AI is breaking India's IT fresher pipeline, Tier-2 and Tier-3 talent hit hardest

For nearly three decades, there was a reliable script many families in India’s Tier-2 and Tier-3 towns followed, especially across the southern states. Finish an engineering degree, add a short-term testing or full-stack course, crack a small IT services firm, and slowly climb into a bigger company.

It was never glamorous, but it worked. And more importantly, it felt predictable and therefore, comfortable.

That escalator -- the one that carried thousands of young graduates from smaller towns into the middle class -- is now buckling. Artificial intelligence has begun eating away at the very roles that once formed the first rung of IT employment.

ROUTINE WORK DISAPPEARING, ENTRY-LEVEL ROLES GOING WITH IT

At the heart of the old IT pipeline were routine, low-leverage tasks such as manual testing, basic CRUD development, repetitive backend work, and scripted automation. These were never high-status skills, but they were employable ones.

Today, those tasks are increasingly handled by AI systems which are faster, cheaper, and without fatigue.

Jayaprakash Gandhi, a career consultant and long-time analyst of engineering education trends, puts it bluntly.

“The initial entry-level jobs, especially in IT and computer science, are getting replaced by advancements in AI and newer computing methods,” he says, pointing not just to generative AI, but to shifts in high-performance and high-throughput computing as well.

“The basic knowledge of coding or electronics is no longer enough to get entry-level jobs,” Gandhi adds.

While jobs still exist in IT and core companies, he stresses that freshers now need exposure to newer technologies, from AI tools to building AI agents, just to remain employable.

Ritwik Batabyal, CTO and Innovation Officer at Mastek Group, echoes this shift from the industry side. Earlier, he notes, freshers learned on the job by doing routine IT work. “AI is now doing a lot of that work, so those roles are shrinking. But learning doesn’t stop, it just looks different.”

Instead of fixing small pieces of large systems, Batabyal says graduates will increasingly gain experience through real projects, industry-academia programmes, innovation labs, internships that actually build products, and startup-style environments.

“The focus is shifting from ‘doing tasks’ to building solutions,” he says.

Crucially, he argues that responsibility does not lie only with students. Companies, too, will need to redesign entry-level roles -- moving away from mass fresher batches doing routine work to “smaller cohorts mentored to work alongside AI systems.”

That shift, he suggests, aligns with the reality of fewer but better entry-level jobs, rather than no jobs at all.

TIER-1 CONVERSATIONS, TIER-2 CLASSROOMS

The deeper problem is not AI itself, but the lag in understanding.

In Bengaluru’s tech circles, conversations have moved on to copilots, AI agents, prompt-driven workflows and outcome-based roles. But in Tier-2 and Tier-3 towns, the conversation is still stuck on which course offers better placement, which institute promises “100% jobs”, and which syllabus matches interview questions.

Gandhi agrees that this gap is real. “Yes, full-stack and DevOps are still being taught in Tier-2 and Tier-3 colleges, and yes, much of it is getting outdated,” he says.

He argues that students who already have basic full-stack knowledge must now double up into areas like platform engineering, DevSecOps, and AI supercomputing platforms, where demand actually exists.

While he notes that a handful of Tier-2 institutions have begun updating training seriously, he is clear that most have not. “Very few colleges are doing this. We need awareness across the entire system,” he says.

The result is visible everywhere: resumes flooded with identical keywords such as Selenium, Java full stack, and React basics even as companies stop hiring for those roles.

EXPERIENCE HASN’T VANISHED, THE WAY YOU EARN IT HAS

One common question follows naturally: if entry-level IT roles are disappearing, where will graduates get experience?

According to Jaspreet Bindra, Co-founder of AI & Beyond, the idea that experience must come only from traditional entry-level jobs is itself outdated.

“For years, entry-level IT jobs were where young professionals learned by doing repetitive work,” he says. “That layer is thinning out because technology can now handle many of those tasks.”

But experience, Bindra argues, hasn’t disappeared -- it has simply changed form.

“Graduates will gain experience by working on real problems much earlier,” he says, through meaningful internships, startups, open-source projects, campus-industry programmes, or self-driven projects that solve actual business issues.

“The old model rewarded time spent. The new model rewards evidence of thinking and execution,” he says.

Batabyal reinforces this shift, noting that graduates who “experiment, create, and learn by doing, even outside traditional jobs, will be the ones who stand out.”

THE REAL SKILL GAP: JUDGEMENT, NOT TOOLS

Across experts, one idea keeps returning: tools will keep changing, bit judgement will not.

Bindra is explicit about what freshers must now focus on. They need to learn how to properly understand a problem before jumping to solutions, how to question AI outputs instead of accepting them blindly, and how to see the larger business or societal context.

“Technology can produce answers very quickly,” he says. “But it cannot decide what really matters, what is appropriate in a given context, or what could have unintended consequences. That responsibility still sits with humans.”

Batabyal sharpens this further. In an AI-driven setup, he says, freshers are no longer just coders. “They are reviewers, integrators, and decision-makers who must understand trade-offs, risks, and system-level impact, including failure modes like bias, hallucination, security and compliance,” he says.

That framing moves the conversation from abstract “critical thinking” to applied responsibility. This can position India’s young workforce not as AI’s victims, but as its supervisors.

Samiron Ghoshal, Senior Advisor at Odgers India, frames the same issue from a talent and hiring lens. As AI takes over routine tasks, freshers must learn how to assess AI system performance, troubleshoot complex integrations, and decide how AI solutions should be deployed across industries.

“These judgment skills -- adaptability, contextual decision-making, and the ability to work alongside AI -- are what will keep freshers employable,” he says.

A SOCIAL CONTRACT AT RISK

If this skill mismatch continues in fresher hiring, the impact will go far beyond hiring statistics.

Gandhi warns of social and economic fallout if colleges and students fail to adapt. Graduates may be pushed into unrelated work or prolonged underemployment.

“We need to bring awareness to students as well,” he says. “They cannot expect everything to be taught in college anymore. Self-learning has become essential.”

Batabyal adds a sharper warning: if the transition is mishandled, Tier-2 and Tier-3 regions risk producing “large numbers of degree-holders who are technically qualified on paper but economically sidelined.”

Bindra echoes the concern but also highlights the opportunity. Location matters far less today than it once did, he says. With the right skills, a student from a smaller town can work on meaningful global projects without moving to a metro.

“The real risk isn’t technology replacing jobs,” Bindra says. “The real risk is not updating how we prepare people for the jobs that are emerging.”

These insights essentially explain how to overcome the chronic problem India’s graduates have been facing of possessing degrees but not the right skills, and thus, not the right jobs.

Ghoshal places the moment in historical context. India has adapted before -- from Y2K to the dot-com era -- by retooling its workforce rather than resisting change.

But he warns that the next 6 to 12 months are critical. If aggressive upskilling does not happen soon, Tier-2 and Tier-3 cities could face a serious setback in upward mobility.

FROM LEARNING TOOLS TO LEARNING JUDGMENT

The old IT escalator was built on predictability. AI has quietly dismantled that certainty.

What replaces it cannot be another wave of short-term courses promising placements. The shift now has to be deeper -- from learning tools to learning judgment, from syllabus completion to problem-solving maturity.

As Batabyal puts it, this shift does not mean fewer opportunities for India -- “it means fewer default opportunities and more earned ones.”

If that shift happens, AI could become an equaliser. If it doesn’t, it risks breaking a long-standing social contract that Tier-2 and Tier-3 India trusted for decades.

And this time, the cost of delay will be borne by those who can least afford it.