CTSH - NASDAQ

Ladies and gentlemen, welcome to the Cognizant Technology Solutions Third Quarter 2025 Earnings Conference Call. [Operator Instructions] I would now like to turn the conference over to Mr. Tyler Scott, Vice President, Investor Relations. Please go ahead, sir.

Thank you, operator and good morning, everyone. Welcome to Cognizant's Third Quarter 2025 Earnings Call. I'm joined today by Ravi Kumar, Chief Executive Officer; and Jatin Dalal, Chief Financial Officer. By now, you should have received a copy of the earnings release and investor supplement for our third quarter results. If you have not, copies are available on our website, cognizant.com. Before we begin, I would like to remind you that some of the comments made on today's call and some of the responses to your questions may contain forward-looking statements. These statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Additionally, during our call today, we will reference certain non-GAAP financial measures that we believe provide useful information to our investors. Reconciliations of non-GAAP financial measures where appropriate to the corresponding GAAP measures can be found in the company's earnings release and other filings with the SEC. With that, over to you, Ravi.

Thank you, Tyler and good morning, everyone. Thank you for joining us. We are pleased to report another industry-leading performance in the third quarter of 2025 as revenue growth and adjusted operating margin again outpaced our expectations. Our results reflect the momentum we have built over the past 2.5 years, helping clients embrace AI. Our investments in platforms, intellectual property, partnerships and in upskilling our people are evolving Cognizant into an AI builder, capable of scaling agentic AI across the enterprise. As AI infrastructure expands, our clients increasingly need support from partners who can help them move from experimentation to enterprise-wide adoption with speed, precision and trust. Turning to third quarter highlights. Revenue grew 6.5% year-over-year in constant currency to $5.4 billion. All 4 of our operating segments grew revenue organically year-over-year. This breadth of performance across industries and geographies reflects the strength and resilience of our portfolio of capabilities and delivery model. This is the fifth consecutive quarter of year-over-year organic revenue growth, our strongest sequential organic growth since 2022 and another podium finish to our peer group's Winner's Circle. We signed 6 large deals each with TCV of $100 million or more, bringing our year-to-date total to 16. Trailing 12 months bookings is up 5% year-over-year and year-to-date, the TCV of our large deals is up 40% from the prior year period. We are focused on converting value from AI across our 3,500 early AI engagements and embracing AI in the delivery of our services and to drive internal transformation. As we do this, we are also increasing our fixed bid transaction and outcome-based services mix. And we are beginning to see trends of nonlinearity emerge. For example, on a trailing 12-month basis, revenue per employee rose 8% year-over-year, while adjusting operating margin, income per employee grew 10%. As we continue to scale our IP and platforms, we expect more examples of nonlinear AI-led growth to emerge. Importantly, we are expanding margins while continuing to fund our organic and inorganic growth initiatives and increasing returns to shareholders. Q3 adjusted operating margin improved 70 basis points year-over-year, driven by our disciplined expense management along with our increasingly AI-enabled delivery model. Our year-to-date performance has put us on track to outperform the revenue guidance we established at the beginning of the year and we expect to meet the high end of the adjusted operating margin range we set then. For much of the last 30 years, IT services grew through a linear model. More people and more projects drove incremental growth. AI is reshaping that equation by compressing time, cost and complexity and redefining how value is created. The opportunity to partner with our clients and drive outcomes is now more expansive, immersive and elastic. The progress we are sharing today reflects 2.5 years of focused execution, amplifying talent, scaling innovation and accelerating growth to return Cognizant to a leadership position in the AI era. Becoming an AI builder means building the platforms and engineering capabilities that enable agentic AI to scale across the enterprise. Our progress begins with our workforce as we enable AI influence -- fluency across the 350,000 associates. We continue to fuel strength and future readiness for our associates through our learning engine and access to AI tools, which is why we are hiring more new graduates across the world this year and investing in their AI upskilling. In July, our vibe coding initiative earned Cognizant a Guinness World Records title for the world's largest online generative AI hackathon. More than 53,000 associates across 40 countries built over 30,000 working prototypes, improving their AI code assist skills and productivity. And we are continuing to expand into the AI ecosystem. Recently, we entered a new collaboration with Anthropic. Under our agreement, we plan to deploy Anthropic's cloud models and agentic tooling with our platforms to help clients scale AI while also deploying them internally to advance our own operations. Our AI builder strategy is anchored in 3 distinct vectors: AI-led productivity, industrializing AI and agentifying the enterprise. While each vector is advancing at a different velocity, together, they're forming a flywheel of new value creation. Let me provide an update on Vector 1. AI-led productivity is the funding engine for enterprise transformation as we help clients accelerate software development, lower deployment costs and reduce technical debt that we estimate is costing enterprises hundreds of billions of dollars in annual servicing. In the third quarter, approximately 30% of our internal code was AI generated, significantly improving productivity of our developers. We believe it could reach 50% in the years ahead. A great example to illustrate our client impact with code assist platform partners is a