Cognizant Technology Solutions Corporation

Welcome to the Cognizant Technology Solutions third quarter 2026 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you'd like to ask a question at that time, please press star 1 on your telephone keypad. A confirmation tone will indicate your line is in the question queue. You may press star 2 if you'd like to remove your question from the queue. For participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. Thank you. I would now like to turn the call over to Mr. Tyler Scott, Senior Vice President, Investor Relations. Please go ahead, sir.

Thank you, operator, and good morning, everyone. Welcome to Cognizant's third quarter 2026 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. 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 for 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. Good morning, everyone. Thank you for joining us. We delivered a solid third quarter while advancing our AI builder strategy. Revenue was in line with our expectations and adjusted operating margins reached its highest level in four years, reflecting continued execution in a rapidly evolving market. We maintain strong momentum in financial services where clients are increasingly using AI to accelerate modernization and address new areas of demand powered by AI-led innovation cycles. We are building the deployment capacity and differentiated capabilities that we believe can help clients move AI into production at enterprise scale and capture more of its value. And we see an opportunity to capture more of that value through platforms as well as deployment services. Looking at the quarter's highlights, revenue grew 4.8% Y&Y in constant currency, led by strong performance in North America, including contribution from our recent three cloud and Astria acquisitions and our integrated offering strategy. Financial services accelerated to 12% year-over-year constant currency growth, its third consecutive quarter of double-digit growth. Communications, Media and Technology also grew double digits driven by inorganic contributions from Astria and strong spending from technology clients. Trailing 12 months bookings increased 4% with the mix of new versus expanded business growing over 10 percentage points year over year to 60%. We signed three large deals with TCV of more than 100 million each while the combined trailing 12 months TCV of large deals increased 9% year over year and adjusted operating margin increased year-over-year to 16.3%, the seventh consecutive quarter of year-over-year expansion. We also continue to see indicators that AI is changing our operating model. Revenue and adjusted operating income per associate excluding Gen C trainees increased more than 3% and 5% respectively. To the end of quarter three, we estimate more than 50% of our software development was AI-assisted, and we have over 8,500 AI engagements. We achieved these results in a complex demand environment. Although macroeconomic conditions were largely stable in the third quarter, we are seeing the macro uncertainty weigh more on discretionary spending in the fourth quarter, particularly in healthcare and consumer-facing sectors. We have reflected these factors in our updated full year guidance, which Jatin will cover in more detail. Despite these factors, we are still delivering revenue growth that ranks among the top of our peer group. Against this backdrop, our strategy and actions are aimed at building the necessary capacity to deploy AI at enterprise scale, capturing more of the value between AI intelligence and the enterprise, and applying these capabilities to the areas where we see the greatest growth opportunities. Historically, major technology transitions required capacity to deploy new technology at scale. We are building that capacity across our talent engineering platforms and partner ecosystem with leading frontier AI companies, hyperscalers and enterprise technology providers. More than 45,000 Cognizant associates have earned more than 95,000 certifications across frontier AI platforms and another 65,000 plus are in progress. We recently expanded our Google Cloud partnership with a new Gemini frontier capability group bringing together more than 18,000 dedicated cognizant associates focused on legacy modernization, developer experience, autonomous business processes, and frontier cyber defense. We're also proud of the strong momentum created through our Gemini partner event where more than 55,000 associates completed Build with Gemini, the largest Gemini partner workshop to date. With this deployment capacity in place, we believe our larger opportunity lies in helping enterprises turn AI intelligence into differentiated business value. As AI moves into production, that value increasingly comes from reimagining how work gets done, providing the enterprise context AI needs to operate effectively, and build the trust and governance required to deploy it at scale. Our AI builder strategy is designed to bridge this gap between AI capability and enterprise value through four connected areas. First, reimagining how work gets done. This starts with redesigning business workflows, operations, and roles around what AI now makes possible in new cognizant proprietary methodology in agile pods engaged in reimagination and reinvention of business landscapes. Work once handled by software systems and human teams will increasingly be performed by a new combination of systems, people, and AI agents. We have pioneered the discipline of context