all. And our growth trajectory, I know what you said like with some other things in the industry.

But we see this growth for this year, even without acquisitions, there's a growth and with it, and we will continue to see that. I think we are very clear that with that AI services work, some of the other things we talked about earlier like on the large deals and so on, we see the growth coming. And yes, there is compression, but we are managing that growth today and the forecast for this year is very clear on the growth.

On the Board oversight.

The Board, in fact, as you noticed, we were a bit late today coming. So we just had an update. We had like a full -- what we did in the AI Day, we did the full update with a lot more detail internally, and there was a lot of discussion. So the Board is very active in our AI work looking at it. And actually, Nandan himself is very active because he's got a very good vision on where the AI is going.

And also helping like a lot of the Topaz Fabric, what we have done, he is working to give us the ideas, which, of course, we are building it, but he's the visionary person on that one. Acquisitions, so we will continue to do acquisitions. There's a good pipeline. We did 2, which came like by coincidence like together. But in general, we will continue to do acquisitions in areas like the health care, which we did, where we feel we can expand nicely and the market is good.

Just one last question, if I can just squeeze it in. What kind of contracts are you seeing? And how have they evolved over the last 3 to 4 years from fixed price to outcome-based? If you can just shed some more light on that. And also wonderful to hear of Mr. Nilekani. But if you can just shed some light on what are some of the means that the Board is having a tab on whatever AI goes out and the kind of AI work that Infosys does?

On the -- so there's -- like there's no specific thing like that on what the Board is doing, they're very involved in it, and Nandan himself is there on it. On the contracts, so we are continuing to see the type of contracting that we were doing in the past. There's a lot of discussions now that can we look at something because the AI is transformative that can we look at something which is outcome-based.

We have built with our delivery leadership, with our sales leadership, good models or templates for how those are to be done. And there are active discussions as they -- it's still early times, but over time, there may be more of that, but there are discussions on that. But a lot of the contracts are also on the way that were being done in the past as well.

Thank you. With that, we come to the end of this press conference. We thank our friends from the media. Thank you, Salil, and thank you, Jayesh. Before we conclude, please note that the archived webcast of this press conference will be available on the Infosys website and on our YouTube channel later today. Thank you, and please join us for high tea outside.

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With that, let's start today's program. For our first session on Tech Transitions - Why is The AI Transition Different, please welcome Nandan Nilekani, Chairman of the Board, Infosys.

Thank you, and great to have you all here in these tumultuous times. Today, I'll talk about tech transitions. I have had the fortune or misfortune of being in this industry for more than 40 years and have seen a lot of transitions. So I thought I'll talk less about that and more about why this time it's different and what are the implications of this transition.

Now safe harbor clause.

Now we have seen technology shifts for centuries, whether printing press or telegraph, but over the last 60, 70 years, we have seen a much faster change in PCs, cloud, GenAI, Agentic AI and so on. So change of technology and the speed of change has been a constant for many decades now. And each time there's a change, the way we address that change has been different. So we went from mainframes to mini computers to PCs, client server, LAN, web computing, mobile, enterprise apps, big data. And each time, we had to think of it in different ways, how do you think of it in terms of making it globally available through Internet or how do you do enterprise IT. So each time there was a tech transition, it had certain implications for us. And firms like Infosys had to deal with what was new. So we are used to the fact that each time there's something different.

This time, the AI transition has been much faster than earlier transitions. If you look at the number of years it took to reach 1 billion users, Internet took more than 10 years, smartphones took 5 years, AI is taking a couple of years. Now you have to realize that the AI speed is because of the first 2 things. Internet was already ubiquitous. Smartphones were already ubiquitous. It therefore allowed people to distribute a ChatGPT or Gemini or Claude very easily. So in some sense, the speed of AI is also because of the infrastructure of the previous era.

Now what has happened this time is that this is a much more fundamental change to the way businesses will operate. So this is not a layer of technology. When smartphones came, we could build applications where the -- instead of having a PC, you did it on the phone, like putting a front-end to an existing application. When cloud came, we could do a lift and shift. You could take the app from your in-prem and move it to the cloud. So you could do a lot of things to get going. But this time, it's not that. This is a fundamental change in the way we do things. Obviously, there's a technology dimension and it's all about having AI native architecture. But there's a whole business dimension to this. We cannot run business the old way, and businesses have to change, the customer journeys have to change, all those things have to change.

It's a huge challenge for talent. Talent will have to deal with a world where writing code will not be the goal. It will be actually making AI work, orchestration and those kind of things. So the jobs will change. And operating model, how do we make this at scale? How do you get a firm with hundreds of employees to change all the things and make it work? And of course, our mental models have to change, because we worked -- technology was always deterministic. You said A plus B equal to C. So no matter how many times you said A plus B, the answer was C. In this AI world, every time you give a prompt, you'll probably get a different answer. And therefore, how do you deal with this nondeterministic world. But how do you make sure what you build has the robustness, reliability and resilience of the deterministic world. That's what the challenge is for everybody. So this is a fundamental root and branch surgery of the way business is done, which is why this technology transition is so dramatically different from anything else that we have seen.

Now one clear learning we have is modernization of legacy systems cannot be deferred anymore. What happened over the last 60, 70 years is people would not replace the legacy system, they just added to it. So if you go and look under the hood of a large enterprise, they will have mainframes from 1960, they'll have mini computers from 1980, they'll have LAN from 2000, they'll have all kinds of things, and all coexisting in silos. That is over. If you really want a firm to take advantage of AI, you have to fundamentally clean this up. So this is a massive, massive cleanup job, which everybody is dealing with.

There are reasons for that. One is the financial drain. Many large companies are spending 60% to 80% of their IT spend on maintaining systems. There's no business value out of that. They want to go from 60% or 70% maintenance and 30% new systems to 30% or 40% maintenance and 60%, 70% new systems. They want to flip the way they spend money, but they can't do that with that fundamental cleanup they need. Moreover, many of these systems were designed in an era before you could have online attacks and so on. So security breaches, which you see every day, are just going up everywhere, and they are more state and non-state actors who are getting better at it using AI. So security is a huge problem for everyone. We have seen so many cases in the last few months.

And because the data is all in silos, you can't even innovate fast. So there are fundamental structural issues today we have. So demand side is absolutely demanding modernization. But the good news is, for the first time, because of AI, we have the tools now to do modernization fast and very quickly and at a much more economic way. So we have a huge demand, and we have the ability now to do it, and perhaps our team will talk about that. So fundamentally, accumulated tech debt over decades must be paid. You no longer have the option to defer this. And this is a huge, huge requirement. And obviously, it's a huge opportunity for us.

Now the other thing which is there is, as AI becomes a bigger part of the spend, the balance of advantage is moving towards build rather than buy. And that is actually what is -- if you see some of the concerns about what will happen to SaaS companies and all that, it's because of this, that building applications has become so simple that very often you may just build or you may replace something that you have, which you bought, with something to be built. And so we are seeing -- and that again actually benefits folks like us, because they're about building. And who's going to build it for them? It's going to be us only who will build it for them. So fundamentally, it's good for us.

And the other thing which is there is that our view is that foundational systems will increasingly become systems of record. But the interface will be agentic, because agentic interface makes a lot of sense. Agentic interface allows people to produce something which is designed pro consumer or pro user. And agentic interface enables you to take out the complexity and hide it behind the agent, so the agent is simple to use. It's a very simple idea.

Now enterprises will, therefore, want to put agentic layers on top of all their applications even if they leave the system of record the same. And that is something which will be a combination of bought out agents as well as building their own agents, because finally, the agents have to be composable in a customer journey which is seamless, which is a mix of agents which are your own or from somebody else. Again, that requires orchestration and work which somebody has to do. So there's a huge amount of work required once they go towards build rather than buy.

Now the other thing is, the pace of change is something which obviously we have not seen. We all know about the trillions of dollars being spent and all that. But even the technology can change. I mean, 2023, foundation/frontier model had 100 billion parameters. Today, it has 1 trillion parameter. There were only 10 to 12 agent networks. There are 60 agent networks. So this is only going to go up. In the U.S. alone, there are at least 5 frontier models. In China, there are big 4 or big 5. So this is only going to go up. In India, we have seen so much action, and you'll see some big announcements this week on Indian-based sovereign models.

So I think this is something -- there are certain implications of this, because if I'm a businessman and I have to choose my technology, how do I make sure I don't make the wrong choice, because something which I invest in today may have fallen behind tomorrow. Already people are facing this reality. And therefore, how do you architect your technology, so that you can deal with this rapid change is a very fundamental and structural need for enterprises. And again, they need help on that from somebody who has done this in 2,000 locations and understands the pros and cons of every approach.

But the main thing is that the technology is far ahead of its deployment. Because of this race and spending billions and some AGI and all that, the technology is moving faster than the ability of enterprises to deploy it. If you look at this chart, you can see that the model performance is going up, but the progress in implementing is not really, because implementing this is hard stuff. Fundamentally, it's about organizational change, business change, retraining your people, thinking about nondeterministic approaches, changing your data so it's no longer in silos. So fundamentally, we have a situation where there's a deployment gap between the power of the technology and the capacity of businesses to use this. So if you guys think that some better product has come, nothing is going to happen, because the problem is here, not there. You get it. It's about how fast companies can implement. So you have to look at that.

And we call this the deployment gap, but this is actually a concept by Professor Clayton Christensen Harvard 25 years back. He called it technology overshoot, where technology gets ahead of the need. And in fact, he argues that that's how newcomers come, because newcomers can then launch new products that are not as sophisticated, but good enough for customers. And Satya in his recent blog talked about model overhang, which is the same idea. Fundamentally, the tech will keep getting better and better because billions are going to be poured into it, there's a massive competition, but enterprise deployment is not going to go up. And this deployment gap is what we can help to address. So again, it's a very important point.

Now I think talent transformation is huge. It's not that you will not need, you will need talent, but it will go from QA testing or development. We have all kinds of new roles, AI engineers, forward deployment engineers, AI leads, forensic analysts, data analysts. So fundamentally, the challenge will be how do you take your workforce and make sure that they are reskilled and ready for the new business. And that's really the challenge that all the firms will face. And this is something -- so there will be roles. Now the way you hire will change, the way you train will change, the way you deploy will change. All that is going to happen. And I think we'll have sessions on that. But fundamentally, there will be a need for people, but they'll be doing different things.

Also, a lot of the talk of productivity is greenfield. Writing greenfield is not a big deal. I can take a tool and give it to a kid and he'll generate 1 million lines of code. But that's not the real world. The real world is the fact that companies have trillions of dollars invested in their systems. They have technical debt. They have data silos. They don't have documents.

Somebody was telling me the other day that there are some old systems and, on contract, they have guys as old as me, 70, 75-year-old guys, because nobody else knows what the hell is going on. And then when there's a crisis to be sorted out, they're pulled in from Phoenix or Florida or wherever they are, and they have to solve the problem, and nobody else knows how to solve. So we have that kind of situation out there, undocumented dependencies. So taking brownfield systems and modernizing them is a hell of a lot more difficult than doing greenfield development. And a lot of us get biased, because all the guys who talk about productivity are talking about greenfield development. And therefore, getting these large enterprise organizations productivity going is very, very different from individual tasks. It's a lot more complicated.

Also, AI implementation requires laser focus. The very fact that you can generate stuff means you can generate slop. In fact, 5 years from now, there'll be more AI legacy system than any other legacy system and all kind of stuff will have been generated and we'll have to clean that up also. And if an organization is not -- you can have this fake productivity. Let's say there are 2 guys and they're having a fight. One guy will draft an e-mail, which will be one paragraph. He will give it to AI to make it into a 10-paragraph e-mail, because he wants to impress the other guy. The other guy will take the 10-paragraph e-mail and summarize it to 1 paragraph. So both have used AI, but what have we achieved? Nothing. So how do we make sure AI is used? And therefore, you need usage guidelines, you need quality gates, you need explainability. So how do you make sure that AI investments lead to real performance and productivity and not just some make-believe stuff. This is something which is very important.

So what still matters? First principle thinking. One of the things when we train people is they have to learn to do this without tools, because all of us learned to do this without tools. So when we got the tools, we knew how to use those tools better. But if you start by teaching them tools and everything is a black box, then it's like the guy who never knows how to calculate because he was born with a calculator. So first principle thinking is very important, all the more important as you think about strategic transformation of large enterprises. First principle thinking is very important.

Second, understanding enterprise context. Every company is different. Every company has a different legacy. Every company has different systems. Some of them have come from acquisition. Some have come because they have 5 business units, all buying their own version of technology. All kinds of reasons. Everybody has a complex estate of systems. And context is essential to being successful at AI deployment. And each context is different. And it's the dealing with these contexts that is the hard part, which is where, again, we believe we have a way of doing that.

I'll give you an example. The self-driving cars, the first DARPA challenge was 2004. The first time they rolled out was 2007. 20 years back. Then everybody said, "Oh yes, by next year, we'll have self-driving cars". It's 20 years later, all we have is a few cities in America where there are self-driving cars, because the context is different, every city is different, every road is different. And by the time they come to Bengaluru, it will be 2047, because dealing with Bengaluru traffic will be a different level of context. So enterprise context is so important, and that is something which cannot be done by a tool. It has to be done by capturing implicit knowledge and making it explicit.

Agnostic design. Again, what I mean here is, don't get locked into a tool, because that tool may no longer be -- it may be obsolete in 2 years. So how do you design for agnostic that you can choose any system. Getting the house in order, we talked about removing technical debt. We have to make the house in order for this whole thing. And then massive change management, you're changing organization, business sector, people. I mean, this is like unbelievable change management. So unless you have leaders who can do effective change, nothing is going to happen.

It's also about strong collaboration across firms. The firms have to -- because all the knowledge is implicit in the heads of different people, how do you make that explicit in one customer journey. Focus on productivity. It's not about using AI tools. It's about productivity out of those tools. Otherwise, you'll get false productivity, which leads to more complications. And then this is an engineering game. AI engineering is a whole way of doing things. And that is part of your change management and transition that you have to do. And that's a big thing.

So my view is there is no opportunity gap. If anything, the opportunity is bigger than ever before. So don't get distracted by that. You should still ask the question, what is the firm doing to take advantage of this? What is the firm doing to transform its talent for this new world? What is the firm doing to design the services and products for this new world? What are they doing to tell the customer in a way that it resonates? What are they doing to make sure that the front-end conversations with clients are done properly. These are all the issues. And I'm sure everybody will not execute the same way. So there is an execution risk in doing that. So it is not an opportunity risk, it's an execution risk. You get it? And therefore, the balance of assessment is how do we know that each firm has the execution plan ready to get to where they have to get? Are they able to do it well? Are they able to do it with speed? Are they able to do it with scale? Are they able to do it with new mindsets? That is really the question of the day that all of you need to ask.

So I'm hoping that today, you will hear from our team and it will give you some reassurance that we are on the right track. Thank you very much.

Thank you, Nandan. For our next session on The AI Services Opportunity, please welcome Salil Parekh, Chief Executive Officer and Managing Director, Infosys.

So good morning, and welcome. I think with that session from Nandan, I'm sure you have a lot of clarity and a vision of where the industry is going, where AI is going and what are the real issues that one needs to look at. I want to share, in the next few minutes, where we see the opportunity today in AI services and how we are planning to go after it. In fact, already how we are going after it, and give you examples of that.

So first, one of the things we've learned again and again is what we see from our clients is that our clients trust Infosys in driving and delivering AI work. And throughout the day, we want to share with you several client examples. Here are a few quotes, the first one from the CEO of a large telco, where we are doing extensive amount of AI work and how he sees the value that Infosys brings, another one from a COO, another one from a CIO. And these are the sorts of examples that drive how we have built our approach, how we are executing on the AI journey.

So today, we are doing AI work for 90% of our large 200 clients. So this is not something which is just here and there in pilots. In terms of the scale, it's across many things. It's small and large parts of large programs with large clients. What we have now done is introduced a way to look at what we are doing through an AI-first value framework. And this framework we are putting together in this Hexagon, which I will share in a few minutes in some detail what we are driving through with it.

We essentially see 6 large areas where there's growth opportunity for AI services. And I'll go through this in a little bit. We will also have each of our different leaders, from their different perspectives, give you specific examples in each area. First, AI strategy and engineering. This is really the area where we do a lot of strategic work. You will, in fact, see one of the client examples I shared where the CEO is engaging with us. There are several others we will share later. And you'll see some videos of this as well. So we are doing a lot more AI strategy work. Infosys is a lot more engaged at that level, because AI is central in that sense to all of those conversations. But the building of agents, the orchestrating of what the platforms are, what the agents are, which are agents which are built by Infosys, which are agents built by clients, which are agents built by third party, and how to make all of that come together.

Second is data for AI. Data is absolutely critical. As I'm sure most of you already have seen, each large enterprise is protecting its data. No one in the enterprise world, unlike in the consumer world, is sharing data broadly with the AI foundation models. Everyone is building their own data, and there's a lot of work to be done to make enterprise data ready for AI in this new era. The third is process where a lot of business process that exists today, whether it was technology enabled or whether it was not, is being driven by agents into new worlds. One of the biggest areas we see here, of course, is customer service and the customer service business case is driving huge change in how process is going to change with the AI world.

The next, again, you heard from Nandan, the legacy modernization piece. This is a massive, large opportunity that we are seeing. In addition to customer service, one of the largest opportunities, where we are essentially taking large legacy organizations. We'll actually share a couple of examples of this, of the work we are doing at scale and bringing them away from the legacy landscape into the modern landscape.

Physical AI is something quite new where AI software is embedded into devices, and that is becoming a growth area because everything will have AI built into it. And then AI trust, which is both about the trust and cyber, but it's also about responsible AI, which is something where Infosys is leading in making sure that things are built with a view to keep responsibility in mind in the scaling of IT systems. So these are the 6 new areas that we are seeing. This is a large opportunity set, and this is where we see a lot of the growth coming.

Now here are some examples of clients we are already working with. Throughout the day, in a little bit more depth, each of the leaders from Infosys will share 1 or 2 client examples. We will also have some videos to sort of have the client share, from their perspective, how Infosys has supported them in this AI journey. So what I'm showing you in the Hexagon in the AI value framework is not theoretical. This is things that are actually happening on the ground with Infosys. This is what we are executing. And this for us today represents 5.5% of our revenue in Q3, and it's growing at a robust pace. And this is something which is extremely dynamic. It is something that is working extremely well with our clients.

