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 a total contract value of $100 million or more, bringing our year-to-date total to 16. Trailing 12 months bookings are up 5% year-over-year and year-to-date, the total contract value 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 adjusted 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, 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 connective 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, small language models 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 its 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 and 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 packaging provider. With TriZetto's core adjudication platform supporting health plans, we have deployed multi-agent workflows that connect TriZetto agents to front-end experience platforms such as Salesforce, Genesys and ServiceNow to address common interactions such as requesting ID cards from a member or giving providers the status of a claim. We believe much of Vector 3 will flow into intuitive operations and automation practice, which is our BPO business, including BPaaS services. Our BPO revenue grew 10% in the last 2 quarters and is on track to reach $3 billion in annualized revenue over the next several quarters. We believe agentification will unlock new labor pools, including roles that don't yet exist. As digital labor diffuses into enterprise operations, the nature of human endeavor will evolve. Together, our work across Vector 1, 2, and 3 reflects our evolution into an AI builder company, one that blends deep domain expertise with platform innovation and interdisciplinary talent. 30 years ago, IT services companies were builders, crafting the foundational systems that powered industries. Over time, that role shifted towards integration, development and maintenance and growth became more linear. Today, Cognizant has a unique opportunity to reclaim the builder mindset and capture a greater share of the fragmented AI market. The scale of this opportunity is extraordinary. While the global software market is in the hundreds of billions of dollars, the surrounding labor spend represents many trillions more. Classical software has barely penetrated that space. We believe AI's winners will be those who diffuse into this labor spend, reshape how work gets done. Software and agent development cycles will coexist and Cognizant is poised to generate layers of value in this expansive new role for enterprise reimagination. In closing, we are proud of our Q3 results and the momentum we are building financially, commercially and strategically. We are evolving from software implementer to AI builder powered by an engineering heritage and AI-ready workforce and proprietary innovation. We know long-term success will be determined by the outcomes we deliver for our clients, our people and our shareholders. Thank you again for joining us. I'll now turn the call over to Jatin.

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's 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 a 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 the 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 opportunities across segments. And we see a growing pipeline of modernization projects that lay the foundation for 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 and 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 expectations 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 remain stable but not immune to impacts 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 1.3 times. 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. The 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 the 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 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 one-time non-cash 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 one-time tax charge, to be in the 24% to 25% range. Based on our current visibility, we now expect the 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.

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. Large deals have been well balanced between the two areas I've mentioned. In early 2024 and early 2025, much of it was focused on consolidation and productivity. Now, we are witnessing the emergence of a new area driven by AI innovation, particularly in deploying AI within enterprise environments. Our digital engineering business has seen an 8% growth in the last few quarters, while our infrastructure-led AI has increased by 10%. Our BPO business is also doing very well, achieving another 10% growth. It's a blend of productivity and innovation. I've always stated that this is a dual-engine transformation. You can enhance software cycles for productivity, reducing deployment costs and allowing for greater software investment. Additionally, there's significant infrastructure spending, which creates opportunities for growth. That is why I emphasize that we are an AI builder. We are noticing a resurgence in smaller discretionary projects within financial services and healthcare, all tied to AI-related expenditures. As savings are generated from software cycles, that capital is redirected towards innovation. The pipeline looks very promising. I'm enthusiastic about the large deals and the resurgence of smaller AI-driven projects. With the substantial infrastructure investment made, it is bound to lead to increased service demand. Traditionally, there has been a lag when transitioning from hardware expenditure to software and then to services. However, that cycle has shortened, and we will disrupt it. The spending on services will accelerate due to the exceptional investment in computing 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 for the question. To follow up on the previous inquiry, we are observing a rise in large deals. In the last quarter, we closed two, and the quarter before that, we had one. These substantial agreements are beginning to accumulate, allowing savings to be invested in innovation. Regarding your question, the increase in revenue per employee and margin per employee serves as an interesting lead indicator. Revenue per employee increased by 8%, while margin per employee rose by 10%. This reflects our evolution into an AI-driven company, integrating platforms, intellectual property, software, and services. We are enthusiastic about this development. Our fixed-price managed services division has grown from 43% in 2024 to nearly 47% now, enabling us to deliver work focused on outcomes, thereby enhancing revenue and margin per employee. We are transitioning towards a business model that is increasingly fixed-price, outcome-based, and transaction-oriented, while reducing our reliance on time and materials. Productivity has improved by 30%, which translates to increased throughput, allowing us to share savings and minimize deployment costs for our clients. Ultimately, this aligns well with AI services, and we believe it is essential for analysts and investors to be aware of these trends.

