Perspectives

There are moments that cut through the fog of diplomatic niceties and reveal the brutal mechanics of modern power. One such moment arrived when Microsoft, in compliance with a US executive order, suspended the email account of an International Criminal Court prosecutor investigating an American ally. For European leaders, this was a jarring wake-up call: an American company providing essential digital infrastructure had become an instrument of foreign policy. As one Dutch parliamentarian put it, the threat of technological coercion is not just fantasy.

This observation is correct — but incomplete. It diagnoses the symptom, not the disease. The more profound truth, the one that should keep Indian policymakers awake at night, is this: there cannot be technology sovereignty without technology democratisation.

India’s innovation ecosystem is not a pyramid. It is an inverted spire, balanced precariously on its narrowest point. Three urban clusters account for 83% of unicorns and 92% of all startup funding. India has a mere 216 researchers per million inhabitants — against China’s 1,200 and the US’s 4,300. India files 64,480 patents annually; China files 1.64 million. These are not marginal differences. They are the anatomy of a structural failure.

This flaw has a historical cause. In the aftermath of independence, India made a deliberate choice to create “temples of modern India” — elite institutions like the IITs — rather than build a broad-based educational foundation. For a young, resource-starved nation, this was logical. But what was rational in 1947 has calcified into a profound bottleneck. The IITs and IIMs remain islands of excellence in a vast sea of underinvestment. The vast majority of India’s graduates remain outside the innovation pyramid — not because they lack capability, but because they lack exposure, networks, and infrastructure.

Meanwhile, China pursued a radically different strategy: mass mobilisation. Its gross enrollment rate in higher education exploded from 3.6% in 1991 to over 17% by 2003. It built the world’s largest vocational education system — 11,133 institutions enrolling over 35 million students — and tightly integrated it with industrial demand. The result: 3.57 million STEM graduates annually, a complete end-to-end ecosystem from research lab to factory floor.

The advent of Artificial Intelligence makes this divergence existential. AI is not just another technology wave. It is a foundational paradigm shift. And for India, it represents a fork in the road: either it becomes the tool that finally democratises knowledge and opportunity on a massive scale, or it permanently cements the chasm between a tiny empowered elite and the vast excluded majority.

The solution cannot be another top-down, centrally planned scheme. The only viable path is to build in parallel — urgently, and from the bottom up. A decentralised ecosystem anchored in Tier 2 and Tier 3 cities, in regional colleges, in the towns where India’s hardest problems live. To miss this moment would be a historic, and perhaps final, failure of imagination.

Bihar, Jharkhand, Odisha, and Chhattisgarh together hold nearly 17% of India’s population — a massive reservoir of human potential. Yet as of early 2025, they contributed a mere 5.8% of the nation’s recognised startups. When AI interest is indexed across Indian states, Bihar scores 22 out of 100 while Telangana scores 100. This is not merely an economic gap. It is a compounding civilisational debt.

With each missed wave of technological change — from IT to fintech — the chasm has only widened. The toll is visible in the steady stream of talent compelled to leave for Bengaluru or Hyderabad, draining these regions of their most precious resource and fuelling a cycle of perceived failure that deters the very investment needed to break free.

Yet this same asymmetry contains within it a rare opportunity. AI — unlike earlier waves of IT or fintech — does not require the dense physical infrastructure or legacy networks that historically favoured metros. It runs on digital connectivity, intellectual curiosity, and proximity to real problems. These states have the last ingredient in abundance. Their students understand local challenges — agricultural supply chains, tribal healthcare, financial inclusion — in ways that no Bengaluru-based startup can replicate from a distance.

National projections indicate AI could inject nearly $957 billion into India’s economy by 2035. These states, with their significant share of the population, risk missing up to $287 billion of that growth if AI adoption continues to lag. Beyond economics: with India facing a looming shortfall of over one million AI professionals by 2026, these states will be disproportionately ravaged by brain drain unless local opportunity is created urgently.

The AI revolution is still young. Its territories are largely unclaimed. This is a pivotal moment — perhaps the first in decades — where lagging regions can genuinely leapfrog. But it requires acting now: building Centres of Excellence locally, connecting students to mentors and problem statements, and creating pathways where a student’s ambition in technology is never limited by their PIN code.

The window is open. It will not stay open long.

In 1893, at the World’s Parliament of Religions in Chicago, Swami Vivekananda made a remark that reads, in retrospect, like a prophecy:

He saw science not as an adversary to spirituality but as its complement — two paths converging on the same truth. More than a century later, as AI becomes the primary interface through which millions of young Indians encounter information, moral questions, and existential inquiry, his vision becomes urgent again.

The hypothesis this article explores: the deeper one’s understanding of Sanatan Dharma, the better equipped one becomes to build and use AI systems rooted in objective truth, universal welfare, and ethical strength.

Consider what Sanatan Dharma offers that the AI era most needs and most lacks. Its scientific temperament — from Kanada’s atomic theory (600 BCE) to Ramanujan’s intuitive mathematics — demonstrates a civilisational tradition of rigorous inquiry untethered from dogma. Its pursuit of satya (objective truth) — “Satyameva jayate” — offers an ethical compass for AI builders who must navigate a world of hallucinations, biases, and manipulated outputs. Its ontological unity — Vasudhaiva Kutumbakam not as sentiment but as metaphysics — counters the fragmentation and exploitation that characterise many AI systems today. And its pluralism — “Ye yathā mām prapadyante tāms tathaiva bhajāmy aham” (In whatever way people approach Me, I reward them accordingly) — ensures that AI adapted to this framework accommodates diverse paths without suppressing any.

As AI democratises inquiry — stripping away the layers of commercial search results and algorithmic manipulations — it draws seekers toward unfiltered dialogues on existence, meaning, and ethics. In this environment, Dharma’s pluralistic, accommodative framework may emerge not as a relic but as a beacon.

Vivekananda foresaw science and spirit converging. The AI era may be the moment that convergence becomes impossible to ignore.