Now this at the high level of 6 big blocks is something that we have as a visual of Hexagon. But within the company, we then break it down to 30 offerings, and then those get broken down to 100 sub-offerings. And each of those are things that are being enabled with our engineers and with agents built on Topaz, which we will talk a little bit more about later on. And with partnerships, you saw one of the announcements this morning that we are working with each of the large AI players in very close coordination to make our clients more successful.

And all of this is the way we are now going to our clients. So each client discussion today is focused on the Hexagon plus the 30 plus the 100. And what is it that we can now work with you as a client executive to make it real for you the AI benefit, whether it's for revenue growth, whether it's for cost optimization, whether it's for innovation. So our entire go-to-market team, all of our segment leaders, all of our practice sales leadership are working with clients with this format to make sure that the AI becomes more and more embedded into the work that we're doing with clients.

And this is sort of pulling back a little bit. We've always talked about Navigate Your Next. This is how we are looking at the journey. The Navigate Your Next has changed, because technology changes, and this Next is about AI. It was different in the previous Navigate Your Next, but the Navigate Your Next concept, the client relevance remains the same. Where we are coming from today, the issues that Nandan shared, where we are going in the future, what the opportunities are, and what are our strengths. Our strength is absolutely clear the understanding of what the client landscape is.

There are some clients that we work with where we have probably as good understanding of their landscape as some of the client teams have. And this makes a huge difference in how we navigate through that through our AI toolkit. Our domain knowledge, our engineering talent, which, with our training, I've always believed is one of the best that there is, and the platform and IP that we have built, which again, we will highlight a little bit later today.

Now there is a dynamic in AI services, which all of you know and we understand. One, there's a huge opportunity. The one that I mentioned, the 6 areas with an external analysis, we understand that the opportunity is between $300 billion and $400 billion in the year getting to 2030. So over that time frame at that time in 2030. At the same time, we have several entities, have made estimates. We have our own views. The AI productivity leads to compression in IT services. However, today, we have a clear view that the opportunity is massive and large and that, that will become the driving force of what we will grow and drive through in the next coming years.

Now in putting all this together, we have created our own playbook, and this is essentially what we want to share with you in depth today in each segment of the day. Of course, my vision and objective is that we unlock all of the AI value for our clients, and we are absolutely on our path to drive that. There's one set of discussions on the new services, what we are calling AI first. So with our delivery leadership, with our segment leadership, we will share with you what it means, where we are doing it, what are the examples, what are the benefits.

Then we have AI augmented services, where we are taking all of our services and making sure that AI is infused into it to become even more relevant for clients. And again, our delivery leadership will share with you some examples of where that's working and how we are doing that. And then we have foundational components, our platform, our IP, what we built in Topaz Fabric, which we want to share with you in a little bit more detail. We have a set of agents that we've already built that are ready to deploy. We have things that we can drive with our clients to build their own platforms, so showcase that.

Our partnership ecosystem. This is extremely critical in this new era. And the partners are not only the partners that existed in the past. There are some new partners, both large and small, that are extremely relevant, and we already have a very strong ecosystem and the way to go to market with those partners. Our talent and culture, which we think is critical, and how we are reshaping it. We are going through a huge reskilling process. As you've seen from the announcements over the last several quarters, our approach has always been on reskilling and making sure that our team that we have builds up to the new, and we are recruiting.

We continue with our recruitment. We have recruited 20,000 college graduates this year and through March, that will be the number. And next financial year, we also have a plan to recruit 20,000 college graduates, but we want to talk about the talent and culture approach we have. And then on the brand, we have a leading brand in the market. Our brand is one of the fastest growing. And what are we doing to keep that or do even better in the brand in the AI world. That's how we are actually getting a lot more connects with the CEO client base, which is what you need to succeed in the AI world.

So that's our playbook, and we will showcase that to you throughout the day. With that, I will close, and I will pass it on to our delivery leadership team to go ahead with the rest of the presentations. We'll, of course, come back at the end of the day, Jayesh and I, to discuss your questions and give you some more views on where I see things are going. Thank you for that.

Thank you, Salil. For our next session on the AI Services Playbook, which is by 3 leaders, I would like to welcome Satish H.C., Chief Delivery Officer for the first part.

Let me set the context before we deep dive into our Infosys AI playbook. Every tech shift, whether it is PCs, Internet, cloud, digital, each one of them led to rewiring of enterprise work and workflows. And AI is the next rewrite. Here's a typical enterprise landscape. Sounds complex. This is one of the simpler ones. A typical enterprise will be far more complex because of the scale, because of the fragmentation, internal and external, the heterogeneity and the divergence of the operating model and the regulation with which it operates in, which is by design, by the way, and of course, technology debt.

So AI in enterprise is not just about low-hanging fruits like localized efficiency or user productivity. Integrating AI in an enterprise is not just a software upgrade or a plug-in. If it was that simple in such a huge complexity, no surprise that AI projects fail. Then what is it about? It's about harnessing the full potential. It's about reimagination of systems, processes and deeply embedded ways of working and rewiring legacy power structures. So Infosys has done this enterprise rewrite with each of the past tech shifts, and we are now doing the next enterprise rewrite with AI.

So let's look at how is the enterprise tech stack changing. Typically, it consists of the systems of record, which deliver deterministic, programmatic capabilities, which are codified, structured processes and enforce policies. And this delivers governance, accountability and compliance. We have systems of intelligence which facilitate engagement, collaboration, transactions, but usually, it is the humans who engage with data and the workflows. Above the enterprise stack lies a vast nondeterministic or non-programmed flows. These are unique, unstructured. They need novel problem solving. It needs experience, gut feel and is usually handled by humans. This is the layer which is underserved today, and this is ripe for AI-led transformation. So it's a myth that enterprises need just 2 layers, which is AI and data, it is enterprise and algorithm.

How should we harness AI then? AI is not the end game of tech transformations. It's just another one, but it's a giant leap in raw capability, and it's not system complete. So we need a multilayer transformational approach and purposeful orchestration to harness the potential of AI. This is why AI diffusion in an enterprise lacks the rate of AI adoption, and it needs time. So how is AI transforming the enterprise stack? What does this enterprise rewrite about? The core intelligence of humans plus machines will be seamlessly shared across the layers, so that every layer gets reinforced within the enterprise stack.

The systems of record need acceleration, so that the business and operational processes can become more efficient. The systems of intelligence needs a seamless integration of structured and unstructured data, so that intelligence can be wired into user journeys and business processes, transactions and decision-making. It is estimated that 60% of effort in an AI project goes into doing this. The models will come in later. And this requires deep industry knowledge and context of the enterprise.

Encoding intelligence and AI in the flows leads to more automation and autonomy. And this is leading to the development of a new layer within an enterprise stack, which is what we call as the systems of cognitive work within an enterprise. As an outcome, humans will shift from acting on data directly to a governance and oversight role on flows and decisions. All the new AI tools that keep coming at us at fast pace will get plugged into the systems of new cognitive work, and it will accelerate the reimagination of an enterprise or its flows and decisions. Infosys will unlock tech debt and complexity and harness the power of AI to be enterprise grade and bridge the evolution adoption gap and expand our addressable market.

So how do we monetize this? Our playbook reflects the structural changes necessary in our industry, so that we drive value at the intersection of intelligence, engineering and domain. With AI, capability is a commodity, because it's available to all. Sustainable mode for an enterprise can be created by deep integration in specialized workflows and unlocking unique organization knowledge and context. So every enterprise has got unique data processes, risks and complexity, and AI will not unlock uniformly across the enterprises because of this variance. So our client intimacy and deep understanding of our client will help us -- or context will help us mitigate this and unlock value and also drive culture and change.

So we have built an engineering approach in our delivery where we can codify enterprise context, which will help accelerating scaling of AI. And this also enables enterprises to retain and protect this unique enterprise context within their 4 walls of the enterprise, so that they can keep their competitive differentiation, and this is not diffused into the AI models. Our depth in engineering and frameworks on IP and patents will accelerate AI readiness and adoption with our Topaz Fabric and our specialized talent in the form of full stack and FDEs.

For a financial services client, they were looking for an AI partner. When we started talking to them, we realized that they have a very strong enterprise AI platform that they have built. But then what we realized was they had an adoption gap, and we pulled out our agent control framework, as we call it, which would address the quality of code that is being generated, which would address the AI slop, which led to a poor adoption within their organization. So now we are working with them on taking our framework and fortifying their enterprise AI platform, so that we can accelerate that journey.

We have embarked on a talent transformation journey to build an ambidextrous workforce, which is deep in engineering and creative in reimagining work and workflows from first principles. We see new opportunities with domain stack. We have over 25 years of industry-focused experience. And when core intelligence connects with agentic economy, the play of AI elevates from how work is done to new outcomes that are possible. So we are invested in building the domain stack powered by our depth in domain and knowledge of how to deeply integrate AI tools and plug-ins into the flow.

We have created strong differentiation in our services stack. AI is now integral to how we deliver every service. Our services stack is powered by Topaz Fabric. We now have an approach to productize and reimagine work and workflows that will lead to a human plus agent model. We're also seeing momentum with new deal archetypes, legacy modernization with reduced risk, higher predictability on cost and accelerated time line, large deals with integrated ops and tech and transformation wired in, organization transformation encompassing enterprise stack and people. This includes the AI-first DCC approach, which we have pioneered in the market. We have also elevated our play to take end-to-end accountability from strategy to actionable road map to execution and eventually outcomes. We have expertise in delivering both above the line, which is business value and below the line, which is efficiency. Infosys is best equipped to deliver enterprise AI ambition with the power of our client intimacy and our AI playbook.

A quick example. Here is a client, a CPG, who had an ambition of clocking about growing their revenue to $7 billion. They came to us to bridge their ambition and deliver an AI operating model, so that we'll have an actionable road map and execute to it with executive AI value office, along with managing risk, governance and assurance. We use our Infosys IP and build their unified data foundation. We build their enterprise Agentic AI platform with the requisite guardrails. This enables them to rapidly innovate and diffuse AI across their functions. Today, they have 10 Agentic AI products in the business across different functions from R&D, sales, marketing.

Above the line, with the agents that we developed in research and R&D for product formulation, they now have line of sight to $50 million revenue, which they didn't have before. Below the line, we've been able to unlock $25 million cost savings through just optimizing operational work. And then beyond this, we were also able to deliver 40% of business productivity improvement in functions like procurement and marketing. Thank you.

Thank you, Satish. For the next part of this session, I would like to invite Dinesh Rao, Chief Delivery Officer.

Thank you, Simran, and good morning, ladies and gentlemen. Thank you very much for sparing your time here today. As we navigate the landscape changes with respect to AI, I think our priority in the last 6 months to 1 year has been how do we accelerate our customers from experimentation to really looking at an AI scalable at industry level.

Now AI as a technology is as good as what it can really understand from orchestration across systems of record, which Satish alluded to, ability to really understand the complex business processes and navigate. And most importantly, how does it even get to understand the deep seated legacy systems that are there. And frankly, looking at all the complexities that we had with respect to some of the estates that we've been working as well as with the customers, we decided to codify our entire services across 6 strategic pillars. And these 6 strategic pillars are all integrated. In a way, a customer who wants to start the journey of AI adoption has to look at each one of them and see how does it -- and then our intent is to take this strategic pillar to walk them through this entire journey of scaling the AI.

Now let me start with the pillar #1, the AI strategy and engineering. Nandan alluded to it, so as Salil. Organizations are extremely complex. One needs to really look at the top down, looking at how do I really create an AI blueprint, a need of really setting up an AI transformation office. What would that mean? I need to first understand which business units, which business processes that I would be able to unlock the AI value. You can't really be spraying across the AI in multiple different business units. Now that is a very key thing because that's where the value realization framework of Infosys comes to bear to look at how do I map the process to the value that it actually arrives with.

Now the second key thing is how do I change the ways of working. Because you have so many models, so many platforms that have come by, one needs to really put together a very technology-centric AI platform with the models that it needs to go with, the governance that it has to happen and how do we make sure that we diffuse this particular platform across multiple layers of the organization, so that we have one standard way of really looking at how do I scale the AI. The third layer, obviously, is to really looking at the entire governance model that you need to put together. In a way, this AI has gone very strongly. The last one, obviously, is to really look at a purposeful selection of an AI infrastructure where you also need to continuously keep an eye on what would happen to my AIOps.

Very recently, we've been working with the CEO as well as the Board of Danske Bank, where we really started working with them to looking at how do I enable this bank towards the journey of being AI first and digital first. So we set up an AI office along with the Board, working along with the CEO to really put together a strategy all the way to engineering, augmented that with innovation labs as well as identification of core processes like KYC, the fraud detection, credit and whatnot. So in a way, the journey is just not that I would start doing software development, but it needs to have a top-down view of really setting up the strategy for an organization.

Now the second pillar, my friends, data is everything that AI needs. Today, organizations have multiple pools of data sitting. It is just not structured data. It is, in fact, even unstructured data, multiple modes in terms of videos, in terms of speeches and whatnot to an extent of about 60% to 80%. And today, the most of the time is spent on data in all our projects. Data is one which accelerates your AI journey or potentially could also decelerate your entire velocity of how you're going to do it. So our framework here today is to really look at help our customers try and harness the data, transform the data, bring them all under one uniform data fabric. And it just doesn't sit there. At the end of the day, data also have to drive intelligence. The intelligence can be driven only by connecting the semantics and the ontology on top of it. And that's a very elaborate process one needs to go through, because the processes are different by region, by business units, and it has been all codified in systems of records as well as in systems of experience. And that's a humongous job.

The third layer there is to really look at how do I govern the data, because the data fingerprinting is extremely critical as you really look at who would get the access of data, so that in some sense, there is a framework if you really look at. So in one of the large industrial manufacturers, there was 10 petabyte of data that we had to really bring in all together, harness it as well as create the semantic ontology today, help them actually drive the supply chain optimization by over 20% to 30%.

Now the third pillar, Nandan alluded to this, this is all of reimagining the entire business processes. Most of the large enterprises today have point-to-point solution. One need to really look at in the context of domain and reimagine the entire business processes. And these processes have to be reimagined with respect to how the human intuition works along with the AI and agents. And it is extremely critical that every workflow by persona has to be reimagined and has to be codified the way AI would actually come by. Now this also has to be contextual to the business and the regions where you really work by. You just can't take a sourcing and a procurement process and say that it is a domain that it could be applied to every industry. It has to really be contextualized to the industry and the business that you are really looking at. And most importantly, since it's going to change and touch every one of us, it has to also be looked at how do I operationalize the entire workflow, the technology and the change management, all put together, to really help realize the end-to-end value.

We've been now with Toyota Motors Europe working through a supply chain transformation process, where we took our industry asset of automobile on top of it, the entire agentic playbook, really looked at by persona of a buyer, a planner or a customer service agent and really double-clicked to look at what does this transformation really mean. And just to look at one critical process of drop ship, which is so critical for an automobile, is to really bring in agent and orchestration there to really take away all the manual work and bring in much better inventory visibility.

Now the fourth pillar, obviously, is modernization and everybody has talked about it. It's the Achilles heel of our large organizations. Today, there is so much of tech debt sitting there. The code is obsolete. There is no written documentations. There are no availability of SMEs today. And it's not that the customers did not really try to do the legacy modernization, but the ROI and the time it took never stacked up in the past technologies. So what AI models as well as powered by our Topaz Fabric today enables is to make sure that we transition some of these large legacy, both on the data as well as on process side, into the most modern cloud-based microservices architecture. And today, it does stack up, and you would hear one of the examples very soon.

Now physical AI is something we believe is at the cusp of really accelerating the AI journey. Whatever intelligence that we all thought and built as a part of the digital workflow is finally now moving towards the actual physical objects. And this, friends, helps the acceleration of AI in a lot of the products that we really look at. Some of the key cases that we really look at is -- and in terms of data first, the new product introduction, wherein the entire process would be reimagined as well as infused with AI, the products have to be defined or designed with AI in the front. And with more and more products with the software BOM being larger than actually the physical and the mechanical, we have a huge play in terms of embedding the AI as we look ahead.

The second case is the intelligence today, the real-time intelligence is moving from cloud to the edge. Now this will help accelerate the decision-making at the edge, which means vehicles, the industry operations, running infrastructure, all of this would actually increase the advancement and usage of AI. And lastly, the autonomous systems today, the prevalence in a lot of industries as well as areas is continuously keeping on increasing. Towards that, we see that we accelerated the journey of actually infusing the AI in the physical.

And here, I also want to draw your attention to the 2 acquisitions that we did, one InSemi, which meant the silicon design as well as validation. The other one in-tech, on the automobile, directly fits exactly into this particular pillar where it would help us bring more context as well as acceleration in terms of enabling the physical AI. The last, ladies and gentlemen, is not the least and the most important is the trust and the governance.

If I today ask everybody here, who has used the AI? I'm sure that all of you would raise your hand, but how many of you really trust the output that came by. I'm not sure whether everybody would raise their hand, because there are hallucinations, there are model breaches, and there are also governance issues with respect to the new AI Act and et cetera, coming in. So in a way, the trust has to permeate through all the other 5 layers for us to really make sure that we have the output that comes in an enterprise, which is trustworthy. To me, the trustworthy AI in every enterprise would be a huge differentiator. So we want to build the trust to our customers, and we want to monetize the trust for our customers.

Now having looked at all these 6 important strategic pillars, right, I just want to dwell on one of the cases, Nova Chemicals. They are a large petrochemical manufacturer based out of Canada and U.S., and it's very asset intensive. As you know, the industrial operations is extremely complex. If an asset goes down, they would have an impact on the top line and the bottom line. In the current context, most of what they were doing with respect to maintenance was all manual, logs and et cetera. So we were invited to a program in smart maintenance, where we actually brought in the data across their machinery, their OEM manuals, their maintenance manual, the historical data, the log data and et cetera, to help a planner to really, with a simple NLP on a chatbot would be able to guide them on what part of the industrial operations have to really go through a maintenance.

And most importantly, we were also able to actually bring in orchestration with agent AI, where the OT systems and the IT systems come together. So seamlessly, we were able to really move towards actually creating the entire work order process, the planning process, which actually moves over from OT systems to the SAP or the ERP that we have. And we see the impact of bringing huge planning efficiency, asset utilization and et cetera. Of course, here, we partner with Microsoft, and we used all the stack of the entire Azure to really make it come to life.

The last case I want to really dwell is about Hertz. I'm sure all of you know it's a very large mobility organization where we are today, as we speak, embarking on really modernizing their entire reservation, their fleet management, their pricing and the whole thing, which today is approximately 3 million lines of code actually sitting on a tandem computer. And I would like to play the video, let's hear from the customer on what their experience has been and what we have done with respect to this journey.