recent award as the AI GitHub Services and Channel Partner of the Year in recognition of our achievements in helping clients with our AI transformation initiatives. Many clients have asked us for support in bringing vibe coding and code assist best practices to their organizations. We recently launched a Cognizant Enterprise Vibe Coding Blueprint, bringing our playbooks and insights to clients seeking to build AI fluency across their own teams. This transformation extends beyond the developer community. Internally, we have embedded AI across more than 150 use cases from finance and operations to sales enablement and contract pricing. These applications are streamlining decision-making, improving accuracy and accelerating cycle times. A primary tool for executing Vector 1 is our Flowsource platform, which integrates generative and agentic AI across the full software development life cycle. Flowsource is now being used at over 70 clients with an additional 120 in the pipeline. One of those clients is Pearson, where we are using AI and digital technologies to modernize their learning platforms, products and applications by leveraging Flowsource. Our proactive shift to AI native and platform-driven engineering accelerates the software development cycle by enabling engineers to deliver enterprise-grade AI-infused digital applications with greater speed and scale. This is showing up in our results with our approximately $2 billion annual run rate digital engineering business growing about 8% organically year-to-date. Vector 1 is also fueling our large deal momentum. As clients consolidate their software estates and shift to outcome-based models, they're capturing savings and unlocking higher value, often, reinvesting those gains into Vector 2 and Vector 3 initiatives. It is creating a self-reinforcing cycle of transformation. A great example of this in action is our cloud and infrastructure modernization business, which grew 10% year-over-year in the quarter. Our AI tooling and services in this space has helped over 25 clients so far to build, respond and resolve to reliant and resilient IT infrastructure. Now more on Vector 2 or industrializing AI as the scalability layer. It's about moving AI beyond experimentation into enterprise-grade systems, building AI-ready infrastructure, integrating contextual data and operationalizing AI responsibly. It also involves developing new business operating models, leading to an interplay of software and agentic layers, human and agentic capital and structured and unstructured data to reimagine an enterprise. We are leading this effort with our consulting basis framework and methodology to help clients reimagine business processes as they develop and deploy agents. And we are deepening our expertise with the next level capability set, including Agent Foundry, a framework and library of the industry and workflow-specific agents, helping power agentic AI at scale. Together with our clients, we have developed more than 1,500 agents across the company. Second, AI data training services, where we have over 10,000 specialists fine-tuning models with domain-specific context. We have supported leading tech companies with training their machine learning systems long before generative AI entered the mainstream and we are now bringing this same expertise to Global 2000 clients. Third, small language models development. Fourth, context engineering, which we believe is one of the most critical emerging disciplines in enterprise AI to capture enterprise workflows, domain and tribal knowledge, personas, rules and execution patterns. It is the connectivity tissue between models and outcomes. In partnership with Workfabric AI, we are deploying context engineers who are helping clients build tailored foundations for AI adoption. And finally, IP on the edge, which I began describing last quarter, is a horizontal foundation layer where we are bundling platforms like Neuro AI with services and IP to deliver outcomes. With 400 platform deployments already in motion, we are helping clients modernize core systems to reduce risk, accelerate time to market and improve experiences. As we build layers of contextual value on foundation models through a combination of context engineering, SLMs and multi-agent systems, we are delivering numerous production-grade AI use cases. To bring this to life, we helped a national grocery chain optimize it in-store pickup process for online orders, reducing fulfillment time by 20% to 45% through smarter inventory selection, product substitutions and routing. This is driving a measurable increase in online orders. Lastly, Vector 3 or agentifying the enterprise is about unlocking exponential agentic capital. Historically, we built software for humans. With agentic AI, we now reimagine processes end-to-end by deploying agents with humans in the loop to deliver outcomes. This expands the enterprise's surface area, enabling a blended human plus agent workforce across new domains. The Agentic Development Lifecycle or ADLC differs fundamentally from the traditional software development cycle or SDLC. SDLC is structured and deterministic, input in, output out. ADLC is adaptive and outcome-driven. You design for behavior, supervise performance and evolve capabilities over time. We believe ADLC significantly expands our addressable market, demanding deep ownership to manage human digital collaboration. As an AI builder, we are creating an agentic ecosystem where agents reason, adopt and collaborate, unlocking service capabilities that weren't possible before. Cognizant is an early launch partner for Google Gemini Enterprise, an AI-powered platform designed for enterprises to drive unified secure AI capabilities. It seamlessly connects enterprise data, tools and workflows and leverages Gemini models to enable agentic journeys. And some client examples include reducing order response times from 5 days to 90 seconds with digital sales agents for a leading food distributor, helping a leading provider of cell-free DNA diagnostics reinvent patient education, access and onboarding processes, modernizing order management for a crop sciences company using Agentforce, delivering intelligent lead generation for a top labeling and a packaging provider. With Tri