Yes, it's a good data point for us to have. As a follow-up, I want to ask about gross margin, which is something I usually do. I'm considering the near-term gross margin performance, especially with the expected deal ramps and mega deals. Are there any specific updates on gross margin for the next couple of quarters?

Sure. Thank you for that question, Tien-Tsin. I would start by saying how we have executed for the 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 on an 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 the 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 your question. We are leading the way in this initiative. Initially, we were the first, and possibly the only, company in our peer group to report that 30% of our code and software development cycles are supported by machines. We continuously monitor our progress to remain at the forefront. We rank as the top company on GitHub Copilot and have been recognized as the GitHub Copilot AI Partner of the Year. Additionally, we were a launch partner for Google Gemini Enterprise and recently signed a deal with Anthropic for cloud services. We've fostered a culture within the company where machine-assisted software development is the norm. This approach has become integral to our operations at Cognizant. Our participation in a large-scale hackathon earned us a spot in the Guinness Book of Records for the highest number of concurrent participants, which aimed to cultivate a lasting culture around software development practices. Moreover, we are committed to hiring more recent graduates than ever, effectively doubling our numbers from last year, as we believe this will result in significant productivity gains through our robust training infrastructure. Altogether, we are presented with a unique opportunity in software development. Alongside this, we are also focused on agentic development, which encompasses broader applications, increased spending, and more expansive reach. Our dual approach—enhancing productivity and fostering innovation—integrates skilling, reskilling, hiring young talent, and increasing productivity through machine collaboration. If executed successfully, this will allow for more investment in software. Ultimately, this funding will convert into agentic capital, augmenting the capabilities of the human workforce. We have trained over 250,000 of our employees in AI-related 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 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 in the 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 with 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 an 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 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 large language models. 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 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. As a follow-up, could you discuss the intellectual property you're developing? Specifically, you mentioned having more than 1,500 agents in production. How does this affect your revenue model at this stage? Are you able to monetize some of that? Do you retain any of that intellectual property? Or is it primarily a core offering, with custom-built agents on top of it?

I believe it's a mix of factors. On Flowsource, which functions as a platform overlay on code assist platforms, we have the chance to enhance productivity. This improved productivity directly influences our revenue and margin metrics per employee. We are also developing other intellectual properties and platforms that leverage the core capabilities of AI and elevate them to an enterprise level, ensuring model accuracy among other things. Just yesterday, we received a patent for a novel method of pretraining a model based on evolution strategies instead of reinforcement learning. Our team is constructing a platform surrounding this concept. We also have a multi-agent systems platform, where different agents can interact with each other. For instance, in TriZetto, our agents communicate with Salesforce agents, Genesys, and ServiceNow agents, automating outcomes like issuing ID cards, checking claim status, and adjudicating claims, among other functions. All our platforms aim to harness the power of AI to meet enterprise-grade standards, whether in terms of accuracy, responsible AI practices, or innovative pretraining approaches, addressing the various requirements for enterprise applications. There has been significant infrastructure investment recently, and this value must filter down to practical use cases. Thanks to our developed intellectual property, we can now generate more production-grade solutions. We are also closely observing our partnerships, particularly in the context engineering area, which presents a unique opportunity for us. We are in a contextual computing era, where providing context—such as tribal knowledge, workflows, data streams, and organizational nuances—into large language models allows us to create contextual agents that outperform generic ones. This process is evolving and requires scientific development, so we are building intellectual property alongside one of our partners. I see our future as a blend of platforms and capabilities, marking our evolution from a capability-focused business to a platforms plus capability model. Historically, we've embraced this approach in our healthcare business, particularly with TriZetto, which integrates platforms with services.

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 the 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.

It is challenging to discuss 2026 at this time. We will revisit it in January. However, there hasn’t been a significant change in the demand environment. We are gaining market share, which is evident from our strong performance in the past quarter. The fourth quarter appears to follow typical patterns with fewer billable days and furloughs, nothing unusual. Our guidance indicates that if conditions worsen, we are at the lower end, while increased revenue and bookings could push us to the upper end. This outlines our approach for the fourth quarter and the full year guidance.

