India must build foundational AI models—not just AI applications
There has been a growing discourse questioning the rationale behind India investing in Foundational AI Models (FAIM), claiming they are yesterday's opportunity, open-sourced, a dozen of them already exist and that India's focus should instead be on building applications—replicating the IT services playbook. This sentiment echoes several doyens of the Indian IT industry. This perspective, however, is limited.
AI is not just another technology like mobile or cloud—it's a fundamental shift in computational capability. It's the new power lever shaping global economic, technological, and geopolitical dynamics. To treat it purely as a tactical business opportunity is to miss the forest for the trees.
AI today is akin to nuclear tech, quantum computing, cryptography, or space minerals mining. Nations that master these foundational capabilities won't just innovate faster—they'll dominate. The question isn't whether India should 'catch up' on FAIM. It's whether we want to participate at all in the next wave of
AI innovation
—especially as we inch closer to
Artificial General Intelligence
(AGI).
To do that, India must cultivate a deep expertise & suitable talent pool. Creating proprietary FAIM from scratch is not the end goal; it's a training ground. It produces the talent needed to build tomorrow's AI breakthroughs. Ask yourself—does today India even have 10 high-caliber AI teams in industry that can build FAIM-level systems or contribute to top 1% foundational AI research? If not, how do we expect to be part of the AGI journey?
And if we are assuming that the U.S. or China will achieve AGI handover to India, maybe as open source, then it is a fantasy. Innovation doesn't flow downstream unless you're in the game. Without hands-on experience and real capabilities, we'll be reduced to using whatever tools others give us—at best. That's not sovereignty, that's dependency.
History has shown us the cost of this approach. In 1993, the U.S. blocked Russia from transferring cryogenic engine tech to India. It almost crippled our space program. But Indian scientists doubled down, and today, we have a thriving space ecosystem & best in class talent pool. If back then we had merely focused on 'space applications', we would never have produced the "Rocket Women of India" who led the Chandrayaan-3 landing on the Moon's south pole. Similarly, had we limited ourselves to 'nuclear applications' and a visionary like Dr Homi Bhabha had not taken a stand to develop India's indigenous nuclear capability, India would have never nurtured a world-class atomic talent pool capable of handling both fusion & fission technology.
AI is no different—arguably more important.
This is not to say we pour all resources into building FAIM from scratch. It's expensive, high-risk, and not for every player. 99.9% of startups and enterprises should focus on the application layer. That's where a large and an immediate opportunity lies—and profits made there can fund the broader AI ecosystem.
But 0.1% of our capacity—just 20-30 serious, mission-driven industrial teams—must pursue FAIM and foundational research. The hope is that some of these teams will secure India's place at the AI table and push the boundaries toward AGI.
Crucially, this can't be left to academia or government alone. They have their constraints. The private sector must lead. If we had Indian equivalents of Lockheed Martin or Boeing, we wouldn't rely solely on HAL for the Tejas fighter jet. In the U.S., AI breakthroughs came not just from universities or government agencies, but from corporate labs—OpenAI, DeepMind, Anthropic, FAIR. When NASA couldn't bring Sunita Williams back, SpaceX did.
How long will Indian corporations chase only low-hanging fruit while shying away from real R&D? As honorable Minister Piyush Goyal recently said—how long will we make fancy ice creams instead of computer chips?
The buck can't be just passed on to startups alone. They have 110 challenges to fight. Answers can come from every cash-rich Indian IT/software/product company above a certain revenue must invest $10–20 million in foundational AI research—
fund at least one FAIM team internally
. This isn't about leaderboard rankings. It's about building core capability that can solve India's & humanity's hardest challenges: predicting pandemics, natural disasters, discovering drugs, understanding demographic shifts, or preventing financial crises; fulfilling the honorable Prime Minister's vision of India becoming a vishwa guru.
We need R&D that pushes FAIM forward—models that can be localized for Indian contexts to solve problems in farming, fishing, or education. This sends a clear message to global Indian talent: that corporate India, not just startups, means business—come build with us.
The returns? Strategic AI independence. Long-term economic windfalls. Deep tech job creation. Sovereignty over critical infrastructure. And a shot at real leadership in the AI century.
The AI race is on. Will India be just another application builder—or will it also rise to light the path toward AGI?
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