Thank you, Ravi and thank you all for joining us. We are pleased to report third quarter results that include revenue growth above the high end of our guidance range, strong margin expansion year-over-year and double-digit adjusted EPS growth. Our performance once again places us in the winner circle and we are delivering these results despite a complex demand environment and geopolitical backdrop. We continue to execute with discipline, driving improved revenue growth while investing in our people, technology and partnership to support our AI builder strategy and long-term growth. At the same time, we are delivering consistent margin expansion. These results are underpinned by balanced capital allocation framework, which we believe are key enablers to driving long-term and sustained shareholder value creation. Now moving to the details of the quarter. In Q3, we delivered revenue of $5.4 billion, up 6.5% year-over-year in constant currency, again led by strong growth in North America. Belcan contributed slightly less than 250 basis points of inorganic growth. Year-to-date, our revenue grew 7.3% in constant currency, including 350 basis points of inorganic growth. Adjusted operating margin expanded 50 basis points and adjusted EPS grew approximately 11%. And we returned about $1.5 billion of capital to shareholders. With respect to demand environment, trends in Q3 were consistent with last quarter. Clients across industries are navigating elevated levels of uncertainty around trade policy and resulting impacts to their businesses. We are also seeing clients carefully evaluate technology investments, which is resulting in a lower pace of discretionary spending in certain areas like products and resources. At the same time, cost pressures continue to spur demand for productivity-led and vendor consolidation opportunity across segments. And we see a growing pipeline of modernization projects that lay the foundation of AI-led transformation for our clients. Now turning to segments. We delivered year-over-year organic growth in all segments in the third quarter. Financial Services led growth driven by healthy discretionary spending in trends, in areas like digital engineering, legacy modernization and generative AI initiatives and improved spending among insurance customers, particularly in North America. Health Sciences was in line with our expectation and has remained resilient despite the uncertainty around government funding and trade policies. While we have seen pockets of discretionary spending pressure, it is being more than offset by the ramp of recent wins in payer and life sciences. Products and Resources revenue growth has improved and we are confident we can build off these levels in the quarters ahead as we expect new deal wins to ramp up more meaningfully in 2026. And Communication, Media and Technology grew organically and benefited from recent large deal wins that more than offset pockets of discretionary spending weakness in the quarter. Geographically, North America once again led growth and was up nearly 8% year-over-year in constant currency, driven by our large deal success and Belcan. Outside of North America, demand trends in Europe and Rest of World remains stable but not immune to impact from recent tariffs and geopolitical uncertainty. Turning to bookings. On the trailing 12-month basis, bookings grew 5% and represented a book-to-bill of 1.3x. After a strong performance of 18% year-over-year growth in Q2, we experienced some lumpiness in the third quarter and bookings declined by about 5% year-over-year. Our trailing 12-month annual contract value, or ACV, growth was consistent with TCV growth. Overall, our backlog remains healthy and our sustained large deal momentum provides us good visibility as we exit 2025. Moving on to margins. Third quarter operating margin of 16% increased by 70 basis points year-over-year, benefiting from NextGen program savings and the Indian rupee depreciation. Utilization held steady at 85% for third consecutive quarter, up from 84% a year ago. These improvements were partially offset by the ramp of large deals and the dilutive impact from Belcan. Voluntary attrition remained low