Ravi Kumar S
Analyst · Wells Fargo
Thank you, Tyler. Good morning, everyone. Thank you for joining us. We delivered a solid first quarter with revenue growth in the upper half of our guidance range, expanded adjusting operating margin and strong bookings growth. I believe our work to become the world's permanent AI builder is resonating, demonstrated by our first quarter performance. Looking at the quarter's highlights. Revenue grew 3.9% year-over-year in constant currency, led by strong performance in North America and driven in part by the ramp of recently won large deals. From a segment standpoint, Financial Services grew more than 10% year-over-year in constant currency, driven by strong demand across banking and insurance clients. Q1 bookings grew 21% year-over-year. We signed 7 large deals with TCV of $100 million or greater, including 1 mega deal valued at more than $500 million. Importantly, we continue to drive profitable growth as adjusted operating margin expanded year-over-year for the fifth straight quarter. Adjusted EPS of about 14% year-over-year was ahead of revenue growth. And we just announced a definitive agreement to acquire [ Atria ], a global IT managed services provider and a specialist in AI infrastructure build-out with deep expertise in managing data center infrastructure, enterprise networks and digital workplace technology. Upon closing, we believe [indiscernible] will add a critical layer to our AI Builder technology stack. We achieved these results against a softening demand environment. Market conditions have become more complex since the start of the year, and we expect the impact from heightened macroeconomic uncertainty to persist in the near term. However, while clients are appropriately cautious about making large investments in this environment, they recognize AI's transformative potential and the value of strategic partners. This transformative potential is reforcing our industry's first principles, which underpin our evolving posture as an AI builder. The industry's first principles were born out of an enterprise reality. Technology was so transformational and complex that companies needed help with optimizing the use of technology to meet their business objectives. IT services companies emerged to solve these problems at scale and over time, helped create many of the greatest business architectures over the last 50 years. With AI, the fundamentals are shifting. Software is penetrating deeper into enterprises and our clients now expect more value and measurable outcomes. The old fundamentals are still relevant, but there must be reforge for a new reality. Cognizant has already embarked on this transition, which demands four significant shifts that redefine the role of IT services firms. First, we are evolving towards owning the full stack of capabilities required to design holistic bespoke AI systems from a system integrator to an AI build. Second, we are reimagining our talent moving away from the traditional pyramid towards interdisciplinary teams that operate at the intersection of domain operations and technology. Third, we are shifting our economics from labor base to outcome-based models that align our success directly with our clients. Our combined fixed price and transaction-based portfolio has continued to grow in proportion over the past 3 years, reflecting our ongoing focus on driving nonlinear revenue opportunities. And finally, we are evolving away from simply delivering projects to underwriting operational results for our clients at scale, taking full accountability for the business impact we create. Last quarter, I talked about the velocity gap the gap between massive AI infrastructure spend and the business value realization. And our Cognizant's mission is to be the AI builder who bridges this gap. Our AI builder stack is the connectivity tissue that translates our strategy into measurable client outcomes. It combines our proprietary methodologies and the science of context engineering with a curated ecosystem of strategic partners and our own differentiated platforms and IP. Our vision is to reimagine enterprise operations, rebuild workflows and break functional silos to unlock AI native ways of working. We aim to do this by bringing human effort and Agentic capital together in a managed governed and a client contextual delivery model. Some of our pioneering clients have started to progress from AI productivity to unlocking new experiences, products and services. Platforms are key to our AI builder stack. Fueling our platform strategies, our award-winning AI Labs, which was awarded 3 new patents, bringing its total number of patents to 65 in the U.S. and the 88 globally. Our AI lab continues to sense the future and partner closely with our clients, platforms and products group, and solutions teams to translate frontier research into industry relevant use cases. To complement our internal investments, we launched the Cognizant innovation network, a new corporate investment arm that will back early-stage AI start-ups. We plan to initially focus on investments in AI, data, cybersecurity and cloud technologies and portfolio companies will gain direct access to Cognizant's deep industrial expertise and its enterprise client base, creating a powerful ecosystem for mutual growth. We