Just one quick addition there. I would say that the activation of AI-led innovation use cases has increased from 2,500 to 3,500 this quarter, representing a 40% jump. The savings from software cycles on productivity will be redirected to innovation cycles, which is progressing very well. Additionally, CIOs are not indicating that they plan to cut their budgets; instead, they are asking how they can receive more value. That’s why we are seeing benefits from this situation.

Okay. That's helpful. And then maybe just one quick follow-up would be if you could just discuss your success with larger deals and the competitive dynamics surrounding them. What is allowing you to continue winning these deals? Also, how important is price in these discussions, and can you elaborate on how AI may assist you with pricing, particularly in terms of passing along any savings?

Pricing used to be linear in the past, primarily tied to labor costs, with productivity from tooling being a minor factor. Currently, pricing is driven by productivity, which depends on how effectively we utilize our platforms and AI tooling, alongside the culture we've developed. Therefore, pricing is closely related to our ability to maintain productivity. Large deals focused on consolidation and productivity are always sensitive to price since they aim for cost savings and increased efficiency. On the innovation front, pricing becomes less sensitive because we are introducing new products and services driven by AI. I don't anticipate significant changes in pricing; if we activate the innovation-led approach, it will strengthen our pricing strategy.

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 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 the 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 the 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 your question. Yes, this is likely my fourth or fifth quarter of experiencing year-over-year growth, as well as sequential growth since the beginning of the year in Financial Services. This sector has been one of our top performers. The spending has gradually shifted from cost savings and consolidation to more innovative projects. Regarding the 3,500 AI-led innovation projects we are working on, many are transitioning from experimentation to enterprise-grade AI. Many of the platforms discussed in this call are being implemented in Financial Services. Additionally, the insurance segment within BFSI, which had been lagging, has also begun to increase its spending. We are very optimistic about the future of Financial Services. In recent years, Cognizant has faced quarters of underperformance. However, we have seen a turnaround starting around mid-2024, and Financial Services is now one of our best-performing industry groups. The spending cycles are promising, and clients are innovating significantly more. Every segment within Financial Services is ramping up its spending, and discretionary spending is returning as the value derived from it is much greater now, given the high cost of capital and lower deployment costs. This has instilled confidence in clients to experiment more and take projects into production. We anticipate that Financial Services will continue to be one of our leading industries through 2026.

Great. And then moving to health care. I mean, there's been some policy uncertainty in that vertical. You've also got the TriZetto asset. Just can you speak a little bit about the outlook for the health care vertical in general? And in particular, with TriZetto and all of the AI work that you're doing, are you seeing BPaaS as an increased opportunity there? Just any color on the health care outlook.

In the health care sector, the number of surgeons and doctors has remained stable over the past 20 years, while administrative costs have surged by 600% to 700%, leading to a rise in the number of administrators. I believe that shifting spending towards predictive care is crucial for the future. We currently have over 200 million members using our TriZetto platform, and we dominate the BPaaS cycle. BPaaS has become our most sought-after offering, allowing us to share our platforms while leveraging our operational capabilities in health care. This has contributed to our BPO business growing by over 10% this year. We are extremely enthusiastic about our BPaaS offering, the AI advancements in our TriZetto service, and our leading position in the U.S. health care market.

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. We estimate that for the fourth quarter, the growth rate will be between 2.5% and 3.5% as we look ahead to the next few months. We are experiencing strong momentum in securing large deals and have improved our execution in the third quarter. This ongoing momentum will be crucial for our performance in 2026. Overall, we are pleased with our execution in 2025. As I mentioned in my opening remarks during our guidance, the environment has been quite dynamic since then, and it is encouraging that we can guide above our original expectations for the last quarter. We have performed well, and we hope to maintain this performance moving 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?

We have openly expressed our view that freshers and AI represent a complementary approach. We believe that expanding the base of our workforce in the industry significantly enhances our progress towards AI integration. This year, we more than doubled the number of freshers we brought on board compared to last year, and this initiative will persist. This is not only about managing costs at the foundational level but also about how we can help the organization become more prepared for AI development, as Ravi mentioned.

And also, we are now hiring freshers in the markets, which is primarily our principal market being the 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.

Thank you. This concludes today's Cognizant Technology Solutions Third Quarter 2025 Earnings Conference Call. You may now disconnect.