[Presentation]

So the important point to note is, models are there, I think workflows are there, but our context of Hertz in terms of what their processes are, how the code has been written, how the existing architecture is and what is the new modular architecture that we need to really help them migrate to is the context that this iLEAD brings to bear. And that is very critical as we really look at this entire legacy modernization.

So that, ladies and gentlemen, summarizes the 6 value pools that we are talking about, and thank you so much.

Thank you so much, Dinesh. For the last part of this session, I would like to invite Balakrishna D.R., Head of Global Services.

Thank you, Simran. So my colleagues, Dinesh and Satish, talked about AI-first services, which is new value pool that is being created out of AI. What I'm going to be talking about is AI augmented services. What we mean by that is taking our traditional services and using AI in that, and we want to be a leader in this space as well, and I will talk about how we are doing that.

So we have taken each of our services that we actually traditionally provide, whether it is application development, testing, modernization, migration, engineering services, business operations. So 20-plus services that we actually provide. And we have created detailed playbooks of how we can use AI in transforming the way we deliver these services. When we are doing this, we are partnering with the best of the technology that is out there. We are working with models, leading models from Anthropic, from OpenAI, from Gemini, from Amazon Nova. And in fact, we are also working with open source models, right? Open source models like DeepSeek, LLaMA, and we have even created our own coding model in this space, perhaps the only GSI that has actually created a coding model. So we use a combination of these models in our engagements.

So in the Hertz example that you actually saw, we, in fact, used 2 models. We used a cloud model that actually generates the code. And one of the things about LLMs are they are better in critiquing output than generating output. So we used an OpenAI model to critique that output, and that is how we actually improved the accuracy.

So one is the models. The second is the tools. And in the tools, we are working again with the leading tools. GitHub Copilot was the first, and it had almost 100% of the market share. Two years back, we set up a GitHub COE that was inaugurated by the CEO of GitHub. And then we are still ranked the #1 GSI in terms of GitHub adoption. Just a few months back, we got this award as the leading GSI working on GitHub. But just not GitHub, we are working with Anthropic, we are working with Gemini. We are working on the models from Anthropic CLI. We are working on the new age models, right, whether Devin from Cognition or also, right, we are working with Cursor.ai that you would have recently seen. So we are working with the leading models. We are working with the leading tools.

But then, again, as my colleagues also talked about, a lot of these models don't understand the enterprise context. They don't understand the standards that are there in the enterprise. They don't know other libraries that are there, other programs that are there. So we have to do a lot to actually bring that context into the tools that we are actually using, right? So we do that by creating MCP registries. We create a knowledge graph of the enterprise context and we combine that. In the recent release that we just did with Anthropic, you hear Dario talking about that. They need Infosys to bring the enterprise context onto the models, and that is what we actually do.

In addition to that, we have actually created agents specifically for each kind of services. So in application development, we have taken the life cycle and said we need agents for requirements, design, architecture, et cetera. And we have created 100 such agents that we are using in each of our services. In addition to that, we have to create other tools, right? You saw in the Hertz example, the LLM models can't digest huge pieces of code at one time, right? Some of these enterprises that we work with have millions of lines of code. If you give that to the LLM, they start to hallucinate. So you have to chunk the code, you have to create graphs, call graphs on how these are actually associated, and that's when you get better output from LLM. So we have created all of these assets that are part of our Topaz Fabric, which my colleague, Rafee will actually talk about in more detail in the next section.

In spite of doing all this, we need talent, right? And sometimes people ask me, if LLMs are generating code, why do you need people? Why do you need developers anymore, right? And I think they asked the same question to Boris Charney from Anthropic, because Anthropic is continuing to hire developers. So somebody on X asked him, why does Anthropic -- right, if Claude Code can actually generate code, why are you still hiring software developers? And his response was that engineering is changing, but great engineers are a requirement still and in fact, the most important requirement going ahead. And that is something that we also actually believe, right?

The way that we actually deliver code or the way we support applications may change, but still you need great talent. And so what we are doing is to take each of our developers and training them on AI. So we have 90% of our developers that have been trained on AI. It will never become 100% since we are always hiring new people into the stream. But our intent is to actually have everybody be able to use AI in their daily work.

In addition, we need specialized roles, right, forward deployment engineers that will create the platforms that the teams will actually use. And then we have created COEs for each of the partnerships that we have. So it is a combination of all of these that actually helps us deliver our AI-induced services. It is the blueprints. It is the technology, our own technology plus the leading technology that is out there and the people that we actually create. The way we are going to market is also, as you saw in the Hertz example, it is not about PPTs anymore, it is about actual demos, and that is what we see creates the impact, and that's how we actually go to market in all of our large deals.

I will talk about a couple of examples of how we are using it in actual programs that we are executing, right? What better example than Microsoft, who is in the leading edge of this kind of technology adoption, creating the technologies and also adopting this technology. So in Microsoft, we have a 360-degrees partnership. What we mean by that is that we go to market with Microsoft. We are one of the big customers of Microsoft. Microsoft is our customer. We provided services to Microsoft. And we do multiple engagements with them, but I'll give you a couple of examples of what we are doing.

Microsoft themselves are going through a big transformation. From enterprise agreements, they're going to what they call MCAs, master customer agreements. What this means is that through the master customer agreement, they want to eliminate all the paperwork that they had to deal with in the enterprise agreement. They also are talking about evergreening the licenses. So enterprise agreements had only 2 years time frame. This is perpetual agreement that you can use for multiple years. Enterprise agreements had a minimum seat count of 250. This actually has no minimum seat count. In addition, in MCAs, you are able to monitor your usage, adapt your usage, you're billed based on your usage, you get a very flexible billing. So multiple advantages for the customers of Microsoft by using this agreement.

And also for Microsoft itself, it actually eliminates -- because you are not having papers and documents anymore, it eliminates and accelerates the way they go to market and also the operations that they have, right? On this engagement, they had to build the IT system to manage all of this. So Infosys is actually working with them to build that. We used all the technologies that I actually talked about, and we are getting 2x developer velocity and 35% improvement in the time to market.

The other engagement that we are working with Microsoft is on their Intelligent Cloud, right? So as you know, this includes Azure and Microsoft Office. They carry a lot of mission-critical systems of Microsoft customers on these clouds, right? And it is important for Microsoft that for these mission-critical applications that there is no downtime and then it is actually trustworthy, right? So Infosys is again providing support for Microsoft on this. And the way that we have used AI is that AI agents today monitor the logs and predict issues before they actually happen. And they give all of this intelligence, which we call triaging, and then we route it to a specific support engineer with the information, so that they can actually work on it before the issue actually happens. So this is for both reactive and proactive issues. And so you can see that we get 40% improvement in the incident response and 10x improvement in the RCA turnaround.

So there are several such examples, right? The other example that I have here is Danske. Danske has a Forward '28 strategy where they're looking at modernizing their entire landscape. They want to bring process efficiency and they want to completely create it as a digital bank. So you must have seen the press release where they've chosen Infosys for this transformation, and we are helping them on the AI strategy and transformation as well. And we are doing everything from AI strategy to implementation. We have set up an innovation lab for them, and we are creating multiple AI solution work streams.

So we are using Agentic AI in the code development, more than 2 million lines of code that we have generated. But then again, these lines of code that we generate has to be validated, and that's what our engineers have been trained to actually do. And 97% of the engineers are using that. In addition, we have created multiple AI solutions. They wanted to use ChatGPT, but they wanted the guardrails. So we created enterprise ChatGPT, which has over 16,000 users. They created other solutions on risk and HR, which have been quite successful. We'll hear from the customer itself. If we can play the video.

[Presentation]

With this, I'll hand it back to Simran.

Thank you so much, Bali. For our next session on Infosys Topaz Fabric & AI Next - AI Platform Suite, please welcome Rafee Tarafdar, our Chief Technology Officer.

Over the next 10 minutes, I'll cover how we are going to power AI-first services and AI augmented services using our IP and platforms. Now earlier during the day, we heard about the complexity with enterprise landscapes. And when I think about enterprise landscapes, I think about city maps. Every city is different. The map for each of these cities are very different. Now if I bring any AI model, any tool, any platform, the only way to accelerate is by creating runways within an enterprise that can help us accelerate AI adoption from pilots to hundreds of projects, and that's where Infosys Topaz comes in.

And we do it in 5 different ways. First, we have created a rapid experimentation and innovation infrastructure where our teams working with our clients evaluate the latest developments that are happening in the AI space. They look at all the noise that is happening and identify tech that is relevant. They then build proof of values that are very relevant for their business and then they demonstrate the art of possible in a very, very rapid manner. And today, there are about 39 such innovation labs that we are running with our clients across the globe.

Second, we take a very value-centric approach in how we look at the end-to-end process, because over the last few years, we have realized that use cases cannot deliver significant value. And this is where we are bringing the 25-plus industry blueprints we have in order to come with already reimagined business and IT workflows that we can use with our clients to accelerate. So today, when our consulting teams, what they do is they sit with our clients, they understand the problems. Then they use the product discovery and vibing tool from our Topaz fabric to very quickly identify good solutions, build a prototype, and then using exponential engineering, they actually create a production scale application by end of the day. And then using this, they're able to demonstrate how we can reimagine the complete workflow.

The third, Nandan talked about creating an architecture that is very evolvable. Now what we have done is, the way we have designed our IP and platforms is to make sure that we give optionality to our clients. They can pick any model they want. They can pick any agent framework they want. They can run on any AI platform. They can run on any AI cloud, and we can integrate with any AI native tool that they have partnered with. And today, in most of our production deployments, we have a number of varieties that today we are already supporting.

The fourth runway is to build that enterprise context. Now here, we are doing 2 things. One, based on the work that we are already doing with most of our clients, we have built an enterprise context. Think of it like a map. Whenever I want to navigate in a city, you need a map which tells you how to go faster. So we have built this enterprise context or map that tells me how the systems work, what the infrastructure looks like, where the apps are running, where the data resides, and how they all connect. And on top of it, we are building an industry context. The industry context tells us what happens within a retail, within a bank, within a CPG context. And these are the models that we are bringing out of the box through a graph technology, and we are building these enterprise twins. And this is what will enable us to accelerate.

Eventually, in most enterprises, to drive projects at scale, they need multispeed IT governance projects, so that they can onboard these AI tools at speed. They need to put these guardrails, and that's why we are building a lot of tooling that enables them to deliver these AI solutions in a very trusted manner. And all of this comes through Infosys Topaz. Now in the IP and platforms that we have been building at Infosys, we have always kept our customer needs in mind. So if a customer comes and says, look, I want an end-to-end vertically integrated AI and agentic platform, then we use AI Next as a platform to accelerate value. Or if the customer says, look, I've already made some investments, I want a composable modular agentic and AI platform which can help accelerate my own AI journey at speed, then we essentially bring the Infosys Topaz Fabric. So with the combination of these, we are able to meet most of the demands of what our enterprise customers have.

Now let me talk about Topaz Fabric itself because over the last few months, we are starting to integrate all the different IP that we have at Infosys into one common way through which we can deliver our services. Now Topaz Fabric enables 5 key capabilities. The first is this builds on our customers' existing investments. So this is not about replacing what they have. So this works above their model layer, above their platforms, and about their enterprise systems. And Fabric can integrate with any model, any framework, anything that they have. So that's the abstraction that we have already built within this.

Second, it provides close to 600 agents, which have been purpose-built for different AI-first services, AI augmented services and also for industry-specific flows. So this is something that we bring out of the box to accelerate the journey for our customers. Third, what we have also done is, we said we'll create out-of-box integration. So we have out-of-box integration with most of the coding tools. We have out-of-box integration with different models. We have out-of-box integration with business platforms like SAP, Oracle, Salesforce. We have out-of-box integration with data platforms like Snowflake and Databricks and with enterprise platforms with ServiceNow.

Now what this enables is it enables us to deliver value to our customers quickly. Now in all of these, it is also about bringing the enterprise context and hybrid intelligence. So the way we are doing is we are starting to build a number of different ontologies and models that comes prepackaged as part of our Topaz Fabric, and that's something that we bring out of the box. And as we deploy it, we learn from the data, we learn from the processes. And this is how we create a closed feedback loop where the context keeps improving as it gets used over a period of time.

Now a lot of our clients also want to use a lot more predictability in the way AI is deployed. This is where we bring a lot of deterministic rules, couple it with AI models, and we also bring our own small language models in order to create a right value proposition from cost as well as from a time-to-market standpoint. Now all of these is backed by a lot of deep research and patents that we have filed over the years.

Now while we are doing a lot of innovation internally inside within Infosys, we also acknowledge that there is a lot of innovation happening outside. So we are working with AI native partners in 3 different ways. One, if they have a platform that is really good at doing something, then we are leveraging it for the tasks that are relevant to enterprise. For example, Nandan talked about brownfield. So our Cognition partnership is largely to use Devin for a lot of brownfield engineering, because we find that, that is really good at it. Second, we are building embedded agents that can work within our partner tooling. So today, we have built agents in Fabric that can run within Claude Code, that can run within GitHub Copilot, that can run within ServiceNow. So whichever platform the client has, these agents work within that environment. And third, we have integrated with their tooling, so that we can cover the end-to-end value chain that is required to accelerate the journey.

The next is also we are focused on where the industry is heading on AI, and this is where we are working with universities to do joint research. We do today on agentic technology, on also scaling, and on trust with Cambridge, with Columbia and Cornell. And we are also doing this a lot more with the research centers that we have set within Infosys. This is to make sure that we continue to build on what will come next.

Now let me bring all of this to life with an example where for one of our logistics client, they were finding that the customers were able to process the orders and bookings in a lot more accelerated manner, and this was creating an issue for them. And they said, we want to be able to process these customer case services in a much more accelerated manner. This is where we took AI Next as a platform, because they had already tried with multiple platforms and they didn't work. And we said, we'll use AI Next first to uncover the existing knowledge, because they had rules that are very specific to each customer. So we pulled out close to about 8,000 different rules that exist there.

The second innovation that we brought here is that we automated the entire workflow. So when we started, the extent of automation was about 0% to 10%. We took them to about 70% automation in their entire workflow. What this meant is the turnaround time reduced from 24 hours to about 30 minutes. The next is they also were very concerned with the sovereignty of the stack. So what we did in this case is we used the Mistral and Pixtral models to make sure that it addresses the sovereignty needs that they had. And this today supports orders or bookings from 116 different countries, and it supports 15 different languages. That's the power of what this could do.

And eventually, as we started scaling, cost became an important driver. So we had to bring in a lot of optimizations to reduce the cost significantly for that customer. And this is something that we did over the last 1 year, and today, this is live. Now you can see a lot of these IP platforms as you come to our living labs, and I encourage all of you to please spend some time and experience these technologies that we are talking about. Thank you very much.

Thank you, Rafee. Now for our next session on Unlocking AI Value in Communication, Media and Technology, please welcome Anand Swaminathan, Segment Head, Communications, Media and Technology.

So let me share a few things in the next 10 minutes, particularly around what is driving AI demand in the communications, media and the tech business. And what is the value that we are seeing when we work with our clients on AI. And I'll also give you one concrete example where we have delivered AI at scale. AI is no more an experimentation with many of the telecom, media and the tech companies. They are looking at making AI a core operating model on which they want to drive customer experience, engineering and network resilience, as well as operational efficiency. So the communications, media and the tech business spans across the semiconductor companies, the OEM platforms, to the hyperscalers and the media and entertainment companies. There are 6 defining themes that are driving the demand for AI.

First is if you look at the telecom companies, they are facing a huge growth challenge. There are only so many consumers to buy mobiles and each consumer can only buy so many mobiles. Then if you look at the B2B business, which has traditionally been a challenge for the telecom companies, it's not growing at a good rate for them. So with the B2B and B2C growth issues, AI is giving them a breather.

Now companies are reimagining their customer journeys using AI. And on the B2B, they are rethinking how should they go to market. In one particular case, we have done a joint venture with an Australian company called Telstra, where we own the majority stake and we will jointly be responsible for taking the B2B nonconnectivity solutions to the Australian market. And we are engaged with a variety of our telco clients doing a lot of B2B and B2C work. And sovereign cloud is a big opportunity for the telecom companies. Now outside of U.S., every country is really looking at telecom companies to provide for the AI infrastructure, to provide for data residency, to provide for cyber resilience and to be able to operate, within the country, the required AI apparatus to keep the businesses going. So that's a big opportunity.

Third one is around the productivity expectations. They have to bring down their unit costs. And the huge challenge for them is the traditional productivity factors are not enough. So they are looking at step change in productivity improvements. And again, here, AI is a huge factor. On the other side, if you look at the tech and the media side, we are all seeing the huge spending surge that's going on with AI in terms of expanding the AI farm. But the issue has been that most of the AI is actually sold within the tech companies in terms of model building, model training and is not really getting diffused to other verticals or other industries. So the opportunity for Infosys is actually to bring our domain knowledge across the different industries and really work with the tech companies and make sure that we are able to take the products and services and actually do the implementations. So this is one reason why many of the tech companies want to work with Infosys because of our native understanding of many of these industries.

And finally, there is a huge race across the tech companies towards gaining AI market share, and that is opening up a lot of opportunities for us in terms of working with them on the engineering spend as well as in enabling them in terms of creating new channels, either on the sales or on the partner side. To participate in the AI opportunity, 2 things are very important. One is trust with the clients and second is the scale. So if you look at the telecom, media and the tech business today, it is a very concentrated segment where there are very few big companies and then a long tail of small companies. So we have deliberately developed a long-standing relationship with some of the leaders in this industry. And that's evidenced by the fact that almost 60% plus of our revenues come from the top 15 clients.

Now what it means is these are the clients with whom we have the level of trust and advocacy to work with them on their AI road map. And with each of these clients, we actually are engaged in one or more of these opportunities today. So where we see, again, AI getting deployed and value getting created, 3 broad areas. First is customer experience. Now Nandan touched upon it, talking about customer reimagination of processes. It starts with that, whether it's a B2B or a B2C. And how do we rethink the process in an agentic world and how do we improve the customer satisfaction and customer retention. So that's a big opportunity.

But along with that, it's not as simple as that because you have a lot of legacy tech in many of these companies. Many of these tech gear there is end of life or end of support. So there is a big question about, are we going to buy new platforms? Or are we going to just build the platforms? And the obvious answer now seems to be going towards building platforms in an agentic AI framework. And that gives companies like us a huge opportunity. And we are seeing an additional improvement or an incremental of about 30% on the Net Promoter Score in many cases.