are progressing towards the AI builder vision through our 3-vector strategy. AI-led productivity, industrializing AI and identifying the enterprise. To date, we have well over 5,000 AI engagements across 3 vectors, up from approximately 4,000 exiting December. Beginning with Vector 1, we are addressing a multitrillion dollar opportunity of AI-led productivity across several value pools by helping clients, building classical software in new ways, accelerate software development, eliminate technical debt and modernizing legacy systems. Our differentiated approach to autonomous software is rooted in engineering-led productivity powered by leading strategic partnerships like Entropic Claude, Google Gemini, Microsoft [indiscernible] and copilot Davin and open AI codecs. This approach has enabled nearly 40% of our code to be AI assisted. Cognizant platforms play a critical role in scaling these productivity [ grains ] by accelerating software development with Flow source, reverse engineering legacy code using agent-based capabilities through Sky grade and automating incident management with neuro IT operations. A great example of our platform strategy at work is with one of the nation's largest health companies where we now underwrite the integrity of their claims process. Our AI solution automates the validation of over 54 million provider contract updates annually, directly reducing revenue leakage and solving a problem that was previously intractable at scale. Some of the early value pools in Vector 1 where we are seeing client momentum are related to legacy debt takeout, like mainframe modernization, SAPs for HANA migrations, autonomous software engineering, digital workplaces and autonomous infrastructure services. For example, we are working on a highly complex true blue field as for HANA transformation at a global scale, focused on modernizing the enterprise core for the North American global pharma leader. What really sets this project apart is our use of a customized AI accelerator that automates both business and IT data validation, replacing a fragmented manual process with a scalable audit ready and a robust solution significantly cutting validation time and effort. For a leading European telecom operator, Cognizant delivered an AI-powered Oracle cloud ERP transformation, unifying finance, procurement and supply chain on a single cloud-native platform, achieving 25% faster time to market and 40% faster deployment through agentic AI and automation. And with Daimler Truck, we will use Cognizant WorkNEXT to transform and modernize its global workplace services. Our multiyear partnership aims to leverage artificial intelligence and automation to enhance workplace operations across their global factories and offices. As our AI productivity capabilities mature, we are increasingly applying token metering at a project or an individual level to provide early insights into usage patents model management and optimization of infills costs. Vector 1 continues to be a primary driver of our large deal momentum. And as a result of the cost savings and shared productivity generated in Vector 1, we're starting to see increased velocity in Vector 2 and 3 opportunities. Let me share some examples. In Vector 2, as we integrate enterprise AI into enterprise landscapes, platforms provide the foundation to move AI from proof-of-concept into production at enterprise scale, managing the full agent life cycle with neuro AI engineering and context engineering. This spans several areas, including data engineering, AI, foundry, cybersecurity and integrating AI into the infrastructure and cloud stacks. As an example, with data engineering for a leading U.S. health care client, we deployed an AI-based data validation system to optimize the distribution of pharmaceutical shipments. The solution uses predictive models to validate data before dispatch reducing downstream errors in the logistics chain and improving reliability across its operations. One of the value pools we see in Vector 2 and a key element of our AI builder stack is context engineering. Cognizant's approach to contract engineering is to build native work graphs by going deeper into how humans work, make decisions and navigate exceptions in their daily business processes. We're also applying context engineering at a top wealth management firm with an advanced proof of concept where AI agents are being designed to work alongside financial advisers handling routine interactions and back office tasks so that financial advisers can focus on client-facing activities. Finally, in Vector 3, we are accelerating development of our AI native products to unlock new agentic labor pools across vertical and functional domains and into core operations. The value pools in Vector 3 are significantly expansive opportunities across business operations of enterprises to embed Agentic capital for productivity, experiences and new services. In health care, for example, we are developing agentic solutions that accelerate and improve the accuracy of prior authorizations to support better patient outcomes. Additionally, we are building on our TriZetto product portfolio in a strategic partnership with Palantir to advance an outcomes-based intelligence platform that embeds AI-driven decisioning directly into health care