Ravi Kumar1:05
Thank you, Tyler. Good morning, everyone. Thank you for joining us today. I'm pleased to report our momentum continued in the fourth quarter as revenue growth and adjusted operating margin again outpaced our expectations. Looking at the quarter's highlights, revenue grew 3.8% year-over-year in constant currency, all organic, driven by North America. By segment, financial services led growth with constant currency revenue increasing 9% year-over-year during the quarter and 7% for the year, the highest annual level since 2016. Q4 bookings grew 9% year-over-year, driving a record quarterly total contract value. We signed 12 large deals with TCV of $100 million or greater, including one deal valued at more than $1 billion. The value of these large deal wins is 60% greater than a year ago. Adjusted operating margin of 16% improved by 30 basis points year-over-year. We now have over 4,000 AI engagements across all three vectors and over 30% of our developer effort in software development cycles is AI-assisted and agentic. And our productivity improved as fixed bid and transaction-based work now represent more than 50% of our revenue. We also saw a 5% and 8% increase in trailing 12-month revenues and adjusted operating income per employee respectively. These results drove 2025 revenues up 6.4% in constant currency, surpassing the $20 billion mark and the high end of our guidance range. Importantly, we delivered profitable growth. Our 15.8% adjusted operating margin exceeded guidance, rising 50 basis points over last year. We achieved this result while investing in our people, including through a merit cycle for most associates and our highest discretionary annual bonus funding level since 2018. January marked my third anniversary as Cognizant CEO. When we began this journey in early 2023, we set out to reclaim our winning heritage. In 2024, we successfully pivoted from stabilization to growth, industrialized a large deal engine, and expanded our platform strategy with AI investments to broaden our capabilities. In early 2025, we laid out our strategic objectives to amplify talent, scale innovation, and accelerate growth. We also set a goal to reach our industry's winner circle by 2027. And I'm extremely proud that we arrived two years early with top-tier revenue growth throughout 2025. We executed with speed and discipline, consistently meeting or beating the high end of our expectations each quarter as our investments began shaping Cognizant into an AI builder capable of scaling agentic AI across our client landscapes.
Looking at additional milestones that demonstrate successful execution on our three strategic priorities. In 2025, we promoted more than 35,000 associates. We signed 28 deals, each with TCV above $100 million, with a combined TCV up nearly 50% versus last year. This includes five mega deals with TCV of $500 million or greater. Our net promoter scores reached a record high in 2025 from when I started 3 years ago. We expanded the breadth and depth of our partnerships across the hyperscaler and AI-native landscapes. We signed and have since closed our acquisition of Thirdeye, adding more than 1,200 Azure specialists and engineers to industrialize our deep expertise in Azure data and AI and application innovation. We returned $2 billion to shareholders through dividends and share repurchases. Our progress is reflected in our total shareholder return, which was top two within our peer group in both 2025 and the three-year period beginning 2023 through 2025. Finally, with Belcan, we completed key integration milestones and continue to build a healthy synergy pipeline in the aerospace and defense industries. Last week we announced Belcan secured a position on the Missile Defense Agency's Shield program. The indefinite delivery, indefinite quantity contract with a ceiling value of $150 billion positions us to compete for a broad range of task orders supporting innovative defense capabilities.
As we enter 2026, our strategy is focused on solving the AI velocity gap—the gap between massive AI infrastructure spending in the past few years and business value realization for our clients. While AI technology is now mature enough to offer transformative value, the methodologies and tools to harness it are only just emerging and the value to enterprises hasn't materialized yet. In fact, our latest New Work, New World research released last month reveals that AI today is capable of unlocking $4.5 trillion in US labor value in the future. Cognizant's mission is to be the AI builder bridging this gap to enterprise value by converting the technology to measurable returns on investments for our clients. We are approaching this opportunity through our three-vector strategy. To capture vector 1 demand, as we call it, we're applying AI productivity to augment and accelerate traditional software cycles. As we shared at our investor day, we see a massive multi-trillion dollar opportunity to help clients accelerate the elimination of technology debt, build classical software in newer ways with AI platforms, and repurpose savings towards innovation. And to capture what we call vector 2 and 3, we are building entirely new cycles of agentic capital and digital labor that goes beyond the reach of legacy software, creating a much larger total addressable spend. Closing this velocity gap, the AI velocity gap, requires new methodologies and evolving beyond the traditional IT services role of the last two decades. In the '90s, we were bespoke systems builders. We wrote custom software code and we owned the outcomes. In the two decades that followed, our role evolved into a system integrator. We orchestrated classical software owned by various software providers. But classical software, which was written around the microprocessor, was deterministic and built on rigid logic and fixed rules. Today's AI software, which is written around the frontier models, is probabilistic and contextual. This shift allows us to own the stack again and deliver to outcomes. We believe reinvention and reimagination of businesses will be driven by value at the intersection of AI, agentic capital, and classical software.