So when it comes to network resilience or engineering reliability, so we have a solution framework called Infosys Smart Network Assurance, which is today part of the Topaz suite of products. Using this, working across many telcos globally, we have been able to improve the network resilience and bring down outages significantly. Now as far as the operations are concerned, it's about really applying Agentic AI in a way where we are working on a human plus agent model to drive the unit economics and be more efficient for our customers.

So let me talk about one particular example where we have really scaled AI across a large enterprise. So Liberty Global is a leading broadband and mobile -- fixed/mobile broadband communications company based in Europe. They operate across many European countries and with about 10 million subscribers subscribing to their entertainment and connectivity platform. Infosys today owns and operates the entire stack of hardware, software and services for Liberty Global. And this engagement is built on a per subscriber basis. The fee is based on per subscriber. So as the subscriber count changes, Infosys fee also changes. So what we have been able to do in a situation like this is using the Agentic AI framework, unlock value in the software stack, which is something that traditionally has not been done by many of the service companies.

So when we took over this undertaking of completely owning a 10 million subscriber platform, which is a highly critical platform, the big question was how are we going to deal with hardware and software, but that is what is giving us the biggest opportunity to unlock savings today. Now also applying a very unified Agentic AI thinking for the entire platform, we have been able to improve customer experience. In one case, for example, where if you imagine a customer at home who has an option to use an Apple remote or some other device to interact with the TV, we are giving better features or richer features using the entertainment platform at Liberty through our Agentic AI framework, where through a natural language, the subscriber can speak to the television and get the shows he wants instead of doing a search with a clunky device. Now this improves engagement of the subscriber to Liberty as a brand as against going via some other brand.

Similarly, we have improved network resilience in this company, and you can see the metrics out there and as well as many of the other important critical elements like improving their own employee experience by bringing Agentic AI.

Now let me actually let the CEO of this company speak to you directly about his own experience in working with Infosys. Can we roll the video, please?

[Presentation]

Thank you, Anand. For our next session on Unlocking AI Value in Manufacturing, please welcome Jasmeet Singh, Segment Head, Manufacturing.

Well, hello, everyone. I'm delighted to share with you today what we see is happening in manufacturing on AI and how are we capitalizing on this opportunity. Leading manufacturers are leveraging AI, embedding it into their product, embedding it into their workflows. They are driving agentic execution to unlock value. In fact, in our recently published manufacturing tech index, 75% of the manufacturers embed AI into their enterprise strategy.

Now we see 3 big areas of opportunity for us. Number one, everything is getting connected. And what that means is it's driving investments into smarter products, smarter operations and as-a-service models. Now it has been talked about before, but the industry has got a rigid tech stack. That is leading to and driving AI-led modernization. That's opportunity number two. Now AI lives on data. And manufacturers have a treasure trove of data. They have it in the smarter products across operations. And so that is opportunity #3.

Now as we look at the manufacturing value chain from design to service, we are obviously seeing a huge amount of applicability of AI. But let me talk about the make part of AI. Now it makes sense that I talk about this because this has the potential to drive operational performance improvements and agility. So as an example, for a leading industrial manufacturer, we are leveraging computer vision and AI to assess product quality in their manufacturing operations. This is driving a 10% increase in throughput. Now it's not only across the value chain. We see now that we are able to solve much more complex problems leveraging AI, and we are unlocking a lot more value. And this is cutting across also the horizontal areas like finance, HR and legal.

Now let me make it real with a couple of examples. This is a mission-critical process at Rolls-Royce. You know Rolls-Royce manufactures and sells aircraft engines on a power-by-the-hour basis. Engines require maintenance. They need to come into the shop for overhaul, for maintenance, and they come to the Rolls-Royce MRO facilities for that. Every time an engine comes, it means that aircraft or the airlines could be facing an aircraft on-ground situation and Rolls-Royce could be losing revenues. So you can understand that the imperative is to try and get the engine back on wing and not idle as quickly as possible.

The process in question is the reviewing and authoring of the repair procedures of every engine that comes in. Now each engine is unique because it has its own unique operating parameters. The multi-agentic solution that we have developed for Rolls-Royce is delivering significant benefits, a 40% reduction in engineering effort. First-time right rates are increasing from under 40% to 75%. And because we are able to accelerate the entire process, it is providing a multimillion pound revenue uplift for Rolls-Royce.

In the words of Declan, as you can see, Infosys has successfully operationalized the Agentic AI solution. It is an approved EASA, which is the regulator. Remember, this process is manual. It's highly regulated and safety first. It is an EASA approved European Union Aviation Safety Agency approved solution. And that means we can now scale it across Rolls-Royce. The second example is on GE Vernova. It has been referenced before. Now GE Vernova is a $40 billion in revenues company. It's a leader in power, wind and electrification. They are at the forefront of the energy transition, and their aim is to electrify the world while simultaneously decarbonizing it. They selected us as the AI strategy partner for them. This is from strategy all the way to execution.

The reason why they selected us was because of what they saw we were doing internally to become an AI-first company. We are able to bring together not only the AI expertise, but the knowledge that we have in product engineering, in business process as well as in IT seamlessly to deliver this significant transformation at scale. We have already delivered over 25-plus agents, multi-agent use cases for GE Vernova in production.

Now let's hear directly from the CEO, Scott Strazik, and Justin John, who is their AI leader. Can you please play the video?

[Presentation]

Now what a phenomenal message. We are delighted to be a partner to GE Vernova on this exciting journey. I want to leave you with 3 key takeaways from manufacturing. Number one, the AI opportunity for manufacturing is massive, and we are already delivering value at scale. Number two, we have the depth and breadth not only in AI expertise, but the knowledge in product engineering, in business process as well as IT to again drive this transformation. And lastly, as you heard in the video, we have the capabilities to drive this from AI strategy to scaled execution. Thank you.

Thank you, Jasmeet. Before we get to our next session, which will be followed by lunch, I would like to inform everyone that after lunch, we will be heading to the Infosys Living Labs for a walk-through on our enterprise AI in action. For our next session on Unlocking AI Value in Financial Services, please welcome Dennis Gada, Segment Head, Banking and Financial Services.

Hello, everyone. First of all, I have to say I really feel at home talking about the impact of AI in financial services to an audience which is largely full of people who come from the financial services industry and understand some of the nuances and challenges. What we see in the industry today is that financial services is really at the forefront in terms of adopting and scaling with AI. And this is different, right, from some of the previous tech shifts, for example, cloud or even digitization, where there was a little bit of lag effect or catch-up for the financial services industry. But this is different.

Financial services firms, whether it's banks, asset and wealth managers, custodians, card providers are really leaning in and leading with AI. And I think the reason for that is that this is one technology and business shift that firms see, which can simultaneously bend the cost curve as well as the growth curve and also help in managing risk and compliance, which is, of course, very important in this industry. So this has a lot of conviction with the CXOs. As you can see, many of the quotes from the CEOs around using AI for augmented intelligence, using AI not just for efficiency, but really driving large-scale transformation within the bank and looking beyond productivity to growth.

So the good news for us with all of this is what we see is a significant increase in spend towards AI initiatives. And we are well positioned to benefit from that, both in terms of the AI-first services as well as the AI augmented services that we talked about. But it also does come with some of the constraints and challenges, right? It is not a technology or a use case challenge, but more around regulations, data privacy and most importantly, change management and adoption, which is where we see a huge opportunity to continue to expand. In fact, one of the CIOs of a large banking organization we spoke to talked a similar concept to the deployment gap that Nandan mentioned. Even if AI technology were to stop evolving today, there is still so much to be done for financial services firms to benefit from and leverage what's already there.

We also see a diffusion of AI use cases across all the subverticals, right? We are working, for example, significantly on fraud prevention in the payment space, in the consumer banking space. And already, there was a lot of work done on machine learning models in the past, but AI provides a lot more capabilities to take it to the next level. Similarly, there's a lot of work on customer experience through contact centers, through UI/UX, but also beyond that, right? For many relationship managers in commercial banking or advisers in asset and wealth management or financial analysts like many of you in the room today, AI provides much more of data and insights and helps with the productivity, so that these relationship managers and advisers can spend more time with their end clients.

We also think that agentic commerce and payments will take off significantly. It's still at the starting point, and that will result in a lot of unlock of new business opportunities for financial services clients. All of this is, of course, on the foundation of AI-based software engineering, AI-based process orchestration and data transformation that we spoke about earlier today.

So I'll talk about one of our flagship client examples in financial services, Citizens Bank. It's a top 15 bank in the U.S. and has grown significantly over the last several years, both organically and through acquisitions. And they have just embarked upon a program called Reimagine the Bank, where the main objective is to use the power of AI to significantly grow and expand the services that the bank provides as well as drive efficiency.

Infosys has been selected as the strategic partner to help the bank in this Reimagine the Bank initiative. In fact, just a couple of weeks back, we opened an AI innovation hub dedicated to support Citizens Bank in this initiative right here in Bengaluru. And this has been an ongoing journey. We've helped Citizens Bank move 100% to the cloud, one of the few financial services institutions in the world that has achieved that. We've already built some industry-leading platforms on the cloud. And then with this foundation now, we are helping them accelerate the AI journey.

Using our Topaz Fabric suite of agents, we are helping them build their own Agentic AI and GenAI platform, which will help across the bank to deploy several use cases. Some of them are already in production. For example, we see a 44% reduction in calls to the contact center generated from the mobile app. And more broadly, the bank has talked about a $450 million cost run rate reduction target as part of this Reimagine the Bank program. This is not just about cost efficiency, but this shows the power of AI to drive structural transformation in a leading bank like Citizens. I would like to play a short video to talk about the journey at Citizens Bank.

[Presentation]

So that's an example of a first-of-its-kind innovation hub right here Bengaluru for Citizens Bank dedicated to support their Reimagine the Bank program.

Now beyond Citizens, right, if you look at the financial services industry, as you know, it's the largest segment for us at Infosys. And we work with organizations across the spectrum, right, from the large global banks to the regional banks, to card providers, asset and wealth management firms and so on. And we are seeing a huge amount of increase in work that we do with them on AI. In fact, 15 of the top 25 financial services clients have selected us as their strategic partner. We work with all of them, but for 15 of them, we are specifically been selected as a strategic partner for AI services.

If I take a couple of other quick examples, for our top 3 card providers, we've been working with them on the modernization journey for their core cards platform, right? This is 40 million lines of code written over the last several decades, and we are using AI to do this modernization. With that, we are seeing a 50% reduction in the time taken to do the modernization and significant efficiency benefits. The beauty of this is, with the success of this program, this particular client now wants us to do 2, 3 more of these modernizations, which were almost impossible to do in the past, right? So it just shows how much velocity this creates based on success of delivery on some of these programs. Similarly, for one of the large global wealth management firms, we are helping them build the Agentic AI platform. support a lot of initiatives for the financial advisers to get better data insights, higher productivity, so they can focus on their end clients.

In summary, financial services industry, as all of you know very well, is very complex. There's a lot of legacy. There's a lot of regulatory oversight, but has also always faced a bit of a growth and a cost challenge. And I think AI is a catalyst that can really help accelerate some of those mitigations and drive the organizations forward. At Infosys, we have deep expertise in the industry vertical. It's our largest segment. We have strong capabilities that we talked about earlier today.

And also, most importantly, we have the depth of the relationships, right? Many of these organizations, we've been working for more than a decade, and that gives us a lot of institutional knowledge and context, which we can use to help them on the AI journey. We really see this as a huge opportunity to bring the hybrid intelligence, human plus AI, and help these organizations become truly AI-powered and pivot to a completely new operating model for the future. There's a lot of work to be done. We are excited. We are just getting started, and we think we will be super successful. Thank you.

Thank you, Dennis. Before we proceed for lunch, everyone, a few important announcements. For departures in the evening, like I said, we'll have coaches to the airport at 4:45 and 5 p.m. If anyone needs an airport transfer earlier than that, please inform the help desk outside in the lobby. As you finish lunch in the next 30 to 35 minutes, we will walk down to the Infosys Living Labs or take buggies, which is right next to this building and to see enterprise AI in action.

On your registration badge, you will find a number that indicates your group for the Living Labs tour. Group volunteers will be arriving here by 1:25 p.m. Request you to join the volunteers and proceed towards the Living Labs in Building 45, where you will collect your headsets and will be briefed by your group leaders for an immersive experience. Kindly access lifts to the right side of the banquet hall when you exit for the Living Labs tour. I now request everyone to proceed for lunch on my left and straight back outside this room. For people who have specifically requested for Jain food, you will find it at the counters on my right side of the hall. Thank you. See you after lunch.

[Break]

Welcome back, everyone. We hope that you had an insightful visit to the Living Labs and so all of our value pillars in action.

Now for our next session, on unlocking AI value in energy, utilities, resources and services. Please welcome Ashiss Kumar Dash, Segment Head Energy, Utilities, Resources and Services.

Hello. Hello, and good afternoon. I hope you had a good session in the Living Labs. And you could see some of the things in action. Now over the next 10 minutes, I'm going to talk about an interesting segment called Energy, Utilities, Resources and Services, and I call this interesting because AI has created a circular economy in energy, utilities and resources sector. While these sectors are heavy users and consumers of AI, they are also critical enablers of AI. If you look at utilities today, particularly electric utilities, they power and decide where the next data center should be and how fast the AI data centers can grow. In fact, there are views that electricity is the only limiting factor in growth of AI. So they have a massive, massive role to play.

A data point here, the projection for data centers to consume about 10% to 12% global electricity by 2030 is almost 4x the current level. So that's the amount of growth that we will see in the electricity sector. Oil and gas have always underwritten the global energy and stability of supply of energy.

Now with data centers, natural gas and CNG are becoming the transient fuel so that we bring more reliability and load balancing to the grid, we can dispatch the load when the wind is not blowing and the sun is not shining, right? And resources, interestingly, are the providers for raw materials that runs -- that AI runs on. So the new metals; copper, lithium, nickel, cobalt, rare earth materials and aluminum are very core to scaling AI anywhere in the world.

Now with that kind of an interdependency, we are seeing circularity in action here. Energy besides the physical scalability of AI, utilities decide the reliability and sustainability of AI. This also decide the material availability of AI because of the materials they supply. And services continue to be the big consumers of AI when it comes to inferences because of primarily the B2C nature of their business. What we are seeing in the industry sectors across these different sectors in the segment is the demand has gone up, digital intensity is at an all-time high.

And there is not only growth, there's also margin expansion for these players because of what AI is creating for them. AI is also becoming the operating system for many of the industrial implementations, whether it is subsurface computing, whether it is digital mining or remote mining, whether it is grid reliability and prediction of the load on the grid, AI is sitting right at the heart of it. And my colleagues, Dinesh and Satish spoke about this earlier. This is an asset heavy and ERP heavy industry.

So ERP is all over the place. There are a lot of business rules, data, compliance, regulation that has been built in the ERP systems over decades. And that, in a way, has created this opportunity where we can put AI to unlock value from the data and also create an orchestration layer for a better human experience. And that creates a unique opportunity for SIs like ourselves to go in and look at the ERP landscape and see how we can get the best value out of it.

Obviously, we are helping clients move their OpEx savings because of AI to do a lot more discretionary projects, a lot more transformational projects that AI has unlocked for them. And what differentiates us is a triangulation of our deep understanding of the client's context, our extremely rich domain consulting skills and engineering AI at an enterprise scale. When we triangulate these 3, it has put Infosys in a pole position when it comes to AI. And the proof of the pudding is we have the AI partners for 15 of our top 25 clients in this segment.

We do work across the AI framework. We've created digital twins for a very large oil and gas major to take asset telemetry and make the assets more intelligent, more automated, reduce their downtime. We have worked in AI grade data engineering for a very large electricity provider to predict the load on the grid, forecast the load on the grid and ensure they invest on the grid where there is a congestion to provide electricity to the data centers. These are problems, mathematical problems that could not have been solved at a granular level that we are doing today.

We are working with helping our 20-plus of our clients reimagine their business processes, F&A, customer service that Salil talked about. And this is unlocking new opportunities for us to bring AI at an enterprise level and then commit to the outcomes that the client desires for; growth in revenue, reduction of costs, that is expansion of margins; and customer satisfaction and innovation, right?

So another example is the agentic AI platform, where we are building enterprise-level agentic AI platforms to drive significant change in the way client imagines their workflows and then make digital -- the agents, more of a co-worker with our clients' employees, we have done 15-plus such implementations in this segment. And of course, not to mention the full stack modernization of clients, legacy systems, which is a huge opportunity. You saw the example of Hertz. We are doing 15-plus different ways and different flavors of bringing in AI to modernize assets that have been sitting there for the last 15, 20, 30 years, where clients can immediately unlock value.

A great example is a very large airline, where we really deployed Agentic AI to modernize their systems to give better customer experience, and predict the delivery of baggage to the customers on time. Let me bring this to life with 2 examples. This is a mega deal that we signed with BP, a super major. Now the challenge was to enhance enterprise-wide adoption of AI. And here, we're talking about massive scale that cuts across all of the value chain elements.

So starting from production and optimization to dynamic pricing in the retail and convenience stores, contract automation for the thousands of contracts that they sign, IT operations and corporate functions. We picked 50-plus AI and agentic AI initiatives and then brought in our partnerships. The technology stack that we use here was an Azure foundry, open AI stack. And of course, for the developer productivity, we use GitHub copilots at a very, very large enterprise scale.

The outcomes were measurable, 18% year 1 improvement in IT operations efficiency, 50% faster contract validation, which is something that they are very proud of and 95% payment accuracy. The proof of the pudding is in a statement that the CEO made in the Investor Day, which said Infosys and Palantir are their top 2 partners who are making AI real for the entire company, and he calls it super cool and the other quote is from the ex-CIO. Let me give you another example. And this example is about scale. This is example about complexity. This example is about also not having fragmented but unified implementation of AI. This is for a large scale, for the largest oil and gas operator -- upstream operator in Australia, their challenge was to bring in and build an enterprise AI platform that cuts across different parts of their organization, starting from their production and operations, contracting, procurement, finance, HR and IT ops, we identified 16-plus high-value AI use cases for implementation, and we used Amazon Bedrock as the agentic AI for upstream functions and then Azure OpenAI foundry for corporate functions.