at 14.5%, down 70 basis points sequentially, the third consecutive quarter of sequential decline and down 10 basis points year-over-year. A brief comment on H1B visas. Over the last several years, Cognizant has significantly reduced the dependency on visas while increasing local hiring and our nearshore capacity. We also stepped up our investments in automation and AI productivity tooling. We, therefore, do not expect a material impact to our operation or financial performance in near term as a result of the recent policy changes in the U.S. Now to additional details. During the quarter, we recorded a onetime noncash income tax expense of $390 million or $0.80 per share. As we discussed last quarter, this charge is related to a deferred income tax asset on the balance sheet that is not expected to be realized due to the enactment of the July U.S. budget bill. Adjusted EPS, which excludes this impact, was $1.39, up 11% year-over-year. DSO of 82 days declined 1 day sequentially and increased 1 day year-over-year. Third quarter free cash flow was $1.2 billion and represented 170% of adjusted net income. This compares to free cash flow of $791 million a year ago. As a reminder, cash income taxes in the third quarter were approximately $150 million, lower compared to our projections prior to the passing of the July U.S. budget bill. For the full year, we expect that reduction to be $200 million. Through the first 9 months of 2025, free cash flow is $1.9 billion and represented approximately 100% of adjusted net income. During the third quarter, we returned $600 million of capital to shareholders through share repurchases and dividends, bringing the year-to-date total to approximately $1.5 billion. We are on track with our plan to return $2 billion to shareholders in 2025. This will bring total capital returned to shareholders since 2022 to nearly $5 billion. We ended the quarter with cash and short-term investments of $2.4 billion or net cash of $1.8 billion. Finally, our M&A pipeline remains active and we have ample flexibility to invest strategically in the quarters ahead while continuing to return substantial capital to shareholders. Now turning to our forward guidance. For the fourth quarter, we expect revenue to grow 2.5% to 3.5% year-over-year in constant currency, which is all organic. We, therefore, now expect full year revenue to grow 6% to 6.3% in constant currency, above our prior guidance range of 4% to 6%. We continue to expect full year inorganic contribution of approximately 250 basis points. We are increasing our adjusted operating margin guidance to approximately 15.7%, which is the upper end of our prior guidance and represents 40 basis points of expansion. We continue to expect margin performance will be driven by cost discipline and SG&A leverage. This year, the fourth quarter will include the impact from a merit cycle compared to its Q3 timing last year. This will be partially offset by year-end seasonal margin strength. We continue to expect free cash flow conversion to be approximately 100% of adjusted net income. This includes the benefit from lower cash taxes as a result of the U.S. budget bill discussed earlier. We expect our adjusted tax rate, which excludes the onetime tax charge, to be in 24% to 25% range. Based on our current visibility, we now expect full year tax rate to be closer to the midpoint versus the lower end that we indicated last quarter. We are increasing our EPS guidance to $5.22 to $5.26 compared to our prior range of $5.08 to $5.22. This represents 10% to 11% year-over-year growth. Our expected weighted average diluted share count is unchanged at approximately 489 million. In closing, we are very proud that our guidance puts us on track to meet or exceed the high end of the initial guidance range we provided back in February despite a dynamically changing market compared to the beginning of the year. While we are not commenting on financial expectations for 2026, we feel well positioned to carry this momentum as we look ahead and remain committed to the long-term financial framework we provided at the Investor Day earlier this year. With that, we will open the call for your questions.

