AI and Indian IT: disruption, pricing, and the next growth engine.

Automation challenges the billable-hours model. The investment case depends on who captures the productivity gains.

The investment question

AI can reduce the effort required for coding, testing, maintenance, and support. For contracts linked to staffing or billable hours, fewer hours can mean lower revenue unless new work offsets the reduction. This is a scenario analysis, not a claim that all Indian IT companies face the same outcome.

Where the pressure may appear

Clients may negotiate productivity savings into renewals, while providers fund reskilling and new delivery capabilities. Higher revenue per employee alone does not prove stronger pricing power: headcount reductions can improve that metric while overall growth slows.

Where opportunity may emerge

Enterprise integration, data modernisation, cybersecurity, governance, and industry expertise can create implementation demand. Outcome-based contracts may allow capable providers to retain part of the efficiency gain, although execution and pricing risks remain.

Evidence to monitor

Compare organic constant-currency revenue growth, deal conversion, contract pricing, utilisation, operating margins, and cash flow. Separate incremental AI revenue from relabelled existing work. TCS’s FY26 disclosure describes AI-led services and enterprise transformation demand; management commentary is evidence of activity, not proof of sector-wide investment returns.

Portfolio implication

Assess companies individually. A lower P/E can reflect deteriorating earnings expectations. Test whether new demand and retained productivity gains can offset pressure on legacy services before treating a correction as an opportunity.

For research and education. Not personalised investment advice or a promise of returns.