The way we approach this is on 4 value vectors. The bottom of this, the foundation layer is the enterprise grid platform that we build for them. On top of it, we built agents for intelligence and insights to their operations, agents for employee experience improvement, agents for asset operations; the results are visible, 20% to 35% efficiency gains in upstream value chain and 15% to 20% productivity gains in just improving the employee experience on a day-to-day basis because when they deployed this and they pick the corporate functions for agentification, this was one of the goals that we picked with them. Let's hear from the CIO or let's hear from the sponsor of this program on how this whole initiative went through. Can I have the video from Woodside, please?

Can you talk a little bit about what are some of the trends you are seeing in the oil and gas sector when it comes to AI?

Woodside is a global energy company. So we supply energy around the world. And I think being in the oil and gas industry is a really exciting place to work. Fundamentally, last year was a year of foundations for us. And so our AI strategy really fits into our digital obligation of providing intelligent systems for our staff to interact with. And that supports Woodside's ambition and goal to provide the energy that the world needs reliably at low cost and with lower carbon.

We have some 300-plus use cases. We scaled our AI pods from about 1 last year. We've got 11, 12 running now, scaling up 1 of our AI pods to 11 or 12. That was done in conjunction and partnership with Infosys. And if I look at the number of people, which is 100-plus in those pods that we on-boarded and hired over a year, first, the number of people we were able to hire in Australia was about 10. And so the ability to leverage our partnership with Infosys, your brands and your expertise and to be able to scale was really helpful to us.

So to summarize, I think we are bringing an outcome-focused responsible AI framework that is working at scale and at speed. And we're very excited to be doing this for so many clients in the sector. Thank you.

Thank you, Dash. For our next session on unlocking AI Value Retail, CPG and logistics. Please welcome Ambeshwar Nath, Industry, Head CPG Logistics and Retail.

Good afternoon. Let me start off by walking you through the market outlook and the role that AI has for our clients. If you look at the quotes from market leaders in our industry, there's a common trend that's emerging. AI is no longer just about pilots. Today, AI is embedded deep into our clients' operations that is helping them improve their revenue, efficiency and driving better customer value.

If you look at the sub verticals that we operate in, within consumer goods, we are seeing a significant impact of AI in multiple business use cases. We are seeing precision revenue growth management being one of the key levers, where millions of demand -- data points regarding demand, price, promotion, channel is ingested near real time to determine whether value is being created or lost. This is creating a potential of an improvement of 3% to 5% in the overall gross profit.

There's a significant focus of applying AI for hyper-personalized marketing, driving deep individualized consumer campaigns as well as driving AI planogramming compliance. Within the retail sector, we are seeing evolution of large language models for loyalty programs. Today, as of 2026, 70% of all loyalty programs we'll engage in will have an AI component in them. We have seen the evolution of camera vision in stores to help store operations, and we are seeing a strong evolution of agentic commerce.

Within logistics, we are seeing AI evolve in terms of doing demand sensing, in terms of route optimization as well as leveraging it for waste reduction, that's resulting in benefits of 15% to 30% in terms of overall cost reduction. So all in all, we are seeing an extensive use of AI for business outcomes and business use cases or business relevant problems for our clients.

And as Infosys, we are uniquely positioned because we bring in deep domain expertise, a strong understanding of data, our strong understanding of AI technology capabilities and governance to bring it all together to deliver meaningful outcomes.

Let me talk about 2 specific examples of how we are bringing some of these business relevant capabilities to bear. The first one, and I would believe that most of you have seen this in the Living Labs as well a short time back. But Ralph Lauren is one of the leading high-end fashion and apparel companies across the world. They are also, as of today, one of the fastest-growing companies. But one of the uniqueness about why they're growing this fast is because they are true innovators. They were one of the first companies to evolve into going online for digital sales when e-commerce was just evolving.

And today, they are looking at how they can bring fashion and technology at an intersection to drive more meaningful conversations and path to purchase with their consumers. Clearly, one of the key elements they're looking at is how can they replicate the whole concept of stylists which happened in stores and how can they bring that same culture online. Now in store, there are always challenges. You do a lot of manual merchandising. There's a lot of interaction with individual consumers.

But the beauty is, if you do it online, even if there are millions of consumers engaging, each consumer is a separate segment in itself. You can do hyper personalization at scale as if you've got a merchandiser working with you to style your exact outfit the way you want it. And the third element, which is extremely important is to reduce the path to purchase, how do you ensure that you are able to connect to real-time inventory so that the actual order can get placed. That's also a significantly complex puzzle as part of these engagements.

As part of what we did, and this was an engagement we did jointly with Ralph Lauren and Microsoft. First thing we did was we ingested 50 years of Ralph Lauren archive and lookbooks. So all that information was fed in, and then we created a whole natural language processing capability which allowed consumers to engage in a manner which is similar to the way you would engage with a human being. So you're engaging with an AI capability, but it felt very similar. And so if you wanted to choose an outfit of the nature you want or you wanted for a specific occasion, it's happening as of your talking in real life.

It drove significant hyper-personalization. And the path to purchase on an online setup was, if you can imagine, it's always you search for an item, then you browse the item, then you click it in the shopping cart. It's a long established process, but this was a seamless process because you were connecting to inventory, you could cut the path to purchase to something which is very immediate.

This has resulted into significant benefits, and this is just the start of the journey because this is evolving. But today, more than 50% of the interactions -- this has led to a 50% increase in interactions of styling queries that are coming in. The overall results of Ralph Lauren showed a 12.2% increase in revenue. A lot of that, a significant amount was contributed to their online and digital capabilities. So this is one of our best examples in the industry where we are driving hyper-personalization at scale, leveraging the power of AI.

Moving on, I'd like to now talk about a second example. We talked about a global high-end fashion apparel retailer in my first example. I want to move gears and talk about a regional player because I think that's very important as a lot of our regional players are also leveraging the power of AI.

Posti is Finland's logistics leader. It's original -- it's a legacy organization, 400 years old. It has a legacy of over 40 years. Its primary business many years back was just the postal business, but they've evolved over a period of time to get into parcels, into supply chain, into warehousing. So now they're an end-to-end logistics player.

And as the postal volumes are declining as it's true for the entire industry, they have been focused on how can they pivot to the new, how can they move from being a player that has legacy debt to a player that can drive new age capabilities, who can focus on the run to growth element and pivot themselves into building differentiated capabilities.

Infosys is an end-to-end partner for them. We are the single partner, the largest partner and the single partner that is doing entire IT services for them. And as part of that entire exercise, we have evolved an AI-first operating model, which is really across run and transform. So how do we bring in AI in every part of the Infosys set of engagements that we work on.

Today, we are running with over 20-plus initiatives on AI across their postal business, across their parcel business and their freight business. So we are cutting the entire value chain and applying AI at all points of the ecosystem. The whole focus is around run to growth. So how do we reduce the run cost and then push them into growth initiatives that can allow them to be a leader within the Nordics industry -- the Nordics market.

And lastly, they have not gone with one solution. We are the single partner who are driving AI orchestration for them. So they are working with a variety of AI tool sets, and we are ensuring that we are orchestrating it to deliver outcomes. Now what this has resulted in. It has resulted in a 50% software generation by AI tools. It's led to a 35% improvement in productivity and the mean time to recover considering that they had a large amount of legacy systems, has been improved by 70%. So this has created a massive impact. What I will do now is play a short video which talks a bit about how Posti has evolved its AI journey and how our sponsor looks at Infosys' involvement.

[Presentation]

I'd like to just summarize by highlighting 2 points. One is the fact that we are seeing AI evolve within our client landscape. It's critical, it's a true game changer for our industry. Second, together with our clients, we are working on a number of business-enabling capabilities all centered around having AI at the center and this is helping us create differentiated value and long-term association with our clients. Thank you.

Thank you, Amby. For our next session on partnership ecosystem for AI value delivery, I would like to again welcome Anand Swaminathan, Segment Head Communications Media and Technology.

Right. At this time, I think you should have gotten a fair idea about, one, the opportunity in front of us, and it's more the execution risk that can hold any IT service company back. It's not the opportunity itself. And then if you looked at the AI value framework that Salil unveiled one of the main components of that is the partnership ecosystem. It makes it even more important now that we have a very strong set of partners to be able to go to market.

And as the AI evolution was taking place, one of the things we did was to really rethink our partner strategy and construct a partner ecosystem that really got us thinking about the future and will help us to actually cross the chasm because the AI stack has to be reflected in how we are going to get the partnerships done, right? Today morning, we announced a big partnership with Anthropic is an example of how we are actually moving this forward.

So we need model companies. We need infrastructure companies that actually are investing in terms of AI transformation. Similarly, a set of companies around the chips to application layer to infrastructure to cybersecurity, to model are all part of the AI stack. Now normally, people are equating AI to one particular company or one particular category of company. It does not. It's a very complex set of components you need to make AI come to life.

And enterprises want the stack to be governed. It's very complex. It's not easy to manage the contracts or manage the performance obligations of these companies or to get the business outcomes they want unless they have somebody who is going to take ultimate accountability for it. So where we come in is we are at the center of this. Yes, AI is reshaping the IT services value chain.

But we are in the middle of, and we are now orchestrating outcomes for our clients and managing risks for them, not just emanating from us, but also from the ecosystem of partners we have. So all the partnerships that we have been announcing and we have announced are a very carefully curated set of partners who will actually make the needle move for our clients.

And again, these are partners that will help us with specific industry workloads rather than generally come with one specific set of capabilities. And that's what differentiates Infosys as against other companies in terms of how we look at these partnerships. So if you see the AI value framework, now across the framework, already, we have started executing some really solid programs in AI that is giving us referenceable templates to actually take it to more clients.

So in the case of the first component, which is the AI strategy and engineering, with a leading investment management firm, we help them to actually work with an NVIDIA stack, where their onboarding of investors accelerated by about 30%. And this is an investment firm that has more than 5,000 plus rules, regulations, and I don't need to explain that to you this particular group of people as you might understand how it works in your world, now we were able to bring in an NVIDIA AI stack -- or NVIDIA as a center point on the stack and be able to drive that change.

In another case with a leading telco, we were able to create a digital sales assistant where 95% of their fiber sales was done by the digital agent or set of agents instead of human-powered selling. Now that is the power of the partnerships that we have because in order to bring this to life, you need preestablished relationships, training between companies and contracts so that the friction to market is less. And we also have that way a mutual understanding of how will we manage together the total risk that needs to be spread between us and the partners.

Similarly, on the data for AI, a lot of examples have already been taken by my colleagues. They all talked about many of the examples, including the Polo Ralph Lauren example, which is an amazing one. But in addition to that, we have actually delivered a variety of work in terms of actually helping the clients to get the data ready for the AI world. And that is about moving it into a place where it's easily retrievable and is curated and it actually can deliver insights.

On the process AI, one of the areas where we see most of impact with the AI and the opportunity is really bringing AI into our BPM plus IT stack. And already, when Ravi spoke, he announced one of the AI products from Infosys is AI Next. So if somebody wants a full platform, they can actually get AI Next from us. So AI Next, in this particular case, with one of the leading restaurant chain has actually enabled them to faster processing of their vendor invoices. Similarly, there was an example you must have heard about CMA CGM, which is one of our clients in which AI Next played a very crucial role in accelerating the supply chain.

On the legacy modernization, one other area of this value framework, which is another area where we see a huge amount of opportunity. Bali spoke about a few opportunities there. So here, our partners together with us, we have created a set of accelerators that are enabling our clients to move from legacy architecture to the AI architecture faster. One example is a mainframe modernization program that we have done for Hertz that you saw the Hertz customer come and speak. Similarly, we have many other examples of where we have really taken this to our clients and getting them the benefits.

So physical AI, Dinesh spoke about some of the examples on physical AI, which is around how do we really bring the AI in terms of the robotics and other physical products and make sure that they are actually getting ready for the AI world. And those examples are also building. So essentially, what I would like to actually sort of sum up is to say that the opportunity -- the opportunity is really in front of us. And there is no question about that. We have the conviction on that. But the -- at the same time, we also acknowledge that this requires complex execution across multiple components. And one of the key components is the partnership ecosystem. And I think as an organization, we have invested heavily and really brought in a set of partners that will help us to transcend this from the current position to a position where we can be a leading AI player.

I would like to conclude this with an announcement we made with Anthropic today. And one of the anthropic exec says the following about us. So can we please roll the video?

Hello, everyone. Thank you for having me at your Investor Day. So look, the company is winning with AI right now. They are the ones who have the right ambition, but they're also marrying that with the right approach to deployment, governance and partnerships. Infosys has spent 4 decades building that foundation for enterprises around the world and establishing a deep position of trust. And that is not something that you can replicate overnight. And that's why we're incredibly proud to have infosys as a strategic partner.

At Anthropic, our goal is to build AI responsibly because we believe that, that is what it takes for enterprises to actually trust, adopt and put AI to work at scale.

And Infosys has always approached technology in the same way because you've managed multiple technology cycles over 4 decades at an incredible scale across all industries and all geographies. And that history gives you all the credibility that most companies simply do not have. You are embedding this frontier intelligence into Topaz, the AI platform that reaches across your entire client base, 2,000 organizations, 59 countries. So when Infosys scales AI, you don't just scale it to one company, you scale it simultaneously across so many industries and so many countries. And at Infosys, you've done that better than almost anyone and you've done it across 4 decades, across multiple technology cycles. I'm genuinely excited about what we're going to achieve together.

So in summary, we think trust, scale and partnerships are going to be the 3 pillars in which this transformation needs to happen. And we have the trust with the clients and the partners. We have the scale, and we have also a fantastic partner ecosystem that will help us to actually carry our clients on this transformation journey. Thank you.

Thank you, Anand. For our next session on the human AI workforce reimagination, please welcome Shaji Mathew, Chief Human Resources Officer.

Good afternoon, everyone. Through the day today, we heard how AI is transforming the industry, how it is reshaping the work all of us do. That necessitates a complete transformation in our workforce as well. I believe in the saying that it is not the organizations, which has got the best technology that will win, but those are the organizations which prepare their workforce to embrace that technology that's going to win.

Our AI transformation strategy is built on 3 pillars. We have seen today in the map that there are AI-first services, there are AI augmented services. So we need to augment everybody in the organization with AI. At the same time, we also have to create the deep engineering and domain skills, which are required to execute the AI-first services. And this duality is what we call the ambidextrous organization.

So the first part of the pillar, the first pillar is, therefore, a new talent operating model. Once we have this dual architecture, it's important to have a career architecture, which can hold this talent. Therefore, the need to create a new career model as well. And of course, the most important part, in my mind, is how do we develop the talent to have an AI-first mindset. So what we will do now is to double-click on each one of this very quickly.

So in ambidextrous organization, we need to enable all the people in the organization. We also need to create the deep engineering and the domain expertise. So here, what we will talk about is how we're going to create this deep expertise. That is through channels. One is by external hiring. Recently, you would have seen an advertisement where Infosys is now recruiting fresh engineers up to INR 21 lakh salary per annum. And that is really towards this developing this deep engineering talent. We go to some of the best engineering colleges in the country, the IITs and NIITs. We have a differentiated assessment to get these people in. We are also doubling down on our full stack engineers. We are doubling down on getting domain experts from the market.

But all of us know that, this technology is changing at such a rapid pace, and we don't have enough AI experts in the market. Therefore, the success of the organization will lie on who are able to develop this talent internally. So we have created the bridge programs, and these are real hands-on training programs, working on sandbox environments. And once someone has gone to this bridge program, we would do the assessment. The assessment center of excellence that we have, does the assessment on a 5-point scale all the way up to AI-led simulations.

And we also know that, in a new AI world, the skill is the new currency, not necessarily the jobs and the roles. So the CQ, which is our Capability Quotient, which really assess the skill of the employee has got four dimensions. It assesses people on technology. It assess people on domain, looks at people on the foundational skills as well as on societal skills. It's a comprehensive framework that we have to assess people on their skill.

And the business incubator series is a new way of identifying the best of the best ideas, AI-focused ideas from the company. Last time when we ran this, we had 1,000 ideas and the selected ideas will get funding from the organization. They will also get mentorship. And this is a way to develop entrepreneurial skill within the organization as well as to develop deep AI engineering talents within the organization, which will culminate in certain platforms and systems.

Now coming to the next part of the pillar -- the strategy, the second pillar, which is the career track. Once we have an ambidextrous organization, it is important to have a career model, which can encapsulate this new organization. Traditionally, we have a unidimensional career architecture. We will have people joining us software engineers at the bottom of the spectrum. They will go through the career trajectory and become all the way to the Executive Vice President.

In the new career model that we are working on now, people actually branch out in this Y architecture. The one on the left side are the -- all the people in the company who are enabled on the -- on AI. But on the right side are the people who once take the bridge program and when they get assessed and then they get moved to the specialist frame. And these are the deep engineering or the domain experts that we have -- we are creating within the organization.

Also on the far right, what you see is the expert-led organization. This is a flat organization structure that we have. They bring in really deep engineering expertise to the organization. They act as the catalyst of the accelerators around which the larger specialist ecosystem work around them. And it has got roles like distinguished technology, engineers and so on and so forth.

This career architecture also look at another angle that is in a human plus AI paradigm, Humans will do some part of the work. AI agents will do some part of the work. Therefore, there is a need for us to look at our job roles to redesign so that it works in the new human plus AI paradigm. Also, the career architecture enablement looks at introducing some of these new roles, which are not existing earlier, like the ones that we heard earlier, AI strategies, responsible AI engineers and so on and so forth.

Now coming to the third pillar, which, like I said, is probably the most critical and the most difficult one to do. We look at our talent from multiple spectrum. At the bottom that we see, these are the consumers of AI. Everybody in the organization are consumers of AI, whether they are from the software engineering discipline or they are from HR, from legal, everyone are consumers of AI. And therefore, we are enabling everybody in the organization on AI. Today, about 90% of the organization is enabled on AI.

Then we have a set of people who work on AI models, who are developing the AI agents and so on and so forth. These are the AI builders. Obviously, they are trained and developed in a different way. They have more deeper expertise. Then at the top of the spectrum are the AI masters. These are the people who work with the large language models, who create our own small language models and so on and so forth, who set the vision, who with the direction. And they obviously have quite a much differentiated enablement program.

Now the forward deployed engineers are the ones who are embedded in the client's organization. They are at the intersection of consulting, technology as well as the client context. Now there is a much more deeper program to enable them as well as to assess them. The 5-point assessment mechanism that I spoked about, which culminates with AI-led simulation and case study-based assessment, that complete spectrum is used to assess the forward deployed engineers.

