Coforge CEO on AI: FY26 $0.0055bn spend, 30k trained

AI is forcing a reset in Indian IT’s operating model

Coforge CEO and Executive Director Sudhir Singh has laid out a blunt view of what AI is doing to India’s IT services business. He argues the industry is moving away from a labour-arbitrage model and towards AI-native delivery where process redesign, agentic systems, and lifecycle management become decisive. In this framing, headcount growth alone is not a strategy. Singh says AI is already improving internal operations and supporting margin expansion at Coforge, while helping the company move beyond the traditional “labour-led” model. He also warns that companies reliant only on manpower scaling could struggle as AI changes delivery economics.

The debate matters because Indian IT is large and employment-heavy. The article places India’s IT services industry at about $185 billion, employing close to six million people. That combination makes every productivity shift politically sensitive and financially material.

FY26 AI investment and building an AI-first workforce

Coforge has backed its positioning with spending and training. The company invested over $1.0055 billion in AI during FY26 and trained more than 30,000 employees to create what it describes as an AI-first workforce. Singh’s message is that AI adoption is no longer limited to pilots or “experimentation.” In his view, that phase is over, and the next phase is enterprise reinvention driven by cloud, data, and AI.

He also points to internal use cases, including a customised AI co-pilot for the sales team and the use of Coforge’s Forge-X platform to accelerate software development and legacy modernisation. However, he adds a note of caution on claims of dramatic productivity jumps, saying Coforge is seeing improvements closer to 30%, not the 70% to 80% figures often cited.

Singh’s thesis: AI is “accretive”, not deflationary

Singh has publicly described AI as “accretive, not deflationary” for service providers that combine domain knowledge with technical capability. His argument is that AI changes how client budgets behave. He splits spending into “run the business” and “innovation” axes, saying the former will keep contracting as AI drives efficiencies, while innovation budgets become more elastic when AI delivers measurable outcomes.

He also links competitive advantage to “AI fluency” and deal momentum, and says new operating metrics like deal velocity and revenue per employee are becoming more important. In the AI era, he argues, the winners will be the firms that translate productivity into client outcomes and pricing power, not just internal cost reduction.

The Sabre deal as a marker of shifting deal leadership

Coforge’s positioning is illustrated through its Sabre contract, described as $1.56 billion over 13 years and structured in three phases. The article frames this as “mega deal territory” that historically would have been associated with the largest firms.

The contract structure is explicitly laid out: integration and migration in years one through three, optimisation and enhancement in years four through seven, and innovation and AI deployment in years eight through thirteen. The narrative also claims Coforge competed against TCS, Infosys, and Accenture and won, citing better AI capability, faster delivery, and deeper travel-tech expertise.

Agentic AI delivery and the Forge-X platform

Coforge has also announced advances in Forge-X, describing it as an integrated engineering and delivery platform built on “Agentic AI principles.” The company says Forge-X uses autonomous AI agents supported by engineering expertise and industry domain context to deliver complex technology transformations at scale.

Forge-X is presented as an AI-native approach spanning both the Software Development Life Cycle (SDLC) and Product Development Life Cycle (PDLC). The stated objectives include faster time-to-market, improved resiliency, and optimised engineering costs. The tools listed under this umbrella include CodeInsightAI (GenAI-powered reverse and forward engineering), BlueSwan (AI-led digital assurance and quality engineering), NORTHSTAR (continuous integration, delivery, and observability), and EvolveOps.AI (autonomous IT operations management across hybrid cloud lifecycles).

Encora acquisition and the push into AI-native engineering

Coforge bought Encora, described as a Silicon Valley AI-native engineering firm, in December 2025 in an all-stock transaction from Advent International and Warburg Pincus. The deal value is stated as $1.35 billion.

The article says the Encora acquisition positions Coforge as a stronger AI solutions provider, with AI-led product engineering, cloud, and data expected to deliver $1.0 billion in revenue by FY27. In the broader narrative, Coforge is described as having risen to the eighth-largest Indian IT services firm from its 18th position in 2017, as it shifted strategy under Singh.

Midcaps vs large firms: product engineering DNA vs services DNA

A recurring theme is the difference in delivery approach. The article contrasts large firms that often lead with professional services and staffing-heavy implementations, versus midcaps that bring product engineering DNA and build AI into client products while creating IP. It links this distinction to contract outcomes and how AI is embedded in modern deals.

Persistent is cited as an example of this trend, with AI components embedded into 60% of its Q4 FY25 deals. Coforge’s Sabre engagement is described as being structured around agentic AI deployment and labelled the largest AI services deal in the travel industry.

Global delivery economics: innovation versus cost arbitrage

The article also highlights delivery economics that combine time zone and cost advantages. Coforge is said to run 30 plus global delivery centres. In the Sabre partnership example, it states the engagement leverages India’s AI talent pool to deploy 100 AI engineers at the cost of 30 in the US. The broader point made is that midcaps are increasingly competing on innovation, not just lower cost, while maintaining a 40% plus cost advantage.

Jobs, code generation, and why integration still matters

Addressing layoff fears, Singh argues that AI-generated code still requires maintenance, security, and integration, which creates new work. He also makes the point that bespoke coding is not the bulk of what tech services firms do, saying they are primarily in the business of building business solutions and integrating platforms.

The article notes that AI is already writing around 30% of code. But it frames the practical constraint as everything around the code: documentation gaps, legacy dependencies, compliance requirements, and operational lifecycle management.

Market structure: services and GCCs growing together

On the GCC debate, the article states that both IT services revenue and GCC headcount grew by roughly 40% between 2020 and 2025. It uses that to argue that GCCs have not replaced outsourcing, because services revenue did not decline.

It describes a typical 2025 enterprise setup as 300 people in a GCC for core platform work and 700 from vendors like Coforge or Persistent for features, support, and AI projects, totalling 1,000 people. The conclusion drawn is that the future model is “services plus GCCs” competing against global players, not services versus GCCs.

Key facts and figures

Why investors are watching AI fluency and deal design

The article’s investment-relevant takeaway is not that AI will shrink IT. It argues the market is expanding, citing a projection that the IT services market could add $100 billion in the next five years and reach $1.8 trillion by 2030. Within that growth, it suggests value will shift toward companies that redesign processes around AI and can run complex, multi-year transformations.

For Coforge, the combination of platform-led delivery (Forge-X), large-contract execution (Sabre), and portfolio moves (Encora) is presented as a blueprint for competing beyond scale. The implied challenge for the broader sector is adapting operating models so AI drives measurable business outcomes, not just automation.

Conclusion

Singh’s central claim is that AI is the biggest structural shift Indian IT has faced since the labour-led model became dominant, but that it can be growth-positive for firms that combine AI capability with domain depth. Coforge’s FY26 AI investment, 30,000+ employee training, the $1.56 billion Sabre contract, and the $1.35 billion Encora acquisition are positioned as proof points of that strategy. The next markers to watch, based on the article’s framework, are continued large-deal momentum, evidence of AI-led delivery at scale, and progress toward the $1.0 billion FY27 revenue target for AI-led engineering, data, and cloud.