Coforge’s AI pivot set to power its next phase of growth

A DAY AFTER Christmas 2025, when Noida-based IT firm Coforge Ltd said it was buying Silicon Valley’s Encora, a digital engineering firm, the deal was the largest-ever in the Indian IT services and consulting sector at $2.3 billion. The tab dwarfed earlier IT buyouts, such as HCLTech’s $1.8-billion acquisition of select IBM products in 2018 and Wipro’s $1.45-billion acquisition of tech consulting firm Capco in 2021. As a premium player, Encora is yet another contrarian bet for Sudhir Singh, who joined as CEO in 2017, when the company was still known as NIIT Technologies, and steered its transformation and rebranding into Coforge in 2020, following a change in the controlling ownership pattern in 2019. “We normally don’t get into competitive bids. We go in for firms where we see intrinsic value, and further value that can be unlocked,” he says. For earlier acquisitions such as Cigniti and SLK (Global Solutions), Coforge had been the only bidder. And both had been contrarian plays. Singh knows integration is the key to any acquisition, but he prefers not to waste time on it. “As part of the acquisition process itself, we make it very clear that we don’t expect them (the leadership) to stay around. Our leaders who do the complete due-diligence are asked to step in and work with the remaining leaders of the acquired firm to run it,” Singh says. The same playbook applies to Encora, a supplier of software engineering services to digital-native firms, which caught Coforge’s eye for its AI-native DNA. With operational integration now complete and the churn settled, “The usual operating dynamic — where some people have expanded roles and others step back and get layered — has played out. These changes were implemented on the day of the announcement. So, the team is settled,” Singh says. With the Encora acquisition adding over half a billion in revenue and a focus on AI engineering to accelerate growth, Coforge is looking at its AI-native platform play and pricing models to capture downstream AI revenue. The AI platform strategy Coforge is positioned as an “AI-native” digital services and engineering firm. The early pivot came in mid-2023 with the release of ‘Coforge Quasar’, an enterprise-grade Gen AI Platform with 100+ pre-built use cases. Since then, there have been many additions. Singh sees the AI opportunity for his company play out in three distinct ways. One, the current demand from enterprises for legacy modernisation, which will help prepare and structure data for efficient AI adoption. Two, the medium term — a very significant value pool, around agentic engineering, once the managed services layer of those agents is put in place. Those agents need continuous monitoring, governance, and interventions. And three, as AI adoption picks up, “whether it is modernisation, agentic engineering, agent-as-a-service or model engineering — the longer term will have a much larger technology services spend to target,” the CEO says. According to Singh, the current platform play is based on the gap between enterprise AI pilot projects and the structural challenges when these pilots are scaled to production. “We have closed this gap with two things built together: a reference architecture called Coforge One AI designed for production-grade behaviour, and a delivery model called Mod Squads that leads with business outcomes.” The platform offering Forge X (an integrated agentic software delivery platform) includes CodeInsightAI (an intelligence and modernisation platform), BlueSwan (focussed on testing lifecycle, design, and execution), and EvolveOps.AI (an IT operations management platform). Each of these is meant to address different stages of the software, data, quality, and operations lifecycle. When a client wants all these in one deal, Singh sees its ‘Coforge One AI’ as a differentiator. Coforge One AI is the outcome of investments made over the years to build AI-native engineering and operations platforms. “It is a unifying intelligence layer, and that layer builds business context, industry semantics, and enterprise intent together to ensure that AI-driven execution is aligned not only to efficiency goals, but also to outcomes,” Singh says. Coforge’s AI Mod Squads is a subscription-based delivery model that replaces traditional time-and-materials billing with outcome-driven pricing, faster time-to-market, and full cost predictability. “We allow our clients to have the optionality to assemble custom AI native teams, AI agents, and pricing,” Singh says. He cites the banking, financial services and insurance (BFSI) sector where human+ agent mod squad has reduced cycle time by 70%, and in insurance underwriting where it led to a 50% faster underwriting cycle for clients. Pricing & deals in the AI age With AI infused into most deals in the IT industry, execution is changing on both talent and delivery fronts. In Coforge’s case, Singh says, the premium is on architecture judgment, domain understanding, and governance in newer deals. With the AI piece driving large-scale engineering transformation and migration towards agentic AI, pricing and expectations associated with agentic AI are also becoming centrepieces in such deals. In agentic AI, the AI runs independently to design, execute, and optimise workflows, without requiring a series of prompts. “Firms like us have to choose relevance over scale. That means we are having to hyper-specialise in select domains,” he says. At a time when large IT firms are talking about the AI-deflationary impact and some of it being passed on to clients, Coforge’s CEO is taking a contrarian view, aiming to capture the AI productivity gains rather than pass them all on to clients. Pointing at the EBIT margin guidance of 16.5%/17% (standalone) in FY27, against 14.4% in FY26 and 10.7% a year before, Singh says the diamond-shaped talent pyramid and agents themselves give them enough comfort to stay optimistic on pricing power. “We recognise AI-driven efficiency-related deflation. There is no denying it, but there are these new value pools, some of which are already in place, some of which are likely to start getting into play,” he says. Even with AI having a deflationary impact, agentic engineering and agent management — once AI agents are deployed in agent-as-a-service, model management, including managing model drift, continuous validation, and retraining of the model — are some of the tailwinds that he sees. What do the markets make of Coforge’s bets? Brushing aside the sharp sentiment-driven hit that Indian IT stocks have seen in 2026, with the Nifty IT index down 25% year-to-date, with frequent upgraded AI model versions being announced by frontier tech companies casting a shadow on the sector’s traditional IT revenue basket, the markets already have a heightened earnings growth expectation from Coforge. In FY26, the company saw strong year-on-year revenue growth of 29.2% in dollars, with total revenue of $1.9 billion. The EBIT margin improved by 370 basis points over the last fiscal, and the free cash flow of $135 million improved by 68.4% YoY. All this coming on the back of AI adoption, operational efficiencies, and the closure of low–margin accounts. As the company aims for $2 billion in AI revenue this fiscal year, the stock trades at a price-to-earnings ratio of 36.61 (as on June 30, 2026), higher than the Nifty IT average of 18-19. Following the company’s Analyst Day held at its Greater Noida campus on June 16, brokerages remain bullish on its growth, maintaining a buy call on the stock. According to Motilal Oswal Financial Services, the key takeaway was the company’s move beyond a purely volume-led growth model, increasing work engagement within their large accounts, embedding AI into transformation programmes, and expanding outcome-based engagements. “That said, execution around large-deal conversion, acquisition integration, and AI monetisation will remain key monitorables,” the note said. MOFSL iterated a buy call and is of the view that Coforge is a “structurally strong mid-tier player” and iterated it as a “top pick”. JM Financial Institutional Securities analysts, on the other hand, noted the management’s move to improve margins by exiting underperforming businesses, such as divesting Advantage Go (loss-making, cash-negative), leading to +60bps EBIT and exiting the Indian government’s business of $50 million annual revenue (low margin, adverse working capital) in their note dated June 17. With around 45,000 engineers and a pro forma revenue run rate of more than $2.6 billion, Singh says, for now, “We think there is no white space that Coforge foresees filling through M&A.” “But we will continue to be open,” he says. “We think the biggest badge over the last decade that the management team has earned is our ability to take distressed or near distressed assets and make them very high performers”.

Coforge’s AI pivot set to power its next phase of growth

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