[Operator Instructions] And our first question comes from Jim Schneider with Goldman Sachs.

Ravi, I wonder if you could speak to the new business pipeline you're seeing for smaller deals at this stage and whether you're seeing any kind of significant uptick there or not? And then relative to larger deals, are you seeing any pull-in or extension in terms of the commencement date for those large deal new bookings?

Thank you, Jim, for that question. Look, large deals have nicely balanced between the 2 swim lanes I've been talking about. Early on in 2024 and early 2025, a lot of it was consolidation, productivity-led. Now we are seeing a new swim lane evolve, which is AI innovation-led, which is primarily agentic cycles, deploying AI into enterprise landscapes. And therefore, if you've noticed, our digital engineering business has grown at 8% in the last few quarters. Our infrastructure-led AI has grown by 10% in the last few quarters. And our BPO business is rocking. Actually -- it's actually growing at 10% again. And that we are starting to see. So it's a combination of productivity-led, innovation-led. I mean I've always been saying that this is a double engine transformation. While you can apply it on software cycles, get productivity and transfer the lower cost of deployment for higher spend of software, on the other end, you can apply it on -- you can apply agentic capital on enterprises. There's so much of infrastructure spend, which has happened. It has to create a build opportunity. And that's why I keep saying we are an AI builder. So we are seeing discretionary small projects starting to come back in financial services and health care. And that's all related to AI-led spend. So as you save on one side from software cycles, you transfer that money to innovation. So a very healthy pipeline. I'm excited about the large deals. I'm excited about the discretionary coming back on small deals, which is AI-led. I mean so much infrastructure has been spent that it has to trickle down to services. And there's always been a lag between when hardware was spent, then the software, then the services. That cycle has shrunk now and we'll be breaking that cycle. So the services spend is going to catch up because of the extraordinary spend on compute and AI infrastructure.

And our next question comes from Tien-Tsin Huang with JPMorgan.

Nice results. Well done. I wanted to ask on the revenue per employee. It looked like up 8%, operating income also better than that, up 10%. So just understanding the lift there and if it's sustainable and or even structural given some of the AI returns that you talked about.

Thank you so much for the question. In fact, just a follow-up on the previous question. We're also seeing mega deals. Last quarter, we did 2. The quarter before, we did 1. So mega deals are also starting to line up because that savings can be underwritten for innovation. Now coming to your question, this is a interesting lead indicator, revenue per person and margin per person. Revenue per person went up by 8%, margin by person went up by 10%. It's indicative of how we are becoming a AI builder company with platforms, intellectual property, software and services, all bundled together. So we're excited about that. It's a combination of things. Our fixed price managed services business is going up. It has gone up from 43% in 2024 to right now almost close to 47%. That gives us a chance to deliver work for outcomes and therefore, create more revenue per person and margin per person. It is actually going to transition and Jatin has been talking about it, that we are a fixed price, time and material and a transaction-based business. We are going to go from more fixed price, more outcome-based, more transaction-based, less time and material in the future. So productivity has gone up 30%, which means there is more throughput, so you can actually create more throughput, share the savings, lower cost of deployment with our clients. So effectively, putting all this together, this is a very good proxy for AI services. And that's why we thought -- we've been tracking this but we thought we should let analysts and investors know about it.

Yes. [indiscernible] Good proxy, good data point for us to have. Just on the -- my follow-up, then I'll ask on gross margin probably like I usually do. Just thinking about near-term gross margin performance potentially given the expected deal ramps and the mega deals and what have you. Any specific callouts on gross margin in the next couple of quarters?

Sure. Thank you for that question, Tien-Tsin. I would start by saying how we have executed for first 9 months. While you see the headline number a little soft but on gross margin, we have been able to largely maintain the gross margins on an organic basis. The reduction that you see on a year-over-year basis is coming through on account of the consolidation of Belcan, which was expected when we did the deal. So overall, we are quite happy that despite the ramp-up of large deals and investments that we are making, we are able to maintain gross margin in a very narrow range of last year in a organic basis. Going forward also, our endeavor would be to continue to look at 3 or 4 operational levers and the top of that is AI-led productivity that Ravi spoke about. The second is pyramid. You know we have invested 15,000 to 20,000 in recent college graduates.

And it's more than last year.

And it's significantly higher than last year. So we continue to improve the pyramid. And third is utilization, which you can see we have kept it at 85%, now third quarter in a row. It is higher by 1 percentage point compared to quarter 3 of last year. So we feel we are making good progress on gross margin and hopefully, that will continue to reflect in the numbers.

And our next question comes from Maggie Nolan with William Blair.

Can you shed some insight on how you're tracking the success of upskilling your employees with those AI-related skill sets?

