Coforge AI push in FY26: $5.5m, 30,000 trained

A CEO message aimed at Indian IT’s next cycle

Coforge CEO Sudhir Singh has laid out a clear view of how artificial intelligence is changing the business model of India’s IT services industry. He argues that AI is already improving internal operations, lifting margins, and reducing dependence on the traditional labour-led delivery model. The company says it has invested more than USD 5.5 million in AI during FY26 and trained over 30,000 employees to build an AI-first workforce.

Singh’s broader point is that the industry is moving into a phase where manpower growth alone may not translate into sustainable revenue growth. In his view, the winners will be firms that redesign processes around AI, build agentic AI systems, and develop capabilities across the full lifecycle of AI applications.

Coforge’s FY26 AI investments and workforce training

Coforge’s disclosed AI investment for FY26 stands at over USD 5.5 million. Alongside this spend, the company trained more than 30,000 employees, framing the effort as a workforce shift toward “AI fluency” rather than a narrow set of specialist hires.

Singh has linked these initiatives to tangible operational outcomes. He says AI is improving internal operations and supporting margin expansion, indicating that productivity improvements are being pursued alongside new revenue opportunities.

Moving beyond the “labour-led” model

Singh’s warning for the sector is direct: companies dependent only on manpower growth could struggle over the next few years. The logic is that as automation, AI-driven engineering, and cloud-native delivery mature, the value clients seek may increasingly shift from staffing-based scale to outcome-based delivery.

He has positioned Coforge’s direction as process redesign and integration-led work rather than only adding people. The stated focus areas include AI-native process redesign, agentic AI systems, and lifecycle management. The message is that building AI solutions may become cheaper, but running them reliably, securely, and at scale can expand the demand for managed services.

AI spending: why “run” budgets may shrink and “innovation” may expand

In an interview, Singh described client technology spending across two axes: “run the business” and innovation. He said spending on “run” work can contract because AI can drive efficiency at scale. But he also argued that the innovation budget has become more elastic, especially when a provider can tie AI tools to a concrete business outcome.

This framing matters for Indian IT because it shifts the conversation from headcount-linked execution to business-led transformation and system integration, where providers are expected to modernise infrastructure, fix fragmented datasets, and implement AI as one integrated approach.

Three marketplaces Coforge sees in AI

Singh described AI as creating three distinct marketplaces:

• A base layer of frontier models, which he indicated tech services firms typically will not target directly.
• A middle layer of tools for the AI ecosystem, where services firms may not “play” directly but need strong partner relationships.
• An overarching layer of system integration and services, where Coforge sees the most direct opportunity.

This is consistent with Coforge’s emphasis on integration, operations, and lifecycle ownership, rather than competing with model builders.

Encora acquisition and the AI-native engineering bet

Coforge made a sizeable acquisition in December 2025, buying Encora, a Silicon Valley AI-native engineering firm, in an all-stock transaction. The reported acquisition value was USD 2,350 million. Coforge has also set a target of USD 2,000 million in revenue by FY27 from combined AI-led product engineering, cloud and data.

The acquisition is presented as a strategic step to expand AI-led engineering capacity and deepen capabilities across product engineering and modernisation. Singh’s narrative links this to enterprise realities, such as patchwork infrastructure and fragmented datasets that require both modernisation and AI deployment in a single program.

Addressing layoff fears: maintenance and integration still matter

On concerns about job losses, Singh said AI-generated code still requires maintenance, security, and integration. His argument is that while AI can change the nature of work, it also creates demand in adjacent areas such as operating AI systems safely, managing change, and integrating new capabilities with enterprise-grade delivery.

This is presented as a shift in workforce mix rather than a simple replacement cycle, especially for firms building managed services and lifecycle capabilities.

Recent performance signals and AI-linked demand commentary

Coforge reported USD 462 million in revenue in the September quarter, up 4.5% sequentially and 26.6% year-on-year, and above a Bloomberg expectation of USD 461.6 million. On an analyst call, Singh said demand has “mutated” with AI, but the addressable demand continues to grow.

The company has also highlighted deal momentum and AI-led solutions. Separately, Coforge reported that its executable order book for the next 12 months grew 47.7% year-on-year to USD 1,500 million.

The industry backdrop: scale of disruption in Indian IT

India’s IT services industry is described as a USD 285,000 million sector employing close to six million people. The model historically relied on labour arbitrage and manpower-intensive delivery, but is now being tested by automation, chatbots, AI-driven engineering, and cloud-native delivery.

Coforge has framed AI as a growth tailwind rather than a deflationary force. Singh has also argued that by 2026, investors should watch forward-looking indicators such as “AI fluency”, large deal momentum, deal velocity, and revenue per employee. He has also noted the rising importance of EBIT over EBITDA, particularly for companies active in mergers and acquisitions.

Key data points mentioned

Market impact and why Singh’s view matters

Singh’s comments sharpen a debate investors have been tracking across Indian IT: whether AI compresses services demand or expands it through new categories of work. His case leans toward expansion, but with a clear condition that firms must move toward AI-native delivery, system integration depth, and lifecycle ownership.

For Coforge, the stated operational impact includes improving internal operations and supporting margins, while the strategic impact includes pushing beyond labour-led growth and positioning around AI-led transformation, managed services, and large deals.

Conclusion

Coforge’s disclosed FY26 AI spend and employee training, combined with its Encora acquisition, underline a strategy built around AI-first delivery and integration-led services. Singh’s core message is that Indian IT’s growth will increasingly depend on AI-native redesign, agentic systems, and lifecycle management, not just workforce scale. The next set of markers, by his framing, will be seen in deal momentum, revenue productivity and profitability metrics such as EBIT, as AI-driven enterprise reinvention spending expands toward 2031.