US-headquartered IT consulting and modernisation services provider Cognizant Technology Services has been consistent in targeting growth through investment in AI, and its plans on diversifying across industries and geographies with a focus on AI assets.
Cognizant CEO Ravi Kumar’s $1 billion commitment in 2023 towards generative AI to be deployed over the next three years has translated into the firm’s fight to be back in the “winners’ circle” by 2027, as emphasised by the CEO in his communication to employees. The company recently announced the setting up of its AI Lab for research, and the Moment Studio dedicated to digital experience practice in Bengaluru are the key levers towards expanding the company’s AI innovation footprint.
With its three-vector AI strategy and strategic acquisitions to strengthen its position as an AI builder, Cognizant has managed to win new deals, with the CEO stating during an investor conference in October that the company has been closing four to five deals of over $100 million every quarter.
Forbes India caught up with Surya Gummadi, president, Americas at Cognizant for his insight into advancing the company through global large deals and GCC strategy. In his 25-plus-year career at Cognizant, Gummadi has borne witness to the company’s changing focus.
“Earlier, we focussed primarily on hiring technical talent, but now we are hiring industry practitioners, such as claims processors, insurance underwriters and other domain experts to train and validate AI agents that mimic real-world enterprise workflows,” Gummadi told Forbes India.
The company acquired Microsoft Azure services provider 3Cloud in November for an undisclosed amount, adding 1000-plus Azure specialists to its workforce. The acquisition will help Cognizant become one of Microsoft’s biggest Azure partners.
With the demand for AI application layer growing, Gummadi says Cognizant’s strategy shift is encouraging for the company and the industry in general. Edited excerpts:
Q. What is Cognizant’s AI strategy at large? How do you decide between bolt-on acquisitions versus in-house development?
Three years ago, when our CEO Ravi joined, he prioritised a $1 billion AI investment and accelerated our AI build-out across three strategic dimensions.
First is infrastructure—we have incubated AI labs in San Francisco, London, and Bengaluru with 30+ full-time PhD researchers driving innovation and have 61 patents.
The second aspect is talent—we have rolled out code-assist platforms to all our developers, and recently conducted the world’s largest vibe coding event, and have trained over 200,000 associates in AI technologies through global partnerships and internal programs.
Third is platforms. We have built multiple internal AI tools, frameworks, and launched the Cognizant Neuro Suite—our AI platform stack that helps clients accelerate productivity, AI development, and agent orchestration. We continue to expand and enhance these platforms.
We focus on building the right frameworks and platforms for our clients, and we integrate acquisitions when the capabilities align. It depends on the opportunity, the asset, and the technology it brings. In parallel, our AI Labs remain a major investment.
Our researchers at AI Labs are working on several areas—optimising and training LLMs, developing domain-specific AI solutions, advancing agent education, and building multi-agent orchestration frameworks. We have developed a comprehensive suite of tools under the Neuro Suite that supports the entire AI stack—LLM integration, accelerated AI development, identification layers, and orchestration frameworks. We continue to expand these capabilities as part of ongoing research and innovation.
Q. Can you tell us about Cognizant’s strategy to leverage AI and how does the recent acquisition of 3Cloud fit into the “builder strategy”?
Let me take a step back to explain why this acquisition is important. Our go-to-market approach to AI is built around three vectors.
First, we focus on unlocking productivity for our clients—leveraging AI tools and frameworks to drive efficiency across every part of their enterprise, from operations to support and beyond.
Second, we enable what we call AI industrialisation—infusing AI across the entire tech stack. This means preparing the cloud infrastructure, getting the data layers AI-ready, including integrating large and small language models, building native AI applications or docking AI models into applications, and modernising business processes.
The third vector is identification and orchestration—building AI agents and multi-agent orchestration platforms that enable systems to collaborate seamlessly.
Over the last 12–18 months, most client activity has been in the first vector—productivity. But now more clients are moving into the second vector, AI industrialisation. The next frontier is agent-based systems and multi-agent orchestration.
From a macro lens, over the past two years, nearly $400 billion has been invested globally in chips and infrastructure. I believe the spend is now shifting to the applications layer which aligns perfectly with our three vectors.
We see ourselves as AI-builders. Anything we acquire must strengthen one or more of these vectors, and the 3Cloud acquisition dovetails perfectly into all three vectors. 3Cloud is a company that is deep in Microsoft Azure space. They are experts in unlocking productivity, building Azure-native AI applications, and now we have acquired the capabilities to identify and orchestrate on Azure platforms.