So this is for the larger cross-section of the company, in fact, pretty much for everybody. But the picture is complete when we look at the entry-level folks as well as the senior most leaders in the company. Now you must be familiar with the Global Education Center that we have set up in Mysore, where all the fresh engineers from the campuses come and get their training done. The complete foundation program has been revamped now to enable AI, to make AI-based training program so that every engineer who comes to the doors of Infosys from day 1, they all get enabled on AI.

On the other side, the leaders, it's critical that leaders lead from the front with this entire AI vision that we are talking about. As we speak, this week, we have a program that's going on in our Mysore campus in collaboration with Harvard Business University, where most of our executive vice presidents are going through an AI immersion program. We also had a similar program last month for all our senior Vice Presidents in Mysore campus again, and that was in collaboration with MIT. So that kind of completes the entire breadth and length of the talent that we have in the organization. And like I said, we have a differentiated program for everyone in the organization, and that is how we are preparing for the future.

So in summary, from an AI transformation perspective, we are doing 3 things. First, we are building deep engineering and domain expertise. Second, we are redesigning our career architecture to future-proof the company for the years to come. And third, we are developing a future-ready workforce, leveraging the best-in-class training infrastructure that we have, both from a physical perspective as well as from a digital perspective.

So I will summarize by saying that this AI transformation is bringing a lot of challenges in front of all of us. But I think we are all -- we are very confident that with the transformation that we are doing within the organization, we are ready to embrace this challenge as well as to leverage all the opportunities that is lying ahead of us. Thank you.

Thank you, Shaji. For our next session on brand as a growth catalyst, please welcome Sumit Virmani, Chief Marketing Officer.

Good afternoon, everyone. I know it's been an intense day of learning. And first of all, thank you for really taking the time and spending this entire day with us.

Now I'm quite pleased to actually talk to you about the role of the brand in the larger AI journey that we are on. As most of you know, mind share leads market share. Now that is something we have heard as an adage. For many, brand is a nebulous concept. But for this audience in the room, the financial analysts, I'm sure you realize that a well-managed brand can indeed drive much stronger impact on the business, be it on the revenue dimension, the market share dimension or the shareholder value dimension. And what you're seeing on your slide out there is how brands not just across categories, well-managed brands drive a revenue and a market share uplift. But even if you look at the data to the right, well-managed brands across decades outperform not just the industry, but the market as well.

So with that as a philosophy with which how we nurture our brand, I want to actually give you an example. Just like any other strong brand, we follow a multichannel, multi-offering, multi-segment approach to marketing. But we attempt to do it with a little bit of disruption and a little bit of a twist. And what you're seeing out there on the screen is an example of how we think about our strategic partnerships. Some of the brands that you're seeing on the screen are possibly one or some of the largest brands in the world, but there's a consistency in all of them. They actually play at the intersection of passionate executive participation. And for decades, brands have leveraged these kinds of partnerships to showcase their reach to the world.

But when we think about these platforms, we think of them not just as a platform to showcase brand visibility to billions around the world, but to also ensure that these platforms are becoming better, more disruptive to their end consumers by leveraging Infosys cutting-edge technology. That's the magic in the partnership because it becomes a showcase to 1 billion people in the world what Infosys AI can do. And I want you to take a look at this video because this will give you an example of how one of our biggest partnerships is being shaped through this approach.

Let's have the video, please.

[Presentation]

Well, that in itself sounds wonderful. I guess the natural question would be, how has it tangibly impacted the brand? So let's take a look at that.

What you're seeing on your right is a ranking by brand finance, a leading brand consultancy firms based out of London. And they've seen Infosys as the fastest-growing brand in its category around the world 6 years -- for the last 6 years. To your left is another highlight of Cantor Brands the top 100 brands results. And Infosys for several years in a row is now being rated as a top 100 brand, not just in the IT industry, but across categories.

How is that larger brand awareness translating into enterprise AI resonance? And what you're seeing at the bottom of the screen are some of the initiatives we've undertaken to really drive strong association with enterprise AI. To begin with, we were the first in the industry to launch an AI services brand called Infosys Topaz. We then went around with multiple channels, whether it's enterprise AI conversations or enterprise AI world tour around the world where just in the last 12 months alone, 700 of our clients have interacted and understood our approach to enterprise AI. We even invested in expanding the Infosys Knowledge Institute to really drive research on where AI is headed, whether it's the enterprise AI radar or whether it's AI indexes across different verticals.

The idea simply is how can we be the engine of knowledge awareness and brand awareness in the enterprise AI category. And that's why what you see to your left is how Infosys is being seen from an enterprise association platform when it comes to the entire industry. This is the research that we undertake quarter-on-quarter because this is a space that is changing quite rapidly. And we'd like to know how is brand Infosys faring on the Enterprise AI association.

And clearly, as you can see across the last year alone, we are at the top of the stack. You saw multiple client stories played out over the last few hours. And that is a metric that we track very, very closely because we believe that the biggest proof of our success is our client voice. And that's the word of mouth that you're seeing consistently rising.

What's to the bottom right is how the focused effort on thought leadership is driving media share of volumes around the world. And again, as you can see year-on-year, we are almost growing that by over 100%. And this is not just how Infosys see it inside out, this is also how one of the stakeholders that all of you track very, very closely, the industry analysts, they are acknowledging it as well. Whether it's across the digital ratings or whether it's across AI ratings, Infosys has consistently been on top when it comes to leadership rankings.

And I'll bring the conversation back to where I started, which is how has all that translated into business impact for Infosys. It has not just helped us stay ahead on the revenue curve vis-a-vis the market, it's also demonstrated tangible impact on the market share gains. So the question then in front of us is what's next? And how are we thinking about our brand going forward.

What we intend doing clearly is to really live the promise of navigate your next as our clients' transition through another big turn of technology. But to really bring this promise to life is how we're going to do it is to unlocking AI value. And that's going to be the endeavor of the brand over the foreseeable future.

Thank you very much, and I think it's time for the conversation and the questions.

Thank you. Thank you, Sumit. For our last session, please welcome Salil Parekh, Chief Executive Officer and Managing Director; and Jayesh Sanghrajka, Chief Financial Officer, to summarize the day, followed by question and answers.

[Operator Instructions] Salil, over to you.

Okay. Good afternoon. I think the good news is most of you look like you're awake. So hopefully, the day has been exciting, interesting and a lot of depth from our side. Let me maybe spend just about a minute or so with a summary, and then Jayesh and I can answer questions. I know at lunch; we had a few discussions and there are a lot of questions on your mind.

So first, my sense is we have a really comprehensive set of AI offerings. You've seen the Hexagon. You've seen that beyond that, we have 30 offerings, 100 sub offerings. And you've seen examples across each of the 6 areas, which give you a view of what's going on with the new services, and you've seen all of our augmented services and the impact there is on them.

Second, the opportunity is huge. I think we started that discussion with what Nandan shared. I gave an indication of what we see external analysts quantifying these opportunities as these are large value streams. And as we go through over the next few months and quarters, we will dig into many of these individually to share with you what the value looks like, how we are going after it to make it more real for all of you as you look at Infosys.

Third, I think it's quite clear that large enterprise clients trust Infosys. You saw some of the videos and you've seen videos of client executives, CEOs, CIOs, COOs, very senior executives really mentioning the word trust and looking at Infosys as a strong partner there.

We are working with so many of our clients across the Hexagon in each of the big areas. So it's not theoretical anymore. It's really practical. It's happening in the field, and we have examples of that. We have examples of large delivery teams working on that.

Then we spend a bit of time on the platform itself, whether you look at what we built with the Topaz Fabric capability, what we built with AI Next and the individual agents that we built within that and how we can integrate across with different platforms, client platforms, third-party platforms.

You heard a lot about our talent, deep engineering talent and actually even the culture, which is much more of innovation within the company, how can we do something new? We are not a company simply of break and fix. We are a company of innovation, and that helps in AI because there are new ways of doing things and our engineering culture and mindset is a big advantage for us.

And then the partnerships, of course, we announced a very large one today, but we have several of these. And it's very clear from how the partners are looking at Infosys that it's a joint work activity. You heard from one of the videos from one of our partners, the depth of knowledge that we have, the depth of talent that we have and the capability that the partner brings, that really makes a difference with our clients.

We've already put in place a very good go-to-market, which is really take everything we have on the Hexagon, the 30, the 100 and start to meet all of our large clients to see where AI can start working with them for them and make an impact.

And then we have an incredible brand that is working well. It's growing very fast, and that helps that can -- you can see the elevation of the sorts of relationships that Infosys has in part because of the strong brand that we have built, and we will continue to build. So that in a sort of brief way is the summary.

And with that, let me request Jayesh to join us here, join me here, and then we can go through with the Q&A here.

So the first question is, you highlighted in the morning that the net new opportunity from AI will be $300 billion to $400 billion. Could you also elaborate what do you think is -- sorry, the incremental opportunity is $300 million to $400 million on new services. Could you elaborate what would be the potential for the net opportunity adjusting for the compression that you might see in many of these services? A lot of examples through the day highlighted that everything can be done faster, fewer resources or from months to weeks. What does that mean from a compression perspective? And what are we looking at on a net basis?

Some of it broke up. So what you're saying is we've talked about the growth expansion and what is the net number.

So there, what we have shared in the morning is really on the 6 areas, what we see as the expansion from what we've seen externally, the $300 billion to $400 billion quantification from a couple of sources. On the compression, we've talked about, again, what we understand to be where the compression is coming from, whether it's on application development, whether it's on infrastructure. We have not quantified that number for any external use at this stage. We have said that the expansion number from what we see today looks larger than the compression number.

Thank you for hosting us and taking us through in detail through your verticals and service base capabilities. What I have understood is that you spoke about one of the key advantages Infosys has is strong understanding of clients' data estate and the context of the client. Now that would be something which many of your peers would also claim to be having.

The second part is the partner ecosystem, which you are developing and building strong relationships. Again, that is something which here or there, put together your competitors also would potentially say that they have. So what exactly in terms of delta or incremental capability that you see that Infosys has that helps you to have a better right to win when going for enterprise implementation of AI tools?

So there, the focus in addition to the points you mentioned is one on the platform and Topaz Fabric capability that we build, where we built our own agents and we can integrate other agents. The other is the way we have identified clearly what the 6 areas of growth look like and how we are executing on that, working with our clients to make sure that we are positioned in that by reskilling our people, by building investments in those capabilities and making sure that each client, we are building that capability to grow into those areas. That's where the real difference, the execution is where the real difference will come.

Has our pipeline to TCV conversion time lines improved because now leveraging AI, we are able to build prototypes or working models much faster and clients are able to view the ROIs much faster.

So I'll take that, Salil. So if you look at the large deals that we have signed in the last few years -- last few quarters, we haven't really seen the time line of those large deals shrinking at this point in time. We have seen the deal time lines remaining similar based on what we have signed till now. Of course, the future is yet to be seen as we sign. But at this point in time, we have -- [ majorly ], we have not seen the deal time line shrinking significantly.

So recently, one of your competitors had made a comment that many ERP migration programs are seeing a significant compression in time from years earlier to weeks. So do you see that practically happening? Or you think it's probably a corner use case in a specific context and that might not be extrapolatable to the entire ERP implementations or migrations as such?

On ERP migration, we have not seen that, that specific point is valid. So what is valid is what I think some of our leaders talked about, which is when you look at modernization, which is not only an ERP migration, but it's an overall modernization approach from old legacy landscape to a more current landscape. There, we see that the speed or the time line is much more compressed. And of course, the cost is much more reduced.

Just in response to the first question that you answered that we're kind of quantifying the compression factor. If I were to take a look at it, let's say, direction-wise, let's consider this and compare this to the earlier digital cycle. There also, we saw an initial compression in the IMS and some parts of our business. And then, of course, the new opportunity took place. So we generally see a compression, then that followed by the opportunity that comes in.

In terms of relative comparison, where are we in the cycle at this point of time? Have we seen the peak cannibalization of revenues? Do you think we can further go down? Or do you think from here, we are more closer to the inflection point where the net revenue from GenAI becomes positive? So in the entire adoption cycle of this technology, where would you place us at this point of time?

So there, if you step back a little bit, there are usually sort of multiple dynamics that are at play. Typically, if there is nothing else changing, the macro is one important factor for Infosys for IT services revenue growth. And then there is a change of technology, which is going on, which is another factor. So what we see today is that in many ways, for us, the macro is improving. If you look at what we see in the large markets we are operating in, for example, in the U.S., we see overall with the changes in regulations with tax reduction and maybe an impact on interest rates, we see some move on the macro.

On the tech cycle, it's difficult to say where we are because each of the 6 areas are different in the way that will play out. So for example, some of the things on process can go very fast. For example, in customer service today, there's a huge move. And there, we will be going after areas that we are not today currently in our revenue base. So this is all incremental for us. But we have the technology, we have the partnership, we have the capability.

In some of the other areas like modernization, we have a lot of good technology. It's something that will again be incremental now. Some of the others, maybe as the time line flows out, we will see how they play out. Data is happening very much more quickly at this stage. In terms of the compression, those are things that, as we mentioned throughout the day, we see that visible, but it's not something which is large and it's not something that is insignificant. But we don't see an acceleration of that either at this stage.

So my sense is if you look at our current business situation, next year, we definitely see in financial services a strong growth. We see in energy and utilities, a strong growth compared to this year. So we're already seeing signs of visibility. It's a function of AI leverage, meaning more AI being used. It's a function of macro and it's a function of the compression. So these are a little bit more intertwined than would otherwise be.

I would request to give your name and the name of your organization since we are webcasting this session.

This is Jonathan Lee from Guggenheim. A lot to be excited about here around the AI opportunity. Can you help us understand the level of investment necessary there to reskill and hire laterally to meet the opportunity in hand? And how should we think about the impact to margins there ex potential currency benefit?

So there, I'll start off. Jayesh may have some things to add. One of the things we've been very clear about is we want to make sure we invest in this AI capability build-out, AI Topaz Fabric and platform and other tools that we have built to invest in scaling that up, scaling up the go-to-market and scaling up what we need to do in terms of training. We've also put in place some years ago, a very strong program to support our margin and make sure our cost is more and more efficient. So our view for the period in the future is we will maintain our margin guidance, and we will take all of that, that we save, which is quite substantial from our margin program and invest that into scaling up AI even faster.

So we are ready with that from the operating -- from the income statement point of view. From the balance sheet, we are also ready to make as required, appropriate acquisitions, which will fit our overall value framework, which is what we've done in the past. With that sort of a mindset, we will continue using the balance sheet as well.

Yes. Just to add to what Salil was saying, if you look at this year, 9 months into the year, we've been able to maintain our margin stable. That was on the back of FY '25 where we expanded our margins by 50 basis points. All of this is after absorbing all the investments that we saw through the day-to-day, whether it was partnerships, whether it was tech investment, whether it was training investments, the sales and marketing investments that you see in our P&L already, which has impacted 50 basis points. So we have absorbed all of that and delivered on our margins and maintain the margins and stability. As Salil said, our endeavor is to ensure that all the investments come out of our margin guidance.

This is Pankaj Murarka from Renaissance. Salil, I have two questions. One, when you called out that we have 5.5% revenues coming from AI. And in the context of -- that's still, I think, a small number, but we've seen a lot of use cases today. But in the context of the Fortune 2000 clients, I still think there are a few and even the deal size seems to be small. So my assessment is that probably average deal size is about $4 million, $5 million or something like that. So how far are we? Will we start seeing $50 million, $100 million deal and where the adoption really becomes accelerated? Meaning that's first question. Probably if you could answer that, and then I can ask the second.

So there, I think one of the reasons we wanted to share -- what we shared today in terms of AI is to give a real depth on what we are doing on AI. Now as you rightly pointed out, we shared the number of 5.5%, we still have a lot of other work that we do within Infosys, which is making up the other parts of the business. What we see in this AI activity is it is going across many things in the areas that we described and becoming part of almost every discussion.

And so our sense is it will now continue to grow. We will see how that growth is, but starting at that sort of a level, there's a long runway because essentially, over the next several years, there will be a shift. If you sort of look back a few years, we started to call out our digital numbers when they were around 25% or 20%, something like that. And we had a shift over 3, 4, 5 years where it became 65%, 70%. And so that's the sort of a play that you have. We don't know if this is going to go in that sort of a range in 18 months or will it take 7 years? But we are well on our way with what we have created to start to play it as our clients are absorbing it. And even if it goes faster, we are ready, even if it goes at that pace, we are ready.

Sure. Just one of the more -- one of the important things that we learned during the discussion today is the context. So in the context of what you laid out, the new opportunities of $300-odd billion over the next 5, 6 years, for a long-term stakeholder or an investor in Infosys, how should one think -- what are the 3 or 4 things that will change from a financial metrics perspective probably 5 years out as we navigate this journey from where we are today?

From the financial metrics...

Yes, that's right. From where Infosys is today, as we navigate this journey, let's say, over a period of 5 years, if you could put that in context.

So if you look at every tech cycle, we -- and this is no different from a cycle perspective. Of course, the metrics can be different. But the way we have always articulated it is if you are riding the tech wave and ahead of the curve, it should reflect into better growth, better RPP and therefore, better margins, right? We said that in the digital era, we are saying the same thing today. If you look at our RPP for the last 2 years, we have delivered superior RPP. RPP has grown 3%, both FY '25 and FY '26. If you look at margins, it is showing resilience. We grew margins by 50 basis points last year. We are stable margins this year despite all the investment that we talked about. So I think that is exactly what is going to boil down to if you're looking at any tech cycle in my mind from a services perspective.

This is Aditya from UBS. Just a couple of questions. So you guys have spoken a lot about Topaz, and it's good to see. I think it's moved beyond those pilot use cases to more enterprise-wide use cases. But if you could also touch a little bit on how we should think about the pricing models there? Because, for example, in the walk-throughs, we learned that some of the projects that needed huge team sizes have now been compressed to just use of the platform and maybe a very lean team.

How should we think about how the pricing is evolving in -- or pricing model rather is evolving in those kind of projects? And any rough or framework at least to think about margins as well in those kind of projects? So that's the first question.

And secondly, on headcount, I think you have given a plan on how you'll be reskilling talent and hiring more specialized talent, et cetera. But as of today, you do have a wide kind of fresher or bottom of the pyramid talent. How should we think about the utilization of that workforce now because incrementally, we will be getting into more and more projects where we will have leaner team sizes and maybe just more specialized workforce rather than the kind of fresher coders to put it simplistically. These are the two questions.

