INDIA CURRENTLY HAS about 42 million students pursuing higher education—from undergraduate and postgraduate programmes to doctoral research. Of these (including UG, PG, integrated programmes, MPhil, and PhD), around 4.63 million are enrolled in engineering education. At the undergraduate level alone, 4.39 million students are studying engineering and technology (31.1 per cent are women), making engineering the country’s third-largest undergraduate discipline.
As I write this, another two million students will soon enrol in BTech, BE and related programmes. However, this is where the real concern begins.
Most of us already recognise that much of what is being taught today may no longer be relevant—and may even become obsolete—by the time these students graduate around 2030. Never before has the relevance of higher education been under such intense scrutiny. We still do not know the full extent of the capabilities AI will acquire or which human skills it will eventually replace.
For any nation, these are worrying numbers. For India, they are not merely about economic growth but about national survival. What is often celebrated as our demographic dividend could quickly become a demographic nightmare if we fail to prepare. Unemployment is already a serious concern. Now imagine millions of unemployed graduates. Add to that graduates burdened with education loans and unable to find meaningful work. The consequences for our institutions, economy and social stability would be profound unless we urgently rethink what we teach, how we create jobs and how we make our graduates employable.
Recently, TCS chairman Natarajan Chandrasekaran said: “I predict that over the next three years, TCS will have as many AI agents as human employees.” He elaborated: “If the company has half a million employees, the day is not far when it will also have half a million AI agents. Human employees and AI agents will work together, and that will be the future.”
While ruling out mass layoffs, Chandrasekaran also acknowledged that the era of large-scale IT hiring is unlikely to return. The numbers already reflect this shift. TCS’s workforce declined from 6.13 lakh employees in June 2025 to 5.93 lakh in June 2026. Similar trends have been visible across major IT services companies, including Infosys, Wipro, HCL and Accenture.
Nor is this an Indian phenomenon. Amazon cut 30,000 jobs. Microsoft cut 16,000 jobs in two rounds during 2025 and has announced further reductions for 2026. Meta reduced about 10 per cent of its workforce. Google, Microsoft, Adobe—virtually every major technology company is restructuring and trimming headcount.
Today’s student therefore is at a crossroads: shrinking employment opportunities, rising education costs, declining educational quality and the prospect of AI disrupting entire categories of human work.
NVIDIA founder and CEO Jensen Huang has repeatedly advised students not to become obsessed with choosing an “AI-proof” degree. His message is straightforward: study a subject you genuinely care about, master it deeply and learn to use AI to become dramatically better at it.
He has also said: “If I were a 20-year-old today, I would probably choose a physical sciences field rather than a software sciences field.” He explained: “The next wave of AI is physical AI. It is AI that understands the laws of physics.”
Elon Musk expressed the same sentiment in July 2025 when Telegram founder Pavel Durov said, “If you’re a student choosing what to focus on, pick math.” Musk responded: “Physics (with math).”
The people leading the AI revolution appear to be placing their bets not on narrow technical skills but on the foundational disciplines—particularly mathematics and physics.
So what should educational institutions do? And how should students make their choices? The answer may lie in returning to first principles.
The emphasis must shift towards the pure sciences, especially mathematics and physics. Many skills that currently command a premium are likely to become increasingly automated. Coding, radiology, data entry, first-level customer support, call centres, manual software testing, transcription, elementary translation, routine research, information compilation, accounting, invoicing and bookkeeping are all susceptible to AI-driven disruption. Trade schools and skill-development institutions will have to fundamentally redesign their curricula to reflect this new reality.
Students must understand why a physical law or mathematical equation works—not merely how to substitute values into a formula. They should be able to derive a mathematical result from first principles rather than simply recognise the correct answer in a multiple-choice examination.
They must learn to reason through unfamiliar problems, identify flaws in AI-generated answers and ask better questions. Whatever direction technology takes, these abilities will remain distinctly human. AI should become a tool for verification and augmentation—not a substitute for thinking.
For educational institutions, this means resisting the temptation to dilute rigorous maths and science education in favour of fashionable skills that may soon be automated. Universities must prepare students not merely to secure their first job, but to build careers that can endure technological disruption. Deep conceptual understanding will become the true competitive advantage in the age of AI.
In the years ahead, AI will make breadth inexpensive; depth will become the premium. As generations of students have increasingly been trained to crack entrance examinations dominated by multiple-choice questions, the need for conceptual clarity has never been greater. Rote learning will become obsolete. Asking the right questions will no longer be optional. Expertise, not familiarity, will define success.
The question is: Are we prepared for the AI tsunami?
The writer is entrepreneur, educationist and Careers360 founder.