engineering to develop our associates expertise in this discipline. And we believe we are building the specialized engineering capacity needed to build agentic systems at scale. Second, engineering enterprise grade AI. Putting reimagined work into production as bespoke agentic systems requires enterprise grade systems, meaning governed, trustworthy, safe, and grounded in the enterprise context. This is an area where we believe our platforms will play a critical role. This allows us to embed our capabilities and IP directly into delivery, scale them across clients, and increasingly bend the cost curve. Our platform opportunity rests across two pillars. First, engineering platforms support the end-to-end engineering lifecycle through AI-led engineering and modernization. Second, business platforms apply to repeatable business processes particularly bounded workflows where AI can increasingly perform and improve the work. The third area of our AI builder strategy is building the capacity to help clients absorb AI. Effective enterprise AI adoption requires the right skills, tools, and ways of working. We are putting into this practice inside Cognizant through SkillSpring, our AI native learning platform, which is now used by approximately 315,000 associates. We're also making the platform available to clients that are building an active pipeline of opportunities. Finally, compounding and protecting institutional intelligence. As AI is embedded in more workflows, enterprises need greater visibility into and control over how AI is used while protecting their institutional intelligence and sovereignty. We recently launched Cognizant AI Nexus, a modular multimodal operating layer that helps enterprises govern AI quality, manage spend, coach in real time, compound repeatable patterns, and connect AI consumption to business outcomes across teams. It illustrates how we aim to help clients manage AI as an enterprise capability while learning from its use and making that institutional intelligence more valuable over time. Together, these four elements of our AI builder strategy are designed to help clients turn AI capabilities into enterprise value while positioning Cognizant to capture more of that value. Now let me discuss how our AI builder expands the opportunity for cognizant in three areas. First, AI-led productivity and autonomous software engineering, which is increasingly becoming the baseline for how we deliver our traditional work. Second, old things in new ways, which is using AI to perform existing work in fundamentally new ways, changing the economics of modernization and enterprise workflows. And third, new things in new ways. AI creates enterprise new services Thank you very much. Notably, we have aligned our software engineering group portfolio around AI-led software engineering and modernization. This shifts the group's focus from engineering disciplines to client outcomes, industry context, and frontier capabilities. We expect this shift will improve how we build and deploy AI-native capabilities while giving associates clearer paths to develop frontier expertise. In parallel, we are evolving our workforce, building frontier roles around the capabilities needed to design, deploy, and operate AI Native Solutions. These roles combine engineering, AI fluency, and business expertise with greater accountability for client outcomes. And they're complemented by our investments while leading frontier AI partners I discussed earlier. We're also adding capabilities through targeted acquisitions. Last week, we announced our intent to acquire Australia-based Diflex Solutions, an SAP platinum partner to deepen our SAP expertise and strengthen our Ability to help clients across Australia and New Zealand modernizing their core platforms. Our commercial model is also evolving. As human and digital labor increasingly converge in delivery, we see more opportunities for outcome-based pricing, AI-infused rate cards, and platform monetization. More broadly, our mix of fixed price and transaction-based work is steadily increasing. In the third quarter, this mix was nearly 58% of our revenue, up 140 basis points year over year, and more than 500 basis points since the third quarter of 2022. And we are expanding the reach of these capabilities. This month, we announced Cognizant Activate, which is designed to bring enterprise-grade AI transformation to emerging high-growth mid-market companies aspiring to reach the global 2000 scale with an operating model purpose-built for the size Next, as we evolve our operating model, the AI disruption has created the immediate next wave of client opportunities. And accordingly, we have identified four strategic growth priorities that we believe can drive disproportionate growth. Modernization, agentifying core business operations, secure AI, and data center and workplace services. Together, we believe these represent a multi-billion dollar opportunity in the years ahead. We are focusing our investments and efforts in these areas with partnerships playing an important role. First, starting with modernization. AI is changing the speed and economics of modernizing legacy technology data and enterprise applications. For example, we expanded a decade-long relationship with Gilead Sciences through a new five-year agreement supporting the responsible application of agentic AI across selected programs, simplifying processes and improving software delivery. At Travelplot, We completed the first phase of the AI transformation we announced with Anthropic