With Indian IT Entry Roles Automated, Freshers Now Need Meta Skills

For decades, India's IT services industry ran a quiet bargain with its entry-level workforce. Companies like Infosys, TCS, and Wipro hired engineering graduates by the tens of thousands, often from streams far outside computer science, brought them to sprawling training campuses, and spent six months turning raw talent into deployable engineers. 

The graduates came unprepared, yet they were hired.

That bargain is being renegotiated. Companies now expect entry-level engineers to show significantly higher readiness, including familiarity with AI-assisted development, problem-solving skills, and the ability to build production-grade applications much earlier than before.

"The bar has raised sharply, not a little, because of AI," Soumitra Mishra, a principal engineer-turned-educator who now leads academics at the upskilling startup Newton School of Technology, tells AIM.

In 2013, when Mishra graduated, knowing one programming language reasonably well was enough to clear most campus placements. By 2020, companies wanted to ascertain familiarity with frameworks, including React.js on the front end and Spring Boot on the back end, by asking candidates to write APIs and demonstrate how they could handle a modern stack.

"Now, in 2026, the expectation is that you should be able to fully develop an application. That is the job," he says. "They will give you a complex application to build in two days, sometimes 24 hours, as the first round. In 2013, that same assignment would have taken me 10–15 days if I were good at it."

The tools that once had a competitive edge, like code generation, intelligent autocomplete, and agentic workflows, are now the baseline expectation. A fresher who cannot leverage them fluently is not just at a disadvantage; they are, in the eyes of most hiring managers, not industry-ready at all.

“Earlier, they used to give a problem and then tell a solution. Now, they are trying to tell their people: this is the problem, don’t just find me a solution, find me the next six solutions,” says Raghav Gupta, CEO and Founder of Futurense, an AI-native skilling platform.

Much of it is driven by the pressure on the pyramid model of IT services companies, as AI increases both productivity and redundancies. 

The Compression Begins

According to Neeti Sharma, CEO of staffing firm TeamLease Digital, AI will automate between 30–35% of entry-level tasks across IT services over the next three to five years. The roles most exposed are software testing, Level 1 support, and routine coding. Yet Sharma is careful to distinguish compression from collapse—only 15–20% of roles face full elimination. 

The majority will be reshaped, augmented by tools that auto-generate boilerplate code, triage support tickets, and flag anomalies before a human ever sees them. In other words, the industry is not heading toward a cliff edge. It is facing a narrower staircase. 

“The pyramid model isn’t disappearing, but it is inverting. There will be fewer entry-level roles, a thinner middle, and a sharper concentration of high-skill, AI-enabled talent at the top,” says Saravanan Balasundaram, Founder and CEO of business consulting and talent solutions firm Han Digital Solution.

“Automation risk at the entry level is significant. Based on our industry conversations, 30–40% of current entry-level roles are at meaningful risk over the next 3–5 years,” he adds.

Senior-to-junior ratios, historically stable at 1:8 to 1:10, are already trending toward 1:4 to 1:6 at forward-looking firms, per TeamLease Digital. The economics are simple. When AI can handle the first pass on a test suite, resolve the top support queries without human involvement, and generate unit tests from a specification, companies no longer need 10 junior engineers to do what three can now manage.

The Meta-Skill Shift

The implication runs deeper than learning a new tool. As AI handles more of the mechanical work of writing code, the skills that distinguish a valuable engineer are shifting toward what might be called the human layer: judgement, problem-solving, and the ability to reason about a system rather than just execute within it.

That transition is also pushing engineers into more client-facing roles. Companies increasingly want developers who can understand business workflows, interact with customers, and use AI tools to rapidly build solutions around client needs.

“Over the last about 12–18 months, we have received a lot of calls from talent acquisition leaders asking whether there are tools in the market that can qualify candidates on meta skills,” Balasundaram says. 

“If I put 100 candidates into a platform, can it identify people with stronger foundational skills and those who are ready to learn? That’s become a big area of focus, but not many existing tools are able to offer meta-skills assessment effectively,” he adds.

The Bench, Reimagined

The six-month bench training programme—India's corporate finishing school for underprepared graduates—is under pressure from both ends. Firms need fewer juniors, but they still need to be equipped with the necessary skills.

"Bench-keeping was never really about training—it was about headcount guarantees for clients. That part is not going away immediately. What will change is how many people are on that bench," believes Soumitra.

The bigger risk is what happens a decade from now. If the base of the pyramid thins significantly, the pipeline that produces tomorrow's senior talent thins with it. Companies cannot hire their way out of a missing mid-career cohort.