Thank you for that question. I mean we are pioneering this effort. Early on, we were the first company and probably the only company which -- in our peer group, which speaks about percentage of code and software development cycles assisted by machines. That's at 30% and we are constantly tracking to stay ahead of the curve. We are the #1 company on GitHub Copilot. In fact, we are the GitHub Copilot AI Partner of the Year. We have been the launch partner for Gemini -- Google Gemini Enterprise. We just signed a deal with Anthropic on cloud. We have created a hustle inside the company that the only way you should write and the only way you should be assisted in software development is through machines. And that has become the way of doing work at Cognizant. In fact, we are on the Guinness Book of Records for the highest number of people on an hackathon concurrently. In fact, we ran that to create culture and create a permanency in the way we write software. We are the only company which is actually saying we are going to hire more school graduates than ever before. We are doubling those numbers from last year because we think we can actually create a significant productivity leap with our extraordinary training infrastructure. So all of this put together, we seem to be on a pioneering opportunity. This is on one swim lane, which is software development. Of course, there is a ton of work on the agentic development, which is much more surface area, much more spend, more expansive. So our double engine, both on productivity and on innovation is deeply embedded with skilling, reskilling, hiring from schools, building productivity alongside machines and that is the only way we want to do -- create throughput. And if we do this well, software has elasticity to be spent more. If we do this well, that money is going to be transitioned to agentic capital and working alongside agents for human workforce, I think, is going to be an amplifying -- amplifying potential of humans. So we have pretty much trained almost all our employees, more than 250,000-plus employees on AI-led skills.

That's helpful. And then should we expect large deal and mega deal signings to impact the quarterly cadence of revenue and margins in 2026? Can you help us think about the ramp over the course of the year from a modeling perspective?

That's a great question. In fact, if you notice, in 2023, our trailing 12 months range of bookings was in the range of $24 billion. And it's now at actually at $27-plus billion. So we've had tailwind from '24 into '25. Our annual contract value is very nicely stacking up to the total contract value. In fact, our total contract value from large and mega deals has gone up by 40%, while the number of deals is 16 and -- so far and we have another quarter to go. Just the TCV value has just significantly gone up. It's gone up by 40%. So we think we have tail velocity going into quarter 4 as well as going into the next year on large and mega deals. I don't see any shift on that. And on the contrary, I actually see that on 2 swim lanes. In '23 and '24, the swim lane was productivity. And in '25, we are starting to see innovation-led, agentic capital-led, much more expansive. I've always been saying one swim lane is software, another swim lane is agentic. The agentic is more expansive, more elastic and more immersive. We are seeing large deals on it. And in '23 and '24, a lot of it was Americas space. Now we are seeing Europe and Asia Pacific starting to be a part of it and we are excited about the momentum we have created in Europe on large deals.

We'll go next to Surinder Thind with Jefferies.

Ravi, can you maybe talk about the partnership strategy here and how important it is to maybe partner with each of the major providers versus maybe being a bit more selective and becoming more of a partner of choice with maybe some of the individual providers, whether it's GCS versus Anthropic or OpenAI or however you're thinking about that strategy?

Surinder, thank you for that question. Partnerships traditionally were SaaS companies and classical software companies, of course, cloud-based hyperscalers as well. Now I would add more things to the mix. I mean, look, SaaS companies and classical software companies will transition the business logic to the agentic layer, which they build on it. I mentioned this in my remarks that the machine was always with the software companies and we were a system integrator. Now we are a AI builder, which means we have intellectual property platforms built. It's a very heterogeneous and a fragmented AI market. Our clients are not saying, come in with your capabilities. They're saying, come in with your machine, which means you have to actually have the platforms. It could be partner-led, it could be our own. And we are actually, therefore, investing into platforms and intellectual property. In addition to that, we have this new thing because now the machine actually belongs to the frontier model companies, which is OpenAI, Anthropic kind of firms. In fact, that's one of the reasons why we partnered with Anthropic. So we are activating multiple swim lanes. Our own custom platforms built on enterprise software companies where we have long-term partnerships, SaaS companies but we also are partnering with frontier model companies because we could create custom AI agentic capital directly. And the Anthropic partnership is an indication of the -- of that particular swim lane. So it's a much broader partnership lens, including start-ups. I mean I work with WRITER, I work with Workfabric AI. These are layers of value on top of the LLM. And some of those layers are owned by us, built by us, some of them are partnered. And of course, the frontier model companies allow us to create a swim lane on -- with the engine actually belonging to them but we build the layers of service around it. So we think it's more expansive and more broad-based.