So I'll start with pricing. So if you look at the pricing models today, the models are evolving, right? You have various examples of outcome-based pricing. You have examples of pricing, which is a combination of outcome-based pricing plus an agent pricing or a platform pricing. But I don't think there's going to be one model that is going to apply to every client. It will depend on the client context, what does the client want and how we are able to best justify the value that we are creating for the client. So it's always going to be the combination like it's always been in the past. We didn't have just one model. There are various models that work. And depending on the client's context, you close on the pricing model. And I think that's how it's going to remain on that.

On the utilization and the specialized talent, I think we'll see more and more of that happening. But equally, we will also see -- and I think somewhere in the day, we had mentioned that there will be recruitment with college hires, with freshers and making sure that they learn without the tools and with the tools as they can develop their own experience and know when it's appropriate to use tools, when it's appropriate and how to assess code that is generated by the model.

So those skills will still remain quite important. And in that context, even if we have more specialized talent, utilization as a metric will still remain pretty important. That will be a driver in a different way, there are -- depending on the specialized talent and the scale and size, there are different levels of utilization. It will still remain an important metric.

And if I can just add to what Salil was saying, if you look at even in the digital cycle, when we started the cycle with 25% digital, we are now at pretty much 65-plus percent of revenue coming from digital. We retrained our employee base from what were digital at that point in time, which was representing only 25% of revenue to more than 2/3 of our revenue today, right? So we have a strong training culture, and that is what we have always dipped into to retrain and repurpose our employees.

Gaurav from Morgan Stanley. Nandan made a comment in his presentation about build versus buy. Do you think the lines between software and services is now getting blurred? And what does it mean from addressable market perspective for service providers?

And second is a question related to the evolution of pricing model that you talked about. If it creates room for nonlinearity, what's the headroom that you get from investment point of view to accelerate your journey in AI?

On the first one, I think my understanding of that is essentially, it expands massively the amount of work that we can do if we can look at some of those. And I think there, it will probably be some of the things on the edge, maybe not the core sort of systems of record and so on. But you could imagine some of the things on the edge, which could be more easily built, as Nandan was saying, in the build as opposed to the buy. And then if that is readily doable and it's effective for the client, then there'll be multiple -- it's not going to be one thing for every client. And so there's going to be different builds for different clients, which my sense is will be a larger opportunity for Infosys.

On the pricing, you're right. If you're able to have a larger part of revenue enabled through platform or agents, it will create to that extent, a nonlinearity. At this point in time, as I said earlier, these are early days, right? So everybody is testing new models. But to that extent, yes, it will create a little bit of a nonlinearity.

Surendra from Citi. So through the day, across the presentations, we heard a lot about value generation, savings, productivity. So my question is, is there a way for Infosys to capture that value better? And does AI kind of result in any change to that either for good or for worse or it really doesn't matter? Because one of the key issues has been that like over the years, we have seen a lot of presentations across the industry, talking about millions and hundreds of millions of dollars of value. But again, it seems like most of that goes back to the customer. So any way to kind of capture the value better?

The question is you saw so much of revenue -- savings for the client. Is there a way to capture it?

I think there was some discussion in some of the client examples on outcome-based. Now if we manage to do some of those with some sharing, we might see some of the benefits of it. Today, if you -- in one of the early charts, we sort of showed the model has moved faster than the reality at the enterprise. So what tends to happen is the enterprise people at a more discussion level are expecting the model type of benefit in the pricing or the cost. And we are not able to make that happen. So today, it's not more equitable. But in the future, when it becomes more aligned, the model and what's in the enterprise, then you could see that part of it could be there.

And if some of the outcome-based works, you could imagine that some more comes our way. But it's not visible today. So it's not something that we are looking, for example, in the coming year. But it's something which is in our mind as what Jayesh was saying, that it is still early days. We'll see how the pricing approach will develop.

Again, if I can just add to what Salil was saying, there are also indirect ways to capture the benefit, right? Like again, through the presentations, you would have seen multiple sectors, 15 out of the top 25 clients, we are the AI strategic partner. Now that only comes in when you have created significant value for the client, right? You saw in Anand's presentation that large part of the telcos, we are large players. That only comes again when we have created significant value for the client and you become strategic partners for the client. So those are the other benefits of creating that value for the client. It's not just that everything gets passed on to the client. You also get a lion's share of the client's landscape.

Kunal from Bank of America. Given all your investments into small language models as well as proprietary solutions, I was wondering if there is a bigger opportunity that you foresee in either of mid-market customers or then emerging market kind of customer base. Mid-market because I wonder if there can be larger turnkey programs that can come your way and emerging markets because if it's not going to be a labor-intensive model, can the profitability of these projects now meet thresholds better than earlier?

Couldn't hear.

Small language model.

Yes. So there, first, the small language model, I think, for us is a very good indication of the depth we have, and it's very useful on a limited data set in a large client already today. So we are seeing some benefit of that, whether it's more for alignment or more even for code development. You heard, I think, in one of the sessions, the discussion on our own model for code development into that.

We have not looked right now at the mid-market because the cost of sales is very different. So we have to figure out if that will work in that market. And emerging markets, we have not looked beyond -- I mean, I would not call them emerging markets that are growth markets that we have looked at. For example, we think markets in the Middle East are very strong. But it's not like an emerging market, but it's a growth market where we will look for some of these models. But right now, the adoption -- it also depends on the adoption in that environment, in that geography before we can go and adoption in the mid-market as a client base also.

This is Sandeep from Equirus. Just one question. When the enterprise client penetrates the adoption of AI, what I mean is most of their legacy application modernize, they do the data layer properly, they migrate it to the cloud and they enter the post-AI mode. In that period, what could be the growth rates of the industry and the Indian service provider? Because in that phase, the growth could be lower because everything could have been automated. Why I'm asking is many investors has a doubt that in a post-AI adoption era, the terminal growth rates could be negligible.

I didn't follow.

I didn't get the question. If you could repeat or maybe increase the volume, we couldn't hear very well.

Yes. What I'm saying is once the enterprise clients enter the post-AI adoption where most of the application modernized data layer has been created, cloud migration has happened. In that phase, the investor worries the terminal growth rates could be much lower because most of the applications data could have been modernized.

So there, I think in terms of what happens in the post-AI world, of course, that seems a little bit far away today, but what we think is -- I was with one of the people who are building the foundation model a couple of weeks ago, and they gave a good sort of example. They said that the amount of software demand that is there for writing software is becoming 100x in terms of the size. So even if you go into the post-AI world, there's productivity impact, we still see a huge amount, even if you assume a 10x productivity benefit to a developer of what is available in terms of what is to be developed, what is to be built.

So the post-AI world, in my mind, is not a static world where everything is done. It's a world where there are large enterprises starting to use agents in many areas, having very strong platforms using, for example, Topaz Fabric as a capability, but also building new functions, new features, managing things. It's much like what we have today where there are new things happening even on platforms, older platforms, which, let's call it, are somewhat stable today in terms of they're implemented. But there's always new work that people are looking for, but that's the nature of the economic growth where there is always new features, functions that tech is driving and more tech across the enterprise, which can give you different areas to work on. So my sense is in the post AI, of course, the transition is very exciting with all the work we'll do, but there's even more work because there will be more and more things that will be going on in that post AI era.

We have time for just the last 2 questions.

It's Kawaljeet from Kotak. I have a few specific questions. The first question is that for AI agents that you're deploying in a client environment, are those homegrown? Or are those of frontier model companies?

So on agents, there are multiple people who are building agents. So first, we are building agents. Second, some of the foundation model people are building, they are a little bit more broad-based. Then there are third-party companies that are also building agents. And then, of course, the public cloud players are building agents of their own and other third-party agents that they are providing. So there will be a host of those agents from which some selections will be done. And of course, clients are also building agents.

And sir, for agents of third party, let's say, what is the services intensity? So for example, let's say, $1 is spent on a third-party model and you basically customize it and configure it for the client environment. And what is the services revenues that you get versus a dollar which is captured by the, let's say, a frontier model company or an external third-party agent provider?

So there, we don't have very deep exact stats on that, that we can share. What we see is different because if you look at a software development life cycle, part of it, as you know, is the cost of building the software. So in this case, the agent -- but there is a significant part beyond that, which is integrating it into the environment, making sure that it's working in that environment and the performance attributes and then the security attributes.

So we have got some examples of what we've done as we shared today in these situations, but we don't have a statistic that we can share that 1 equals to x because of the ratio. As we go through the next few quarters, we will definitely internally build up a larger data set on that. And then we'll see if that becomes something that we can share publicly.

This is [ Zeeshan ] from Capital Group. I guess just a quick one. For the last many quarters, our sort of net headcount has been pretty flattish as we've modeled through sort of the macro challenges and so on. I mean with the AI services picking up, are you internally gearing up for sort of net headcount to start picking up again? I know we're hiring sort of a lot of freshers, and we also have that counterbalance with some internal efficiencies and, of course, just natural attrition. So when you factor all of that in on a net basis, is that something you're gearing up for this year? Or should we expect that to still take some time given the AI-centric efficiencies that you're factoring in?

So there, I think, first, in Q3, we had a headcount growth, I think it was 3,000 or 4,000...

We're at 13,000.

For the year, we've added 13,000 net headcount for the first 3 quarters. My sense is we will continue to add headcount as we go through. And it sort of comes back a little bit to an earlier discussion we were having, which is there's a macro element and there's an AI element. And we will see -- my sense is the macro will potentially be better. And of course, we have a very good sense of the AI opportunity set. So when you put both of this together, if in the last 3 quarters, we've done 13,000 net headcount increase, my sense is we will continue with the headcount increase in the coming quarters as well.

Thank you. That brings us to the end of the Q&A. Thank you, Salil and Jayesh. Thank you, everyone.

Thank you, everyone.

Thank you, everyone.

Thanks.

Thank you.

Thank you, everyone, for joining us at the Infosys Investor AI Day 2026 and for your thoughtful engagement. Hope you have filled the feedback forms on your tables. You can leave them there. Our volunteers will collect them. The people who asked for airport coaches, they are waiting at Gate 9. There are buggies downstairs to take you to Gate 9. And the first coach leaves at 4:45. The second one leaves at 5. Thank you, everyone. We look forward to seeing you at future investor relations events.

Ladies and gentlemen, good day, and welcome to Infosys Limited Q3 FY '26 Earnings Conference Call. [Operator Instructions] Please note that this conference is being recorded. I now hand the conference over to Mr. Sandeep Mahindroo. Thank you, and over to you, Mr. Mahindroo.

Hello, everyone, and welcome to Infosys Earnings Call for Q3 FY '26. Let me start by wishing all of you a very happy New Year. Joining us on this call is CEO and MD, Mr. Salil Parekh; CFO, Mr. Jayesh Sanghrajka, along with other members of the leadership team. We'll start the call with some remarks on the performance of the company, subsequent to which the call will be opened up for questions. Please note that anything we say that refers to our future outlook is a forward-looking statement that must be read in conjunction with the risks that the company faces. A complete statement and explanation of these risks is available in our filings with the SEC, which can be found on www.sec.gov. I'd now like to pass on the call to Salil.

Thanks, Sandeep. Good evening and good morning to everyone on the call. Thank you for joining us. Warm wishes to you for the new year. We had a strong performance in Q3. Our revenues grew 0.6% sequentially and 1.7% year-on-year in constant currency terms. Our large deals were at $4.8 billion with 57% net new. This was across 26 deals. Our adjusted operating margin was 21.2%. We generated free cash flow of $915 million.

One of the most significant large deals we won was with the National Health Service in the U.K. This $1.6 billion deal expands our work in the health care sector. We will help NHS leverage AI to streamline operations and improve patient care for U.K. citizens. We have deepened our Topaz AI capability with an agent services suite called Topaz Fabric. This suite helps our clients manage and implement AI agents across the enterprise.

We are expanding our strategic partnerships with AI companies. We recently announced a partnership with Cognition. Here, we will combine Cognition's Devon software agent with Infosys' knowledge of the client landscape and industry expertise. We are already working with them across clients. Industry analysts recognize Infosys for its leadership in AI. In financial year 2026, we were recognized as a leader across 12 ratings. We had strong momentum in AI adoption across our client base. Today, we work with 90% of our 200 largest clients to unlock value with AI.

We are currently working on 4,600 AI projects. Our teams have generated over 28 million lines of code using AI. We built over 500 agents. We are scaling our forward deployed engineer team. Our clients are turning to us as trusted partners to drive value realization from AI investments. Some of the areas they focus on are fragmented data, legacy application landscape and business workflows that are not conducive for AI.

We bring together a deep understanding of clients' technology landscape, strong data engineering and process reimagination capabilities to help them capture value at scale from AI. We aspire to make AI work for clients delivering business outcomes for cost, revenue growth and innovation.

We are witnessing 6 AI-led value pools emerging that could unlock a large incremental opportunity for us. We also see productivity-led benefits that compress some legacy areas. The 6 value pools of opportunity in AI services we see are AI engineering services, data for AI, agents for operations, AI software development and legacy modernization, AI and physical devices and AI services.

We believe we are uniquely positioned to capture market share across these value pools and emerge as the leading AI value creator for global enterprises. We will share a comprehensive view on our approach at an Investor Day later this quarter. In Financial Services, we see good traction in large deals and discretionary projects. In Financial Services and in energy, utilities, resources and services verticals, we expect acceleration in financial year 2027 over financial year 2026. This is based on good deal wins and AI partner status with 15 of our largest 25 clients in each of these verticals.

With the strong performance in this quarter, we have revised our revenue guidance for the financial year. The new revenue growth guidance for this financial year is 3% to 3.5% growth in constant currency. Our operating margin guidance for the financial year remains the same at 20% to 22%. With that, let me hand it over to Jayesh for his update.

Thank you, Salil. Good morning, good evening, everyone, and thank you for joining the call today. First of all, a very happy New Year to all of you. Coming to the quarter. Our Q3 performance demonstrates continued momentum we saw in the last 2 quarters, underscoring resilience of our business model, relevance of our offerings and our disciplined execution. We had another quarter of growth despite seasonal weakness and reduction in third-party costs. The results for Q3 FY '26 include a charge associated with change in labor codes in India, which had an impact on operating profit, net profit, EPS, free cash flow for the quarter.

Reference to the adjusted numbers exclude the impact from the same. Revenue for Q3 was $5.1 billion, up 0.6% sequentially and 1.7% year-on-year basis in constant currency terms. Operating margins include the impact of change in labor codes stands at 18.4%. Adjusting for the same, it is at 21.2%. Key highlights of the quarter are as follows: -- we achieved strong revenue growth despite seasonality and lower third-party costs. Third-party as a percentage of revenue reduced by 0.3% sequentially and approximately 2.4% on a year-on-year basis.

With 3 strong quarters of performance, our revenue growth in 9 months stood at 2.8%, which is at the higher end of our earlier guided range. This is despite the lower third party, which has reduced by approximately 1% compared to the same period last year and now stands at 7.3%. Momentum in Financial Services continues with 3.9% year-on-year in constant currency terms.

Among geos, Europe continued to lead the growth by 7.2% year-on-year in constant currency terms. Volumes continue to remain soft for the quarter and the year. On a 9-month basis, RPP increased, reflecting continued momentum of value-based selling and productivity increases that we have achieved. Adjusted operating margins increased by 20 basis points sequentially to 21.2%. We continue our investments in sales and marketing, which has increased by double digits this year to date and impacting margins by approximately 50 basis points.

Utilization, excluding trainees was down by 1% sequentially at 84.1% and including trainees, was down by 2.2% to 80% as we continue to create capacity for future growth opportunities. Our adjusted margins for 9 months are at 21% at midpoint of guidance after absorbing accelerated investment in sales and marketing as well as lower utilization. On-site mix further reduced by 10 basis points in Q3 and by 70 basis points in 9 months FY '26.

Investment in talent continues. Net headcount increased by 5,000 to 337,000 employees. LTM attrition declined by 2% sequentially and 1.4% on a year-on-year basis, reflecting both market conditions and our focus on employee retention and upskilling. Large deal TCV was robust at $4.8 billion in Q3 with 57% net new. Total large deal TCV for 9 months stood at $11.7 billion, exceeded the total large deal TCV of full year FY '25. Net new deal TCV for 9 months was up by 40% as compared to the same period last year.

Large deal pipeline continues to be healthy. Our razor-sharp focus aided by the deployment of AI agents on our order to receivable cycle has resulted in decline of 5 days in DSO, including net unbilled to 82 days sequentially. Driven by strong collections, free cash flow generation adjusted for labor codes remained robust at $965 million, which is 113% of adjusted net profit. Adjusted free cash flow conversion for 9 months stood at 118%.

Adjusted EPS in rupee terms for 9 months FY '26 grew at double digits at 11.5%. During the quarter, we successfully completed our largest ever buyback, returning INR 18,000 crores to our shareholders, which will help EPS accretion. We also paid out interim dividend for FY '26 in line with our capital allocation policy.

Adjusted operating margins for Q3 expanded by 20 basis points to 21.2% sequentially. Major components of changes are as below: Tailwinds of 40 basis points from currency movement, 40 basis points from Maximus comprising primarily of value-based selling, critical portfolios and lean and automation, offset by 70 basis point impact from furloughs and lower working days. The impact of higher variable pay was partly offset by one-off benefits during the quarter.

Consolidated cash and investments were at $3.9 billion at the end of the quarter after returning $3 billion to the shareholders in the form of dividend and buyback. Yield on cash balance was at 6.19% and ROE stood at 32.8%. We signed 26 large deals during the quarter, including 2 mega deals. This includes 10 in financial services, 4 in retail, 3 each in Life Sciences and Manufacturing, 2 each in communication, EURS and high-tech. Region-wise, we signed 16 deals in America, 9 in Europe and 1 in Rest of World.

Coming to verticals. We see continued momentum in financial services with approximately 5% growth in last 9 months, led by large deal wins and uptick in discretionary spends across subverticals like banking, payments, mortgages, along with assets and wealth management. There is elevated interest in AI-led transformation, platform modernization and vendor consolidation.

We are seeing a shift from compliance to business growth. Significant core transformation across all FS subvertical is creating strong long-term strategic pipeline, providing good IP platform partner opportunities. We are now a preferred AI partner for top 15 out of 25 banking clients. Uptick in discretionary spend in aforementioned subverticals and deal wins in recent quarters positions us favorably for better growth in FY '27.