To capture this demand, our AI builder stack acts as the connective tissue that addresses four layers of the ecosystem: AI compute, cloud, model access, and human capital services. Let me share some key elements. First is our trademarked BaaS framework, a proprietary blueprint that guides clients in architecting new business processes specifically for deploying and orchestrating autonomous agents. This is a fundamental shift from writing rigid logic to designing behavior, persona, intent, and outcomes. Second is our pioneering science of context engineering, a methodology for mapping a client's unique work graph, giving AI the situational awareness it needs to produce reliable business outcomes. Context engineering bundles an organization's operating principles, tribal knowledge, work patterns, friction sources, and historical and cultural imperatives so that AI intelligently binds to the enterprise's heterogeneous context, creating highly productive agentic capital. Third is our AI partnership ecosystem, which we continue to strengthen. On the NVIDIA stack, we are offering solutions across the full lifecycle from building and fine-tuning models to standing up agentic applications and deploying them as microservices. With Anthropic, Google Cloud, Microsoft Azure, and OpenAI, we are using their frontier models and agentic tooling to build layers of application value to accelerate AI adoption for our clients. With Adobe and Typeface, we are modernizing the enterprise marketing function and enabling cutting-edge customer experiences and content by moving manual workflows to agentic orchestration. With Cloud Code, Cognition, GitHub, and Windsurf, we are industrializing software creation through advanced code generation. With WorkFusion, we are scaling the emerging discipline of context engineering. With Writer and Unifor, we are partnering to deploy specialized domain-specific AI platforms. With Palantir, we will integrate its Foundry and Artificial Intelligence Platform to support the integration of AI with our TCS business. And finally, with Salesforce and ServiceNow, we are embedding our agentic networks directly into our clients' primary enterprise workflows. The fourth layer of our AI builder stack is our own proprietary IP across platform, services, and research. For example, FlowSource elevates our engineering velocity, while NeuroIT Ops harnesses AI to proactively manage and self-heal hybrid environments. Our AI training data services have helped curate billions of high-precision data points for global clients. With Trizetto, we are accelerating and improving healthcare management. Our recently launched Care Advanced AI offerings help streamline clinical workflows, reduce administrative burden, and empower care teams with faster and more accurate insights. And our award-winning AI Labs, which was awarded its 61st patent, continues to feed our continued investments in AI platforms and products.
To industrialize our AI builder stack, we have formed three units to sharpen our go-to-market muscle. First, our market-facing AI units are the hunters or value seekers working to capture the $4.5 trillion in labor value our research identified. Second, our integrated AI solution unit acts as an architectural core bringing various components of the AI stack together with strategic partnerships, Cognizant methodologies, and AI platforms to address specific reinvention needs of businesses. And finally, our centralized AI platforms and products unit is a factory packaging custom IP into repeatable solutions. Underpinning our AI builder stack is our talent strategy. Over the last two and a half years, over 340,000 of our associates have completed AI skilling. We are shifting from a traditional linear staffing model to an asynchronous, autonomous software engineering model. In this framework, our associates are trained to delegate complex, high-value macro tasks to agentic networks while they micro-steer to outcomes using platforms like Cognition, Gemini, Cloud, GitHub, and others, orchestrating through Cognizant FlowSource. We are in the process of developing a hyper-productive, high-velocity delivery model for agents to asynchronously assist human software developers and agent managers. In addition, we are broadening our talent base with non-STEM talent and early career programs. This includes aggressively recruiting interdisciplinary skills at the intersection of industry domain and technology. We added over 16,000 associates in India in 2025. In 2026, we are targeting 2,000 campus hires in the US and approximately 20,000 in India.
We are seeing this AI builder strategy translate into demand across our core practices. For example, our proprietary platforms like FlowSource and NeuroIT Ops are helping clients unlock technology debt, helping to fuel 8% year-over-year growth in both the fourth quarter and the year in our digital engineering practices. Similarly, our clients are rethinking their operations through an agentic lens. Demand for our BPO business, powered by deep immersion of digital labor, grew 9% year-over-year in the quarter and the year. Our AI data training services, launched early last year, is gaining traction with our clients to build fine-tuned AI models at speed and scale. And demand for data and cloud modernization remains healthy, with revenue across both practice areas growing mid-single digits organically, outpacing total company growth. Now let me share a few client examples of our strategy in action. First, with a financial services client, we signed an incremental billion-dollar partnership where we are leveraging our AI platforms, including our NeuroSuite and FlowSource, to help accelerate speed to market, drive product innovation, and deliver enhanced productivity. Next, with Sysco, the global leader in food distribution, we're transforming their complex customer interaction ecosystem into agentic capital. Previously, customer requests from product credits to order substitutions could have prolonged resolution windows. Now, by deploying orchestrated agents, we have collapsed that cycle to 90 seconds. Sysco is harvesting this AI-generated savings to fund its next phase of innovation. In the healthcare sector, we have moved from pilots to production-grade automation for a major US regional player. Our AI intake platform reduced enrollment cycle times from as many as 7 days to minutes. On their claim side, our clinical engine now adjudicates 96% of nurse note reviews autonomously, cutting human review times from 8 hours to 20 minutes. We're scaling this expertise globally through a new strategic collaboration with Bupa Hong Kong, where our GenAI-led business process as a service solution modernizes claim and fraud, waste, and abuse detection, marking our largest BPO win in the region. And we announced a multi-year expansion with Kohler, a leader in kitchen and bath products. Building on our successful five-year partnership, we're bringing our cloud management capabilities and AI solutions like NeuroIT Ops to advance Kohler's digital ecosystem and drive AI-driven innovation.
As we look towards 2026, we are well positioned to continue our momentum. Our ambition is to lead as an AI builder and maintain our position in our industry's winner circle. In closing, I'm proud of all that we have accomplished over the last three years, which helped us reach our industry's winner circle two years ahead of plan. As the next decade of contextual computing unlocks new waves of nonlinear enterprise productivity and agentic software cycles, I believe there is a significant opportunity to create shared value for our clients, our associates, and our shareholders. The foundation is set. I believe the boldest chapters of our story are still ahead. Thank you again for joining us. I'll now turn the call over to Jatin.