We already have a strong Microsoft Business Group and do extensive work on Azure across all three vectors. 3Cloud brings in fresh, complementary capabilities that strengthen our AI-builder narrative on Azure.
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Q. How does Cognizant use AI for internal functions and how has it impacted hiring and traditional roles within the company?
We are embedding AI across the organisation not just for clients, but within our own operations. Today, AI powers our recruitment, training, internal tech support, marketing, sales, finance, legal, and even our intranet is agentified. Depending on the function and use case, internal productivity improvements range from about 20 percent to 30 percent, and the gains increase as processes mature.
AI deployment has influenced hiring significantly. We now have a Chief AI Officer (Babak Hodjat) who leads all our AI labs and AI infrastructure. Under this role, we have AI researchers, AI solution experts, and architects from the industry.
Earlier, we focussed primarily on hiring technical talent. Now, as we move into identification and multi-agent orchestration, we are also hiring industry practitioners such as claims processors, insurance underwriters, and other domain experts. Their expertise is essential in training and validating AI agents that mimic real-world enterprise workflows.
Q. How does the company’s AI strategy extend to the GCC arm of the business?
GCCs are an integral part of Cognizant’s strategy. In fact, Cognizant itself originated as a GCC for Dun & Bradstreet before evolving into the global company we are today. We have deep-rooted experience in scaling capabilities and driving transformation from within which enables us to guide clients through the same journey.
Over the years, we have helped numerous clients set up or scale their GCCs, and we are taking that expertise to the next level with our AI-native GCC framework powered by the Cognizant Neuro Suite. Our goal is simple—enable GCCs to become AI-native from day one, so they can scale faster and deliver greater value.
This framework supports the entire lifecycle of GCC—from legal entity setup and location strategy to talent architecture, ramp-up, execution, and transformation.
We offer multiple models to meet clients where they are, in their journey—greenfield setups, BOT (Build-Operate-Transfer), hybrid models, and now an AI-powered catalogue of services.
We also work with established GCCs, transforming them from capability centres into AI-powered innovation and transformation hubs. For some clients, who previously ran BPO-style GCCs, we help pivot them into AI-driven global innovation centres.
We work with companies across all major industries—banking, insurance, healthcare, retail, communications and media—to set up or transform their GCCs.
There is significant GCC activity across the board, especially in hubs like Hyderabad. Many clients are exploring new GCCs, expanding existing ones, or transforming capability centres into innovation hubs.
A couple of years ago, GCCs were largely seen as capability centres focussed on cost efficiency and access to talent. Today, clients view GCCs as global innovation and transformation hubs, much closer to corporate headquarters. AI is accelerating this shift. There is a clear race among enterprises to move quickly, which is driving more GCC activity.
Q. You have been with Cognizant for over 25 years in its 30-plus year journey. What are the inflection points in the company’s history?
When I joined, the company was almost like a startup—we had fewer than 5,000 employees. Today, we are over 350,000. I’ve grown up with the firm and seen its evolution first-hand.
Over the last 25 years, Cognizant has gone through multiple S-curves. We started in the Y2K era, moved to the internet and client-server era, then to labour arbitrage and fixed-bid models, followed by managed services. After that came the SMAC wave—social, mobile, analytics, cloud—then the digital S-curve, and now the AI S-curve. Across these seven transitions, what has remained constant is our client-centricity, our domain strength, and our entrepreneurial culture. These have always differentiated Cognizant.
Q. How have the roles changed within the company due to the adoption of AI and what would be a good fit for a candidate joining Cognizant today?
Whether you join HR, recruitment, development, or finance, AI is embedded in the way we work. Developers now use AI-assisted coding platforms; HR and recruitment use AI for talent processes; finance teams use AI for forecasting and operations. AI has become a universal enabler. At the same time, Cognizant continues to offer multiple opportunities. You can be part of enabling functions like HR, finance, legal, or marketing; or you can join technical roles in development, design, or architecture. Many roles that exist today didn’t exist five years ago—such as AI engineers, prompt engineers, and forward engineers. As we move from traditional software development life cycles to agent-based development life cycles, roles will evolve, but opportunities in tech will remain strong.
We also continue to hire across business development, pre-sales, and sales roles. While the sales playbook will evolve in the AI era, the importance of the front-end engine—client partners and account managers—remains unchanged. The architecture of the firm still needs finance, HR, enabling functions, development teams, and a strong sales engine. We continue hiring fresh talent across all these functions.
First Published: Dec 31, 2025, 15:03
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