Indian IT stocks have lurched with every new frontier AI announcement—a sharper model here, a coding breakthrough there—as investors try to gauge how much of the services model is at risk. But the volatility is not about any single release. It reflects a deeper repricing of how the $300 billion industry earns its margins.
What is under review is not demand, but the mechanics of delivery: How work is billed, how value is measured and how quickly productivity gains flow through to clients.
“There will be volatility for a while,” says Rick Parrish, vice president and research director at Forrester, during a panel discussion at the Nasscom Technology and Leadership Forum 2026. “Although it’s volatile, it’s definitely not momentary. It is the start of a structural realignment.”
Markets are reacting to the pace of AI innovation. Enterprises are moving at a different speed.
“The enterprise is significantly behind in terms of catching up with the technology wave,” says Rajesh Nambiar, president of Nasscom. “You can’t just say enterprises are sitting around. They will move when they see value.”
That gap—rapid model progress, slower corporate adoption—leaves Indian IT firms in the middle. They must integrate fast-evolving AI tools into decades-old enterprise systems, while convincing investors that productivity gains will not simply erode billing.
The immediate pressure point is pricing. AI is compressing effort and accelerating delivery, undermining contracts built on hours worked and headcount deployed.
“There will be some level of cannibalisation in the system to get to the new models,” says Jasjit Kang, managing partner and global head of business process services at Wipro. But, he adds, “the value of work that we deliver is going to go up significantly.”
The direction of travel is clear: Outcome-based pricing and gain-share models are moving from theory to practice. The long-discussed shift away from full-time-equivalent billing is becoming unavoidable as automation lifts productivity.
Hybrid delivery—human expertise layered with AI agents—is likely to dominate in the near term. “If I want to bet, I would bet on hybrid in the short to medium term,” Kang says.
For investors, the central question is who captures the margin when productivity jumps.
“Depends on who invests,” Kang says. “If the service provider is investing, they’re going to recover the investment first and then go into a gain-share model.”
CFOs are accelerating the reset. Parrish describes finance chiefs imposing tight timelines for AI initiatives to prove savings, in some cases linking budgets to quarterly cost targets. The pressure is pushing technology teams to move faster—and pushing providers to defend pricing.
“Boards are getting nervous these days and looking at how quickly they can see value,” says Sindhu Gangadharan, MD, SAP Labs India and chairperson of Nasscom.
That scrutiny is reshaping how value itself is defined. “Are you purely looking at productivity or are you looking at outcomes and value?” she asks—a question that goes to the heart of how services contracts will be structured in the AI era.
The market’s instinct has been to extrapolate from model announcements to margin collapse. Industry leaders argue that view is premature.
“Just because one company releases something and the market reacts doesn’t mean enterprise IT changes overnight,” Nambiar says of sharp stock swings tied to individual releases. “That’s clearly an overreaction. It will go on for a while and then it will settle down.”
Indian IT still derives 62 percent of its revenue from the US, where enterprise systems are deeply embedded and often decades old. Those environments are not rewritten overnight.
“These are complex systems,” Nambiar says. “They don’t get resolved just because an agent came around.”
If anything, AI may expand the addressable market by lowering the cost of modernisation. Enterprises that once postponed upgrades because of expense or risk may now accelerate them.
Parrish notes that US IT services spending is still expected to grow about 4 percent this year, driven in part by the scale of technical debt. “The opportunity to increase margin by modernising all those systems is huge,” he says. “The amount of money companies spend servicing their tech debt is vast.”
In other words, automation threatens some revenue streams while unlocking others. The net effect will depend on how quickly providers pivot.
AI is also collapsing the traditional order of transformation projects. Companies once modernised infrastructure first and layered innovation later. That logic is breaking down.
“All those days are over,” Gangadharan says. “In the past, you would go into a project and say this will take a couple of years and then come back to innovation. Those days are over.”
With AI embedded directly into business processes, companies are redesigning workflows in parallel with modernisation. The result is shorter cycles and sharper expectations.
“Agentic AI is no longer a feature. It is part of the core enterprise architecture,” Gangadharan says.
The implication for service providers is stark: Deliver measurable outcomes earlier, not after years of groundwork.
The labour model that underpinned India’s IT rise is also shifting. Entry-level, repetitive roles are most exposed to automation.
“Traditional commodity roles will shrink,” Kang says.
Demand will rise instead for AI-literate professionals who can design, train and supervise intelligent systems. The familiar pyramid of large junior workforces feeding smaller senior layers is flattening.
One executive describes the emerging structure as an “inverted wine glass”: Fewer junior roles, more specialised expertise and a thicker layer of AI-enabled mid-level talent.
That evolution complicates hiring and cost assumptions. Productivity gains may reduce headcount growth, but high-end skills could command a premium.
For India’s IT sector, the challenge is strategic rather than existential. The competitive advantage is shifting from labour arbitrage to orchestration—integrating frontier models into complex enterprise ecosystems.
“It’s no longer about how many people you have,” Nambiar says. The industry must move from an implementation mindset to what he called an “AI orchestration mindset”.
Not all companies will make that transition equally well. Some will adapt pricing models, invest in AI capabilities and protect margins. Others will struggle to reset contracts built on headcount economics. That divergence is likely to become clearer in earnings and valuations over the next two years.
The sell-off in IT stocks reflects genuine uncertainty about how fast AI-driven productivity will flow through to pricing. But the deeper shift is structural rather than terminal.
As Parrish puts it, the industry is entering “a structural realignment”. Markets are beginning to reprice the services model, not because demand has vanished, but because the economics of delivery are being rewritten.
For investors, the question is no longer whether AI will change Indian IT. It is which companies will change fast enough to capture the upside without diluting their margins.
First Published: Feb 25, 2026, 20:39
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