That's helpful. And then as a follow-up, can you maybe talk about the IP that you're building? And more specifically, you mentioned having upwards of 1,500 agents in production. How does that impact the revenue model at this point? Are you able to charge for some of that? Do you keep some of that IP? Or is it more of a core base and then you kind of custom build agents, that then [indiscernible]

I think it's a combination, Surinder. It's a combination. Look, on Flowsource, which is a platform which sits on top of code assist platforms, it gives us the opportunity to get better productivity and that productivity passes on to our revenue per person and margin per person metrics. Our other IP and platforms we are building are the ability to take the raw power of AI and make it enterprise grade, which means it could be the accuracy of the models. Yesterday, we got a patent on changing the -- on a new way of pretraining a model, not based on reinforcement learning but based on evolution strategies, which our labs got in. So we are building a platform around it. We have a platform around multi-agent systems, which means you could have agents talking to each other. One example is in Tri

And our next question comes from Darrin Peller with Wolfe Research.

Just a financial question first. Just when I look at the guide of 2.5% to 3.5% constant currency for fourth quarter, just what are the puts and takes there? Any early insights into how budgets are shaping up also into '26 would be helpful.

So as you can imagine, difficult to call about -- talk about '26 at this juncture. We will come back in January and speak about it. But overall, there is no major change in the demand environment. We continue to win share and that is reflected in the superior execution of the quarter that went by. Quarter 4 seems to be a customary quarter 4 with its lower number of bill days and furlough. Nothing out of ordinary. Our guidance range reflects, essentially if things could go a little worse, then it's the bottom end. And if we can get some additional momentum in revenue and bookings, then it's the upper end. So that's how we have worked through quarter 4 and that's the full year guidance.

Just one quick addition there. I would say, look, the activation of AI-led innovation use cases, we've gone from 2,500 to 3,500 this quarter. So literally 40% jump. So the money you save on the software cycles on productivity is going to be underwritten to innovation cycles. That is triggering off very well. And I don't think CIOs are saying they're going to cut their budgets. Nobody has told me that. They're all going to -- they're all saying, how can you give me more value? And that's why we are benefiting out of this.

Okay. That's helpful. And then maybe just one quick follow-up would be if you could just discuss -- just you're obviously doing well with larger deals, maybe just discuss the competitive dynamics for some of the large deals you're seeing and what's allowing you guys to continue winning them? And then how important is price in the discussion and maybe build into that what AI can do for you on pricing, if you could pass through some of your savings into this?

Yes. Look, price was always a linear thing in the past because it was labor related and productivity of tooling was not in the mix. I would say it was a minority. Right now, pricing is productivity-led and it depends on how much you can use your platforms and how much you can use your AI tooling and the culture we have established now. So pricing is kind of linked to how fast we can keep that runway on productivity. Large deals on consolidation and productivity will always be price sensitive because they're done for savings and creating more velocity. The innovation side of it, I mean, that's going to be much more -- that's going to be less sensitive to price because you are actually delivering new products and new services using AI. I don't see much of a change in the pricing. I would actually say if the other swim lane gets activated, which is innovation-led, you will get the strength behind the pricing.

And our next question comes from Yogesh Aggarwal with HSBC Bank.

Just have a question actually totally disconnected to the quarter and demand, et cetera. Just in the past few quarters, Cognizant performance has consistently improved and now you're growing almost at the top end of the peer range. But I'm sure you would have noticed as well the stock still is at a significant discount to the peer group. So just curious, any thoughts on secondary listing in India? I mean, is it something on the table and any puts and takes for the same? Just curious to know your thoughts, please.

Yes. So Yogesh, thank you. That is an interesting question. Cognizant's Board and management team regularly assess opportunities to enhance the shareholder value. Towards this end, we have been assessing a potential primary offering and a secondary listing in India with our legal and financial advisers. As part of this comprehensive review, which is still in its early phase, we are engaging various stakeholders from both India and U.S. to evaluate the implications of such a potential offering and listing. The process of a primary offering and a secondary listing in India by an overseas company is complex and involves multiple steps. We view this as a long-term project. While no decision has been made and any offering and secondary listing would be subject to market and other factors, we continue to assess and review the idea and are committed to acting in the best interest of our shareholders. So that's our response, Yogesh.