operations. We're also sensing a broad structural shift as AI moves beyond digital workflows to governing physical systems and environments and infrastructure. This is accelerating the convergence of physical AI agent AI and governed enterprise intelligence enabling autonomous operations across sectors. Cognizant is investing in the architecture platforms, partner ecosystem and industrial domain expertise for physical AI. Business operations-led offerings are central to this evolution. We're expanding AI-enabled services across sales, finance, marketing, service operations, horizontally and health care financial services and banking operations on the vertical stack. Examples include the recent launch of autonomous customer engagement with Google to support outcome-based human AI workforce models across industries and the combined value proposition of TriZetto and Palantir to identify health care operations. Across all 3 sectors as the importance of platforms grows, we are evolving our commercial models towards fixed and outcome-based pricing, enabling Cognizant to recognize the added value of assets, IP and accelerators that we bring. This is an important pillar of our first principles, shifting our economics to managed services and outcome-based models. Consistent with the shift, we delivered 2.5% and 5% increases in trailing 12-month revenue and adjusted operating margin per employee, respectively. We are beginning to see the emergence of AI infused rate cards where pricing reflects a blended model of human effort and digital effort with several clients, we are exposing tokenized rate cards that prices work along a continuum from fully human-led discovery to hybrid to increasingly autonomous agenetic delivery. This model is intended to turn our outcome-based economics into a true partnership that aligns value creation with shared results. Execution across the sector requires the right organizational structure and a powerful innovation and talent. This brings me back to another important element of our first principles, reimagining talent away from the traditional pyramid and towards interdisciplinary AI-augmented teams. To fuel the shift, we have launched an integrated AI skilling stack for our entire organization. It begins with our AI Builder career program, which maps every role at Cognizant to a future-ready AI family, job family with defined pathways and targeted learning plans aligned to how [indiscernible] evolving. This is powered by Cognizant and SkillSpring, our new AI native learning platform designed to redefine learning in the AI era and cultivate AI-ready talent at scale for our associates and our clients and progress is being tracked for each associate's personal AI fluency dashboard. A real-time context engineered view of AI readiness across various dimensions, including AI skills and proficiency, training and certification, AI tools and token uses innovation and project experience. To enable us to execute on these principles with the speed and the agility of the market demands, we are initiating a new program called Project LEAP. This program is designed to accelerate our transformation to the operating model of the future by funding investments in our AI capabilities and partnerships, integrated offerings and platforms, reshaping productivity and upskilling our workforce. By fostering a workforce that is AI-enabled and equipped with future-ready skills, we aim to create a more agile, scalable and cost-effective operating model. Even as we make these changes, we are continuing to invest in growth through acquiring new talent. We hired around 20,000 freshers in 2025 and plan to hire a greater number in 2026, providing a strong pipeline of future talent aligned to how work is evolving and shaping a broader pyramid with a shorter path to expertise. The LEAP program reinforces our commitment to be in the winner circle of revenue growth and supports our journey of expanding margins. To conclude, I want to leave you all with this. Our conviction in the long-term opportunity emerging with enterprise AI adoption has never been stronger. In our industry, the real work happens inside complex systems across legacy environments, regulated processes, global teams and mission-critical operations. Large enterprises do not transform overnight. The undeniably need trusted partners who understand their systems, context, risks and people. And that is the role we intend to play as an AI builder, bridging the gap to enterprise value. To win, we must move fast and stay agile, which is exactly why Project Leap is so critical. We are reforging our first principles, enabling an AI Era future operating model, equipping our go-to-market teams across the 3 vectors. Adopting new engagement models to deliver value to clients and adopting talent through a blend of digital and human effort. We remain confident the portfolio and capabilities we are assembling can drive sustained progress towards Winner Circle performance including top-tier growth, consistent margin expansion and EPS growth outpacing revenue growth. Before I turn the call over to Jatin, I want to thank our associates for their dedication, our clients for the continued trust and our shareholders for your confidence as we strengthen our foundation to create for durable long-term value.