Indian IT’s Mid-Senior Layer is Getting Squeezed in the AI Shift

When TCS CEO K Krithivasan recently said at a Nasscom event that senior employees are slower to adopt AI than younger staff, he was pointing to more than a generational skills gap.

The comment reflects a deeper structural tension within Indian IT—an industry built on a headcount-driven delivery model, quarterly performance pressures, and incremental efficiency gains rather than disruptive reinvention.

As AI begins to challenge these fundamentals—compressing effort, automating workflows, and reducing reliance on large teams—the industry is being forced to confront a harder question: how can it reinvent its workforce structure fast enough?

Krithivasan also indicated that constraining traditional sources of revenue may be inevitable if AI adoption needs to be fast-tracked.

“We encourage our associates to go out… and use AI… even if it means cannibalising our revenues,” he said.

The Constrained Middle

That tension is most visible in the second rung of leadership—business unit heads, delivery leaders, and large account owners—who are responsible for executing strategy, but do not control it.

In a conversation with AIM, Saurabh Gupta, President (Research and Advisory Services), HFS Research, notes that middle management is under the most strain because they are “neither AI native, nor in a leadership position to be able to control it.”

But the issue is not simply a lack of skills.

These roles are still measured on traditional metrics such as revenue growth, billable utilisation, and margins within existing accounts. AI, by contrast, reduces effort, compresses pricing, and shrinks team sizes. For those running delivery, adopting AI too aggressively can directly undermine their own performance metrics.

At the same time, AI strategy, investments, and client positioning are driven at the CXO level. This creates a structural disconnect: the people expected to execute the transition are not fully empowered—or incentivised—to drive it.

This is not necessarily active resistance. Instead, it manifests as slower adoption and cautious execution, shaped by the need to protect existing business.

As IT services firm Humanizetech.ai’s CEO Jagdish Mitra explains, the challenge cannot be separated from the industry’s operating model. “Publicly traded companies have quarterly pressures to constantly meet their numbers. But this time, the shift is not just about technology—it challenges the core of what the IT services model was built on.”

Indian IT has navigated multiple technology transitions before—from mainframes to client-server, from custom development to packaged software, and later to digital transformation. In each case, the industry adapted by reskilling talent while retaining its underlying delivery model.

AI is different

“The difference now is that you can do the same work with far fewer people,” Mitra says. “Earlier, the game changed, but you still needed 11 players. Now, one person can do the work of three.”

This alters the economics of delivery itself. And for middle management, the trade-offs are immediate. Driving AI-led efficiency can mean smaller teams, lower billing, and potential erosion of their own roles. Holding back, however, risks falling behind as clients demand greater productivity.

The result is a constrained middle—caught between protecting current revenue streams and adapting to a model that increasingly makes those streams less relevant.

Execution is the Real Gap

Meanwhile, HFS CEO Phil Fersht points to a disconnect inside organisations.

“There’s also a leadership vacuum… the top level (CXO) understands this (AI potential)… it’s the next level, the C minus one, minus two (business unit heads, delivery leaders, or large account owners who report directly to the CEO or other C-suite leaders),” he observes.

Firms are caught between short-term performance and long-term reinvention. “This struggle between quarterly demands, maintaining the existing business, and investing in the new is a massive problem.”

That tension in maintaining the workforce structure is already showing up in slowing revenue figures.

TCS reported just 0.8% sequential constant-currency growth in Q3 FY26 even as its workforce shrank by over 11,000 employees, while maintaining a 25.2% operating margin. Infosys posted 0.6% growth in the quarter, with headcount rising marginally to 3.37 lakh, even as utilisation dipped to 84.1%. Meanwhile, HCLTech led with 4.2% growth despite a largely flat headcount, and Tech Mahindra improved margins to 13.1% even as employee numbers declined year-on-year.

Even where alignment exists, execution is constrained.

Praveen Bhadada, CEO and Managing Director of consulting firm Neovay Global, believes the problem is not intent. “The issue is not really alignment… it is really an issue of balancing the two—protecting the core while transforming to the new.”

That balance is shaped by constant performance pressure, but incentives also reinforce the problem.

In most IT services firms, a significant share of compensation—especially at mid- and senior levels—is tied to revenue growth, utilisation, and margins in existing accounts. This creates a structural bias towards protecting current business lines, even as firms push for AI-led transformation.

AI, meanwhile, still contributes a relatively small share of revenues, making it easier to delay change. According to Nasscom’s Annual Strategic Review 2026, the total AI revenue for Indian IT in FY26 was estimated at $10–12 billion, merely 4% of the total industry revenue.

At its core, the transition to AI requires IT services firms to replace billable human effort with automation, effectively disrupting their own model. 

At the top, leadership understands the shift. At the bottom, AI-native talent is emerging. In the middle lies the constraint.