India's 60 Lakh Tech Workforce is Growing—But Not On Par With AI Revenue Surge

India's technology workforce is still expanding, but the hiring model that built the country's IT services industry is beginning to change. 

The industry added around 1.35 lakh net new jobs this fiscal year, taking the workforce past 60 lakh. Yet revenue is growing much faster than headcount. 

According to TeamLease Digital's Digital Skills & Salary Primer 2026–27 report, India's tech industry is projected to grow 6.1% to $315 billion in FY27, while headcount rises just 2.3%.

"Hiring has not stopped, but it has changed," Neeti Sharma, CEO of TeamLease Digital, tells AIM. "We will definitely see fewer hires for routine work like manual testing, basic support, software development, and repetitive reporting. However, we will see strong demand for people who can build, run, secure, and govern AI systems."

The shift is not simply about fewer technology jobs. It is about what companies are willing to pay for, whom they want to hire, and where that talent can sit.

For years, India's advantage was the IT services arbitrage model comprising large pools of engineering talent doing software development, testing, maintenance, support, and back-office work at lower cost than comparable teams in developed markets. Scale was the advantage.

AI is challenging that equation. As AI tools automate parts of coding, testing, support, documentation, and reporting, repetitive work is becoming redundant, and so it are the resources executing it. 

Infosys, TCS, and Wipro have already taken Copilot deployments to over 3 lakh employees, reporting 20–25% productivity gains in selected workflows.

The Big Rethink

The report described a "two-speed" talent market. Advanced AI, data, cloud, cybersecurity, and governance roles are expanding, while routine execution roles are being compressed. 

Roles such as manual testing, basic operational support, and rule-based processing and documentation are being compressed. Meanwhile, roles where pay growth increasingly depends on combining core expertise with AI and domain knowledge—including AI-assisted business analysis and automated testing—are being repriced.

"We are already seeing that entry-level absorption is slowing, and billable-headcount utilisation models are under transformation. The shift is towards outcome-based and IP-led delivery, where you are paid for outcomes, and not just for effort. The arbitrage won't disappear overnight, but it's no longer where the growth is," she adds.

The composition of employment rather than simply shrinking. Roles including AI-native product development and those overseeing enterprise data foundations, cloud infrastructure, and security for AI-enabled systems are on the rise. There’s also a growing requirement for AI workflow design, AI governance, enterprise risk management, and AI outcomes validation.

Hiring Differently

Sharma sees three forces behind the slowdown in volume hiring. 

"First, AI is doing more of the routine work. Many companies have given access to various AI tools and are seeing 20–25% productivity increase in some workflows. Second, companies are moving from trying AI to actually running it. That shifts demand away from volume hiring and towards specialists in AI, data, cloud and cybersecurity. Third, these skills are scarce right now in India."

The scarcity is real. According to the report, only about 16% of India's IT professionals hold AI skills—roughly 20 lakh upskilled and only about 3 lakh in advanced AI. It puts the supply gap at about 53% in GenAI, 55–60% in cloud, and 25–30% in cybersecurity.

Companies increasingly need people who decide which tasks to automate, how AI is deployed, how its output is controlled and what happens when it fails. 

The value has moved from execution to ownership, and hiring teams are finding it hard to hire the cream. One HR leader interviewed for the report tells AIM anonymously that they find many candidates who take AI output at face value, without the domain knowledge to catch errors.

Industry is Also Changing

Technology talent is no longer confined to IT-services companies. Banks, insurers, retailers, manufacturers, healthcare companies, and telecom operators are becoming technology employers themselves.

Global capability Centres (GCCs) are central to this. Sharma says they are "the strongest part of the market right now." 

India has 2,117 GCCs employing 23.6 lakh professionals and generating$98.4 billion in revenue. GCCs lead India Inc on pay, with a 2026 salary increment of 10.4% against a 9.1% average, and their attrition is lower, at 14.1% against 16.4% for the market.

"What's changing is what they hire for," Sharma says. "As GCCs move from cost centres to owning global products and platforms—and 44% have already reached that stage—the demand is for AI, data, cloud, and security talent. Routine support roles aren't where the premium is." 

Outside the tech sector, digital roles are growing faster than overall headcount in every sector the report studied. 

Digital talent makes up about 40% of white-collar roles in BFSI, 25% in manufacturing, and about 20% in retail. Salary premiums there follow domain-linked digital depth. Risk data scientists, industrial data engineers, computer vision engineers, and OT security analysts reach ₹30–34 lakh by 6–8 years.

The Real Disruption

The most important consequence of AI may not be job losses but the collapse of the old hiring pyramid. The traditional model brought in large numbers of junior workers, trained them, and deployed them across standardised projects. AI can now absorb some of the repetitive tasks that made that model scalable.

The report names this strain directly: entry-level absorption is compressing as revenue outpaces hiring, and billable-headcount utilisation models are under pressure. 

Sharma sees three priorities for the industry: "Rebuild the pyramid around AI-skilled talent instead of a wide base of freshers, price for outcomes instead of hours, and reskill the entry layer so young professionals aren't left behind." 

That makes reskilling critical. The report finds only about one in three organisations has reached AI maturity Level 3 or above, and roughly 86% of leaders say their organisations are not very prepared to adopt AI in day-to-day operations. 

The advice is to build and reskill rather than buy, because there is no prepared AI talent to hire.