Our next caller comes from Rod Bourgeois with DeepDive Equity Research.

All right. Yes, guys. So I want to talk for a second about Financial Services vertical. You mentioned improved spending there. We are seeing some of that across the broader sector. Can you speak to what form that improved spending is taking in the Financial Services vertical? And in particular, are you now seeing those clients moving beyond AI for cost savings and into more AI-based reinvention at those clients?

Thank you, Rod, for that question. Absolutely. I think this is probably my fourth or fifth quarter where we have done year-over-year growth as well as from the start of the year, we've been sequentially growing in Financial Services. It's been one of our best-performing industry groups. I think the spend has gradually transitioned from cost takeout consolidation to more innovation. I would say if you take the 3,500 projects we are doing on AI-led innovation, a significant chunk are actually moving from experimentation to enterprise-grade AI. And all the platforms I'm speaking about in the call, a lot of them are getting implemented in Financial Services. In fact, insurance, which is a part of BFSI has also started to spend. It's a sector which kind of was lagging a little bit but it has started to spend as well. So we are very, very excited about the future of Financial Services. Over the last few years, Cognizant per se, we have had quarters where we haven't performed in the previous years. But from -- the turnaround has started from the middle of, I would say, 2024. And here we are, it is actually one of -- it is actually our best-performing industry group. The spend cycles are great and clients are actually innovating much more. Every segment of Financial Services has accelerated in terms of spend and the discretionary is coming back because the value you get out of discretionary now is much higher because the cost of capital is high but the deployment costs have gone down. So that is giving clients the confidence to experiment more and actually take it to production. So Financial Services will be one of our bellwether industries in the -- in 2026 as well.

Great. And then moving to health care. I mean, there's been some policy uncertainty in that vertical. You've also got the Tri

Absolutely, absolutely. In fact, if you look at health care, I mean, if you take the last 20 years, the number of surgeons and the number of doctors has pretty much remained flat. But if you look at administrative costs, they've probably got up like 600% to 700%, number of administrators in that business. So transitioning that spend to predictive care, I think, is the future. We have 200 million-plus members on our Tri

We'll go next to Jonathan Lee with Guggenheim Partners.

Good to see the outperformance here. You called out last quarter that you were expecting the 4Q exit rate to be just under 4% at the high end of the outlook range. Given the outperformance this quarter, can you help bridge the gap between the 3.5% at the high end of your 4Q outlook today and the 4% exit rate you pointed to last quarter?

Yes. I think this is in -- 2.5% to 3.5% is the view that we have of quarter 4 as we look at next few -- next couple of months. It is -- we have great momentum in terms of winning the large deals. We have been able to execute better in quarter 3. And that will really decide -- I mean, continued momentum on those factors will really decide where 2026 comes through. But overall, we are very happy with the way we have executed 2025. As I spoke in my opening remarks, when we gave guidance, since then the environment has been very, very dynamic and still to be able to come in the last quarter and guide above the original guidance range is very heartening. So we have executed well and we hope we'll continue to do so as we move forward.

Can you help us also better understand your pyramid initiatives and how you're balancing the needs of clients while managing margins, particularly as you move into higher-value AI-related work in Vectors 2 and 3 that may require higher skilled talent beyond that of freshers?

So we have been very vocal about that -- about the fact that we see actually freshers and AI, a very complementary strategy. And we believe that expanding pyramid at the bottom in our industry really helps us accelerate the organization's journey on AI. So from that context, we more than doubled this year, the number of freshers we took last year to this year. And that journey will continue; one, from a cost management standpoint of pyramid but even greater context is how we can accelerate the enterprise to become more AI-ready and AI builder as Ravi spoke about.

And also, we are now hiring freshers in the markets, which is primarily our principal market being U.S. So we are doubling down on this with a broader pyramid and a shorter path to expertise.

Thank you. And that does conclude our question-and-answer session. I would like to turn the floor back over to Ravi Kumar for closing comments.

Thank you so much for joining us today. We are very excited about our strategy of being an AI builder company, which is a combination of AI-led capability, platforms, intellectual property and partnerships, which allow us to be on those 2 swim lanes, one on productivity, one on AI-led innovation with a much expansive, elastic and a more immersive opportunity to serve our clients. So we're very, very excited about our future and thank you again for listening to us today.