Manufacturing vertical is also impacted by tariff uncertainties, which is preventing clients from committing to long-term investment. Discretionary spend is under pressure and decision-making is slow. Industrial and aero are doing well, but auto sector remains challenged. Clients are prioritizing cost discipline, consolidation and efficiency, and we are supporting them through digital rationalizations and AI-led productivity initiatives.

Overall pipeline remains healthy and focus on cost takeouts, infra consolidation and ERP modernization. EURS companies are increasingly allocating budgets towards AI infrastructure, data readiness, cloud and software platforms. There is demand for setting up GCCs across sectors with most clients looking at SI to complement their GCC strategy.

We are a preferred AI partner for top 15 out of top 25 clients. We are seeing an increase in discretionary demand in utilities and energy, which should lead to growth acceleration in FY '27. Utility sector is witnessing increasing in demand driven by massive investments in infra and AI data centers. While discretionary demand in energy sector is focused on decarbonization and low-carbon solutions, there is also focus on cost optimization and consolidation due to enterprise AI adoption.

Retail and CPG clients continue to experience uncertainty due to the ongoing tariff negotiations and evolving geopolitical equations. Clients are prioritizing cost takeouts and AI-led productivity deals while discretionary spend remains soft apart from SAP, DNA testing and AI augmented services. We continue to leverage Topaz and our AI Next platform to deliver measurable business value with robust guardrails around privacy, governance and augmenting customer and employee experiences.

Telcos are prioritizing AI automation and transformation productivity increases, while traditionally IT remains under pressure. Clients are increasingly seeking partnerships with SIs for [indiscernible] scaling and innovation within complex ecosystem. Focus is on outcome-based engagement models rather than traditional effort-based pricing model. Our stellar execution in a seasonally weak quarter is a clear reflection of our ability to navigate the uncertain environment effectively. Strong year-to-date performance and robust deal wins have enabled us to revise our revenue guidance for FY '26 upward to 3% to 3.5%. This does not include any revenues from the joint venture with Telstra still await the regulatory approvals. Our operating margin guidance remains at 20% to 22%. With that, we can open up for the questions.

[Operator Instructions] The first question is from the line of Ankur Rudra from JPMorgan.

Good to see a nice print here. Just first couple of questions on the revenue and the demand side. The signs have been quite strong for the last couple of quarters, momentum has been quite strong as well. I'm just curious why the outlook -- the implied outlook for fourth quarter can't be stronger than it is. And secondly, I just want to confirm that your comment is for a growth acceleration in F '27 for the overall business and not for a segment alone? And are you seeing any signs of short-cycle projects or discretionary spending expanding beyond financial services and energy also, especially when you think about F '27?

Ankur, this is Salil. So first, on what we are seeing in terms of the momentum and the deals, all of that has led to the increase in the guidance keeping in mind the overall picture. So we mentioned -- Jayesh mentioned a little bit about financial services, about energy, utilities, the overall deal. And then if you look at some of our other sectors, we are still seeing those sectors starting to come up, but not at that level. So keeping all of that in mind, we've increased the guidance for what we see in Q4.

On the numbers for next year, so what we have shared today is in the 2 verticals, energy, utilities, resources and services, and in financial services, we see that the growth on financial year '27 to '26 will be good, and that is because of the deals we have won large and other deals and the AI where we have partners with 15 of the large -- of our large 25 clients. So those 2 things especially are giving us that view. We are not making a comment on the overall. We are not saying anything on the overall at this stage.

Ankur, if I can just add to what Salil was saying on guidance and your question on why Q4 guidance cannot be elevated more. You should also remember that there is a lower working day calendar day impact in this quarter, which is usually seasonally there. So that is also a headwind from the guidance perspective.

Appreciate it. Just a question for you, Jayesh, as well on the margin side. Margins appear to be down 20 basis points if I adjust the gains from the sale -- property sale this time. Could you highlight if you're seeing any kind of pricing pressure? And also, how do you see the puts and takes going forward? Also, given a lot more disclosure on the AI side, which is appreciated, I'm curious if AI is a headwind or a tailwind on your margins when you do these 4,600 AI projects.

Yes. So you're right, there was a benefit that we got this quarter, and I did call that out that we that benefit was largely offset by the higher variable pay that we also provided in the financial statements this quarter. So that's the put and take of the margin. On the pricing, if you look at our consistent pricing commentary has been that our pricing is accretive. We have seen consistently our pricing going up on back of various factors, including AI, including Project Maximus. Newgen pricing is part of the Project Maximus, which includes how do you price these new AI projects, et cetera, of reagents, et cetera. So we don't really see an impact or a headwind coming because of the AI projects on pricing, especially.

Next question is from the line of Bryan from TD Cowen.

I wanted to ask on North America. So just your comment on your view going forward here, at least in the coming quarters, you see it just dipped down to a contraction of minus 1% on a year-on-year basis. Was that due to any particular industries? And just how do you see that progressing here as you go through March and beyond?

So Bryan, this is what we had called out at the beginning of the year when we provided our original guidance that looking at the deals in the pipeline, looking at the projects that we have and the projects or large deals that were under execution, we expected this year, the third-party cost and therefore, the third-party revenue to be lower than the last year.

It's across segments. Of course, the impact of it by segment could vary, but the impact is across segments.

Okay. Understood. And then just as it relates to the commentary on budgets going forward, can you just comment on the conversations you're having with enterprises now as it relates to their calendar '26 budgets. As you think about this right now versus this time last year, any key changes worth noting?

So this is Salil. I think what we see now is, first, the comment that we made earlier on energy, utilities, vertical and financial services. In financial services, we also see discretionary work that is more prevalent. And then we see much more activity on AI. And in the AI area, what we are starting to identify as the 6 value pools, areas where we can drive faster growth. We are seeing traction on that. And with some of the partnerships we've announced and some others that we're already working with companies on, we see good momentum. So those are the 2 things that we are seeing. Some of the discretionary in FS, good momentum in those 2 energy utilities and financial services. And then in AI, more activity, which is different from this time of last year.

Next question is from the line of Ashwin Mehta from AMBIT Capital.

So just one question in terms of health care. It seems to have done pretty well this quarter, almost $44 million of incremental revenues, which is nearly double of our overall incremental revenues. So what is the driver of the health care growth? And secondly, was there any contribution from the NHS deal in this quarter?

Yes, Ashwin, Healthcare did benefit from the contribution from the NHS deal that we signed.

And we expect residual contribution as you get into the next quarter or this is kind of scaled up?

Ashwin, we don't provide deal by deal the revenue estimates per se, right? But yes, health care did benefit from the NHS.

Fair. And the second question is in terms of wage hikes. I missed the initial comments, but any decision in terms of the wage hikes? And are they expected in 4Q?

Yes. So on the wage hike, whenever we decide that we've always considered multiple factors; when was the last wage hike was done, what are the market scenarios, the inflation, et cetera, et cetera. If you look at this calendar, we've already done -- rolled out wage hikes in 2 stages, effective -- one part was effective January, the other one was effective April, like we always do. So we haven't decided the next cycle yet.

Next question is from the line of Abhishek Pathak from Motilal Oswal.

Congrats on a good quarter. So a couple of questions. Firstly, do you think this is the year when clients kind of move from the AI strategy being good to have to something of a necessity, right, which means that is this a year when foundational AI work starts getting taken seriously across verticals? That's the first one.

And secondly, on the Cognition deal being a very interesting sort of partnership. Sort of very curious to know how you're pricing this, how you're taking it to clients? I mean, is Devin kind of initially leading to a bit of cannibalization in revenues? And sort of how are those contracts structured? And over the next 1 to 2 years, how do you expect a typical deal with, let's say, an agent like Devin and yourself sort of structured? So those are 2 questions.

So on the first one, what we are seeing is there is more and more interest in AI work across different industries. So we will continue to see that going through the year. We will now watch and see because every quarter so far and especially in Q3, we have seen that interest, our pipeline, the number of projects, our penetration of our large 200 clients with AI work, all of that is going up, and it's across those different verticals. There is much more activity there, which we called out in financial services, but we also see that in telco. We see that in pharma, health care. We see that in energy utilities. We see a little bit in life sciences. So it's not like only one sector. But yes, in FS, it's quite a bit more.

On Cognition, the way that works is basically the Devon software agent and our work, we are doing joint work in clients already today. So what tends to happen is there are certain sets of activity. For example, we see some things on legacy modernization where in the past, that was a large long commitment for clients. With this sort of combination between a software agent and Infosys and our knowledge of the client landscape and of the industry, those things become much more addressable. And so those sorts of newer areas, those are the 6 value pools that I referenced earlier. This is one of them. Those are the new areas that start to come into play. And in this particular case with Devin, that's one example. There are others where that agent can be used in different places. And that's the type of growth we are seeing because that's new work that would ordinarily not have been done at all, but now can be attempted in a combination.

Next question is from the line of Jonathan Lee from Guggenheim Securities.

Can you speak to the level of visibility and certainty you have in your implied fiscal 4Q revenue growth relative to the visibility you've had in prior years around this time?

Jonathan, this is Jayesh here. I mean, whenever we have looked at the guidance, we do take into account multiple factors, the deals that we have signed, the deals that are ramping up and the usual factors affecting the quarter like calendar days, working days, et cetera, et cetera. So I think that is what has gone into guidance this time as well. What I can tell you is at the lower end, we have baked in a higher amount of uncertainty. And at the higher end, we have baked in a better macro environment.

That's good color. And a follow-up, can you help us reconcile what you're seeing around subcontractor usage in the quarter versus the downtick in utilization you're seeing? Is there a skills gap that you might be facing? And how should we think about that dynamic going forward?

Yes. So subcon historically, you're right, is always a factor of where the skill gaps are, where the skills that you need depending on the geography, depending on the tenure of the requirement, et cetera. And that is how the subcon uptick or downtick happens in the market in our scenario, and that is what has happened this quarter as well. There are some of the large deals, there are some of the deals which would have started ramping up and we would have -- we needed to dip into the subcontractors to fulfill those requirements, which is what is reflected in the uptick.

Next question is from the line of Vibhor Singhal from Nuvama.

Congrats on a solid performance. Salil, my question was on 2 key verticals, manufacturing and the High-Tech division. So manufacturing, just wanted to pick your brains on how are you seeing the traction in this vertical, given the kind of headwinds the auto companies are seeing globally in terms of their EV rollouts and the competition. How are different parts of the manufacturing vertical looking like at this point of time? And do you expect the momentum to pick up in that?

On the High-Tech vertical, just again, I think we saw a sharp drop in this quarter, might have been due to seasonality of furloughs. But anything that you're looking at? This vertical has been around $370 million, $380 million kind of run rate for us for quite a while now. What are you looking at in this vertical in terms of next drivers of growth? And are we seeing any momentum building up in this in the near future?

On manufacturing, as you mentioned, there is weakness in automotive and in some parts of industrial across Europe. We see some strength in some elements where the manufacturing, and this is partially in U.S., partially in Europe, is supplying capability, which is coming for the build-out of the data centers and so on. So there are some of those companies which are benefiting from that. But the automotive side, as you mentioned, we see that continuing to be weak. We are focused on expanding our base there. So we are looking at and have successfully worked now with multiple automotive companies. And we also see that going beyond automotive as the broader manufacturing, which is supplying capabilities to the boom in AI and data center activity, not the services is what is going to help us in manufacturing.

On High-tech, similarly, there's groups of companies which are strong. There are groups which need more attention, and we have a portfolio of those companies. Overall, there is still cost pressure in High-tech, and we will push. There is a lot of productivity activity that is going on there where clients are looking for productivity benefits. And they are also looking some of them for where they will get their growth into -- again, some of the companies which are supplying servers, et cetera, we are seeing those are doing pretty well with the AI boom. The others are looking for where are the growth elements that are going to come, and we are supporting that work. And high-tech also at this stage, we see some constraints in that industry.

But just to further on that. Do you see this vertical maybe picking up for us, not in immediate term, but let's say, in the medium to long term, given that the widespread adoption of AI should be -- and these companies should be at the -- some of these companies should be at the forefront of that. Do you think this vertical could be a good growth driver for us maybe sometime down the line?

So I think in the medium term or longer, my sense is high-tech is a good industry. We are very comfortable to be in it, as you pointed out, with different ways of AI impacting it across different value pools, they will also go through those changes.

But we have to make sure that we are providing them the services that they're looking for and in a way that they have a lot of cost pressures today that becomes manageable in their cost structure. But I mean, there's no time line in my mind. But yes, in the medium term or beyond, high-tech is a good industry for us.

Got it. Got it. Just one last question for Jayesh. Jayesh, as this quarter we took this exceptional item on the labor law impact. I would assume that the entire impact that we had to take has been taken. And for next quarter, there wouldn't be any exceptional item anymore. And what would be the recurring impact of this new labor laws on our P&L in terms of margins?

Yes. So whatever is known at this point in time on back of the regulation that has been -- that has changed is being taken this quarter. We don't expect -- unless, of course, there are changes in the regulation, we don't expect any further impact going forward as one-off. The recurring impact of this would be 15 basis points on an ongoing basis approximately.

Next question is from the line of Keith Bachman from BMO Capital.

Could you speak to how you anticipate revenue per employee changing over the next couple of years? And the spirit of the question is driven by trying to better understand how you see emphasis in the industry. One of the core value propositions has been managing people and growing in terms of managing agents instead of managing people.

Yes. So Keith, it is similar to what we have seen in any other technology wave. If you are ahead of the curve, you will see an increase in your productivity because of the premium that you can keep with you. If you're behind the curve, then you probably will see a dip. The only measurement that would change here is the premium is measured now in terms of productivity. So if you are delivering better productivity, you would be able to keep some of that with you, which is -- which will get reflected in pricing, better pricing.

If you are behind the curve in delivering the productivity, you would see a dip in pricing. So that's how you will see in a traditional environment, the only change I would say is the pricing models per se are also changing and emerging. There are newer and newer pricing models are emerging, how do you price agents, how do you price the underlying platform, et cetera. But early days to say at this point in time, how will that reflect in terms of linearity or nonlinearity.

Okay. Okay. And the second one is more micro is could you speak to -- there's been some recent press reports about your relationship with Daimler in terms of maybe that moving away. Could you speak to anything you could comment on Daimler and/or is the Q4 guidance reflecting any attrition in contracts, large contracts? Or should we be thinking about if we look over the horizon into FY '27, should we be considering any major attrition -- any attrition from any major contracts? And that's it for me.

Yes. So Keith, our current contracts are valid till December end -- till December '26. So we don't really see any contracts within that expiring at this point in time. Beyond that, we don't really give a color on a client-specific or a project-specific details.

Next question is from the line of Gaurav Rateria from Morgan Stanley.

My question is on the deal renewal cycle. Any color that you can share on what has been the experience on your renewals in last several quarters? Specifically, you did mention about a comment that the legacy part of the business is seeing some compression on refresh because of the AI cycle. So any trend on which service lines are seeing that most visibly in your experience? And is that also -- does that also mean that your overall renewals may have a little bit higher leakage than usually that you used to have, let's say, in the past because of the whole narrative around AI deflation that is coming on the legacy services?

I'm sorry, Gaurav, we actually got dropped off. Would you be able to repeat the question, please?

My question is on the deal renewal cycle. Your comment did allude to significant productivity benefit on the legacy services. So anything that you could share from what you have seen on the renewals of your larger deals, specifically using some of the AI tools? What has been the learning there? Has there been some amount of leakage, which has been higher than usual?

Gaurav, this is Salil. So on the large deals, we are typically seeing whether it's renewals or also deals which are -- we are winning from other companies where we are beneficiaries of consolidation. Typically, across the board, there is a large expectation from clients on AI productivity benefits. What we have done is we have modeled in what we are seeing today and built a path to that because these are typically 3-, 5-year deals. But we are also not in a position where sometimes the client expectations over 5 years are very different.

So we have what we are seeing and there we can view what that sort of a benefit is that we can provide because these are multiyear sort of deals. Having said that, we don't see -- in fact, we are winning on large deals quite a lot. If you look at the numbers in the 3 quarters, we have done more than the full year of the previous year. And Q3 was already $4.8 billion. We've seen some net new deals, for example, NHS.

So yes, there is that productivity. But yes, we are also benefiting from consolidation and winning things across the board where my sense is we are gaining on the market share side.

Got it. My next question on your visibility for CY '26, fair to say that looks better than the last year because last year, you entered into the year where you had a big decline in the fourth quarter because of some specific issues. And this year, your guidance alludes to kind of a much better fourth quarter outlook. So your exit rate is much better than the last year. Does it mean that it gives you a little bit of a tailwind when you get into the FY '27 compared to last year when you got into FY '26?

I think the way you have described it, you have done the maths on that one because what we can see is -- our guidance for the full year, we have the range, which gives us a good traction on Q4 with a lot of the good deals that have come and what we saw in Q3. Then we are seeing the discretionary coming back in financial services. Then we are seeing energy, utilities and financial services looking better in the next financial year than this financial year. And then we are seeing in AI services, the 6 value pools where we see a good growth opportunity. So all in all, that gives us a good, let's say, good view of next year.

Next question is from the line of Sandeep Shah from Equirus Securities.

Congrats on a good set of numbers. Salil, first question, are you witnessing the average size of AI-led deals are going up materially on a Y-o-Y basis across sectors? And just a follow-up, if answer to this is being yes, one can say clients are now in a state of mind where they don't fear in terms of modernization of legacy applications. And if that is true, can it lead to a better discretionary spend on that side of the services in CY '26 versus last year?

On the AI part, so there are 2 things. One is there are deals which are only AI. One is where AI is pervasive in every -- in a service we are offering. So it's difficult, therefore, to say the size of the deal. But in general, the usage of AI is much more across all our services. And the actual only AI, if you can call it like that, deals are also going better. So that's what's happening.

I think on that modernization, if I understood, yes, we are seeing that across the board because AI can open up that and make it a little bit more efficient for the client and therefore, more -- like they'll have a better return on that. And then will the discretionary come after that? That one, we don't know, meaning it depends on the industry situation also for that. Like what we see right now is in financial services, we are seeing it. But the other industries, we'll see how they play out as each one we've given some color. That will be different for different industries is what we think.

Okay. Okay. And just a follow-up to this. Is there a traction in terms of number of deals below $50 million has now started increasing and this could be a trend to continue rather than volatile trend earlier? And just 2 questions to Jayesh. Is it fair to assume third-party items as their cost line as a percentage to revenue for this year, which we guided at the start of the year, may be stable here on or may further decline beyond FY '26. And Jayesh, this INR 165 crores profit on property, plant and equipment, will it be a headwind in the fourth quarter?