New Delhi, Nov 6 (IANS) India’s information technology (IT) services sector delivered Q2 FY27 results that were modestly ahead of subdued expectations, but the broader recovery in demand is increasingly being pushed into FY28 as companies contend with pricing pressure and AI-driven disruption, a report said on Friday.
The report from BNP Paribas India said investors responded positively to better-than-expected earnings after analysing quarterly results from 15 Indian IT services companies, including five large-cap and 10 mid-cap firms.
Shares of the covered companies rose by a median 5 per cent following the results after having declined about 23 per cent year-to-date in 2026.
The market rewarded better-than-feared revenue, margin expansion and strong deal momentum, while penalising margin pressure and weak deal wins. Demand remains steady but narrow, with the financial services vertical as the bright spot.
“While FY27 headline revenue growth guidance cuts seemed modest, the organic cut was sharper, implying that FY27 organic revenue is likely to trail FY26, with acquisitions filling in the gap partly,” the report said.
“AI-led work continues to grow even as clients demand pass-back of the productivity gains, shrinking the legacy books and pushing down pricing pressure. With seasonally weak H2FY27, companies now expect recovery in FY28, supported by large deal ramp-ups,” the report noted.
Collectively, 60 per cent of the firms beat on revenue and 53 per cent beat on EBIT margin expectations, while 27 per cent missed on revenue growth and 40 per cent missed EBIT margin expectations.
Deal Total Contract Value (TCV) inched up modestly annually in Q2FY27, underpinned by strong wins of three companies. Headcount increased slightly sequentially, while attrition and utilisations improved modestly.
Another recent report said that management commentary across nearly all major Indian IT companies during Q1 FY27 earnings season showed that clients demanded measurable outcomes, governance frameworks and stronger data foundations before committing to large-scale AI rollouts.
—IANS
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