The Unsexy Revolution: Why India's AI Strategy Might Actually Work
I’ve been watching the AI arms race unfold with a mixture of fascination and dread for a while now. Every week brings another announcement about some massive AI model that’s supposedly going to change everything, backed by billions in funding and wild promises about achieving artificial general intelligence. It’s exhausting, frankly. So when I came across India’s latest budget announcement committing $90 billion to AI infrastructure, I expected more of the same – another country trying to build their own GPT-killer and join the race to the bottom.
But here’s the thing: they’re not doing that at all.
India’s approach is refreshingly pragmatic. Instead of trying to compete with OpenAI or Anthropic in building ever-larger foundation models, they’re explicitly pushing for “smaller, sector-specific models” and an application-led approach. They’re talking about things like Bharat-VISTAAR – a multilingual AI system for crop planning, pest alerts, and market prices. Not sexy. Not going to make headlines in TechCrunch. But potentially transformative for the 46% of India’s workforce that’s in agriculture.
This matters because it represents a fundamentally different philosophy about what AI is actually for. The discussion I was reading had someone pointing out something rather disturbing about the Silicon Valley AI billionaires – that many of them are genuine transhumanist zealots who see AGI not as a tool to solve problems, but as some kind of digital deity that will transcend humanity itself. That interview with Peter Thiel where he suggested humanity shouldn’t prevail? Yeah, that was wild and deeply unsettling.
The contrast couldn’t be starker. On one hand, you’ve got people burning astronomical amounts of money and energy (let’s not even get started on the environmental footprint) chasing a dream of digital godhood. On the other, you’ve got a policy that says: what if we just… solved actual problems?
The sceptics in the discussion were quick to dismiss this. One person kept asking “what are these startups building exactly?” – clearly implying the answer was “nothing useful.” But that’s exactly the wrong question, or at least it’s premature. India’s creating an environment where people can build things – tax holidays for cloud providers until 2047, semiconductor manufacturing capabilities, shared compute resources for startups. They’re laying infrastructure, not dictating outcomes.
There’s something here that resonates with my DevOps background. The best infrastructure doesn’t force a particular approach – it enables possibilities. You don’t build a CI/CD pipeline that only works for one specific application; you build something flexible that lets teams ship what they need to ship. India’s essentially doing infrastructure-as-a-service at a national level, with policy guardrails that encourage practical applications over moonshots.
I’ll admit, when I first saw that $90 billion figure against India’s $4 trillion GDP, my immediate reaction was similar to one commenter – it seemed disproportionate. But then you realize this isn’t just government spending; it’s meant to attract private investment and create an ecosystem. The government’s role is to de-risk the infrastructure play and set policy direction. The actual builders – those 890+ GenAI startups – will determine what gets built.
And yes, India still has massive poverty and inequality issues. Someone in the discussion suggested the money would be better spent on universal basic income. But this is where pragmatic policy beats ideological purity. India’s already running one of the world’s largest direct benefit transfer systems, reaching over 300 million people. They’re not choosing between helping the poor or building AI infrastructure – they’re doing both. It’s possible to walk and chew gum simultaneously.
What really strikes me about this approach is how it sidesteps the entire “AGI race” framing that dominates Western discourse. The Economic Survey even explicitly warns against the “narrow pursuit of scale for its own sake.” That’s not just policy wonk-speak – it’s a philosophical rejection of the bigger-is-better mentality that’s driving so much wasteful spending elsewhere.
Will it work? Honestly, I don’t know. There’s plenty that could go wrong – corruption, bureaucratic inefficiency, startups that promise the world and deliver nothing. But at least the strategy makes sense. Focus on real applications, build the infrastructure to support innovation, and let the market figure out what’s actually useful.
It’s a reminder that sometimes the best approach isn’t the flashiest one. Sometimes it’s just competent policy making, targeted investment, and a clear-eyed view of what you’re actually trying to achieve. Not digital godhood. Not the singularity. Just better crop yields, more accessible healthcare, and governance systems that actually work for regular people.
Maybe that’s the real revolution – remembering that technology is supposed to serve humanity, not replace it.