in May, establishing the platform's architecture and engineering practices needed to modernize its technology environment. At Odyssey Logistics, a global logistics provider, Cognizant used autonomous AI engineering to rebuild Odyssey's transportation management platform, resulting in a 37% net savings compared with the conventional approach. The second strategic growth opportunity is agentifying core business operations. We see a significant potential to reimagine workflows with agentic AI and our platform strategy. As I mentioned earlier, we will prioritize bounded workflows. Bounded workflows are primarily built on four principles, structured inputs, measurable outcomes, high transaction volumes, and short feedback loops. Our investments in the space are based on our external market study and we are initially concentrating on key areas where we believe we have the right to win with our domain strength and thereby significantly create potential for frontier-enabled platforms. These include long-term care as an adjacency to our existing healthcare platforms, mortgage operations, drug safety, and pharmacovigilance, insurance operations, and the frontier finance function. We will start with these segments and as we make progress, we'll continue to identify more segments for building frontier-enabled platforms and services. A few early examples are as follows. First, healthcare claims. We recently introduced agentic workflow processing for Trizetto that allows AI agents to automatically clear eligible routine-pended claims while routine exceptions to human reviewers. It is designed to reduce manual intervention while preserving human judgment where it's needed. At CETA, A global specialist in air transport technology, we are helping build a frontier finance function on a modern cloud platform spanning finance, procurement, and supply chain. Cognizant will work with CETA to implement a cloud-based ERP and management platform. The goal is to move finance beyond reporting and transaction processing towards a more strategic role built around data, AI, and measurable business value. Next, for the European Bank, For reconstruction and development, we are applying AI across a complex, highly governed technology environment, combining AI-enabled delivery and platforms, including Neuro, FlowSource, and WorkNext, through outcome-led managed services and fixed-capacity services models. And at Talcott, we helped modernize its corporate and bank-owned life insurance business operations by launching a next-generation technology Policy Administration Platform. We embedded governed AI across the delivery cycle from requirements and design to engineering, testing, and implementation driving 30% productivity gains. Our third strategic priority is secure AI. If AI is embedded more deeply across enterprise systems and workflows, trust and security becomes prerequisites for scaled adoption. While securing agentic systems unlocks new demand, we are equally excited about The ability to leverage frontier intelligence for vulnerability discovery and remediating and refactoring existing landscapes with frontier intelligence being a much bigger opportunity. Our cybersecurity business is our fastest growing service line. We are building our capabilities through our neuro AI trust platform and frontier cyber defense workforce. As an inaugural member of the OpenAI's Daybreak Cyber Thank you very much. Finally, the fourth strategic priority is data center and workplace services. The trillions of dollars being spent on AI infrastructure build-out creates opportunities across data center operations, networks, AI environments, and digital workplace services. Our Astra acquisition strengthens our ability to serve this market and show early momentum during the quarter, including an expanded engagement with Google. Beyond these four strategic growth priorities, we are building capabilities in the emerging area of physical AI, We recently signed an agreement with one of North America's largest utility companies to deploy our flagship physical AI platforms, Cognizant Intelligence Pine and Autonomous All-Domain Awareness for Utilities. Together, we aim to fuse sensor, vision, and edge intelligence into a single real-time view to enhance wildfire prevention and grid safety and to accelerate multi-agent coordination and field response. We see a healthy pipeline of similar opportunities in asset-heavy industries like manufacturing, Life Sciences, Retail, and Consumer Sectors. We continue to keep this flywheel running on identifying new waves of demand by sensing, incubating, and scaling for the next set of opportunities unlocked by AI disruption. In summary, we view agentic AI as the most significant enterprise opportunity since digitization, and clients are increasingly focused on converting their AI investments into measurable business outcomes. We believe our AI builder strategy expands the opportunity ahead and opens Multiple revenues for growth, particularly across the four strategic priorities I outlined today. We continue to strengthen our core business while investing in the capabilities, talent, and platforms needed to deploy AI at enterprise scale. We are doing this while delivering top-tier revenue growth, expanding margins, and EPS growth ahead of revenue growth. And we remain focused on disciplined execution and creating durable long-term value for our shareholders. Thank you to our associates, clients, partners, and shareholders for your continued support. Now I'll turn the call to Jatin.