AI becomes a measurable revenue pool for Indian IT firms, but not yet a growth engine

AI is improving productivity, but the margin benefits are yet to reach the bottom line as providers reinvest gains in talent, technology, data capabilities and new delivery models, while facing pricing pressure

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Suchat longthara

Indian IT services firms are increasingly quantifying their AI businesses, as investor pressure pushes companies to demonstrate that the technology is translating into a commercial revenue stream. However, analysts caution that AI is yet to emerge as a broad-based growth engine, with inconsistent revenue definitions and heavy investments in talent and technology limiting its near-term margin benefits.HCLTech reported Advanced AI revenue of $171 million in Q1FY27, up 10.6 per cent quarter-on-quarter in constant currency (cc) and 62.1 per cent y-o-y in constant currency. TCS reported annualised AI revenue of $2.6 billion in Q1FY27, up 13.6 per cent sequentially, while Infosys said AI accounted for 8.2 per cent of its revenue during the quarter.Ai productivityBeyond revenue, AI and GenAI are improving IT service delivery efficiency by automating routine tasks, enabling faster project cycles and improving real-time decision-making. Proof-of-value sprints and AI monitoring centres have also delivered measurable productivity gains in some cases, DD Mishra, VP Analyst at Gartner, said. He added that specialised AI deployments, like domain-specific SLMs, have shown greater ROI due to lower operational costs compared to generalised LLMs.This disclosure is largely being driven by investor pressure and the need to shape the market narrative. AI has moved from being a capability story to a valuation story, said Biswajeet Mahapatra, Principal Analyst at Forrester.“Providers need to show that AI is not only improving delivery productivity but also creating identifiable commercial revenue. The caveat is that there is still no consistent industry methodology for classifying AI revenue, because AI can be embedded in modernisation, data, cloud, automation, platform engineering and managed services deals. New disclosures should be read as directional indicators rather than directly comparable metrics,” he explained.Mishra said that despite efficiency gains, the disclosures indicate that margin benefits due to AI are partially offset by substantial investments in talent and technology infrastructure. With the rapid scaling of AI capabilities, firms are investing heavily in training and upskilling their workforce to manage and advance AI projects. The net result is a juxtaposition: while AI deployments improve operational efficiency and support incremental revenue growth, the benefits to margins are partially neutralised by the need for ongoing, heavy capital and talent investments to sustain and scale these capabilities.Mixed revenue growthAnalysts noted that while public Q1FY27 disclosures are meaningful at the provider level, they are not enough to conclude that AI is driving broad sector acceleration, because overall revenue growth during the quarter remained mixed; discretionary spending is cautious. The better interpretation is that AI is becoming a measurable revenue pool, not yet a sector-wide growth engine.AI is improving productivity, but the margin benefits are yet to reach the bottom line as providers reinvest gains in talent, technology, data capabilities and new delivery models, while facing pricing pressure. AI is therefore helping protect margins rather than structurally expand them.The better-positioned providers will be those that turn AI-driven productivity into priced, repeatable offerings, backed by production-scale deployments, industry-specific AI assets, strong data and modernisation capabilities, and outcome-based pricing.Published on August 14, 2026