India’s AI Moment: Market, Lab, or Builder?

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India’s AI Moment: Market, Lab, or Builder?

For decades after independence, India told itself a modest story about technology. Big, transformative technologies were not for us. What we needed instead was appropriate technology — small, local, targeted. Machines designed to solve immediate problems rather than reshape society. The state promoted specific fixes over sweeping revolutions.

Fast forward to today, and the contrast could not be sharper. The world is in the middle of an AI arms race. And OpenAI, arguably the most influential player of them all, has just rolled out its cheapest subscription anywhere in the world. Not in the US, not in Europe, but in India.

₹399 ($4.80) a month. That’s the price of ChatGPT Go, launched on 19th August.

It is a price that makes no sense if you think in terms of costs. Running these models requires the same GPUs, the same electricity, the same data centers whether the user is in Bangalore or Boston. Computation does not magically get cheaper in India.

So why should Indians pay less?

Because India is once again the testing ground — the laboratory. A place where millions of students, freelancers, and small businesses can stress test tools, feed them data, and more importantly, form habits around them. And this raises the bigger question: If India becomes, yet again, the market that supplies global tech giants with users and usage data, then what happens to Indian AI startups?

Déjà Vu from the Internet Era

The script feels familiar. When the internet and social media exploded globally, India became the fastest-growing market. Meta, Google, YouTube built enormous user bases here. But India never built its own equivalents. No Indian Facebook, no Indian Google.

The reasons were structural. Scale, data, and capital tilted the game in favor of global giants. And now, those same dynamics are playing out in the AI race.

Take OpenAI’s ₹399 ($4.80) plan. Or Perplexity, which is literally free if you are an Airtel subscriber. These aren’t designed to maximize revenue — they’re designed to maximize usage. Win habits now, monetize later.

For global AI companies, India is a goldmine: nearly a billion internet users, a young, English-speaking base, millions of professionals hungry for productivity tools. Every prompt, every correction, every follow-up query becomes training data. And that data widens the gap between incumbents and everyone else.

For Indian startups, this is not just a competition on features. They are up against a feedback loop of global scale, better models, and effectively unlimited capital.

The Brutal Arithmetic

Sam Altman has put it bluntly: it’s “totally hopeless” to compete with OpenAI on foundation models. The economics back him up.

OpenAI has raised nearly $18 billion. Meta reportedly spent $170 million to train its largest Llama model.

Now look at India. Krutrim, Ola founder Bhavish Aggarwal’s AI venture, raised $50 million to reach unicorn status. Sarvam AI, the most ambitious local foundation model attempt, is still a baby by global standards. Most other Indian players build on top of open-source models like Llama or Mistral rather than attempting to train from scratch.

The hurdles are threefold:

• No firewall. Unlike China, where Baidu and iFlytek thrived behind the Great Firewall, India gives free rein to ChatGPT, Perplexity, Gemini, and more.

• Compute costs. Nvidia GPUs cost the same everywhere; there’s no India discount.

• Capital gap. Building big AI takes billions. Indian VCs don’t write checks that size, and state backing is still limited.

The result? India risks becoming the global lab again — abundant usage, but with technology ownership residing elsewhere.

The Local Counterweights

That’s not to say nothing is happening in India.

Sarvam AI, founded by ex-Microsoft researchers and backed by Nandan Nilekani, is building multilingual Indic-first models. Its products span text, voice, agents, and even legal-domain workbenches. Yet, despite heavyweight partners like Microsoft and Nvidia, capital is finite, and some models rely heavily on synthetic training data, raising performance concerns.

Krutrim, Bhavish Aggarwal’s bet after Ola, pitches itself as India’s first multilingual LLM. Still in early days, but with money raised and momentum building.

Then there are niche players: Kisan AI, which builds tools for farmers; Corover, which launched BharatGPT for Indian linguistic nuances. Each tackles narrow but important Indian problems. All run into the same choke points: scarce capital, scarce data, and expensive GPUs.

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The Government Steps In

Earlier this year, IT Minister Ashwini Vaishnaw announced the IndiaAI Mission, a ₹10,000 crore ($1.2 billion) program to build domestic AI capacity. Ten companies from iOta to Jio to Tata Communications will supply nearly 19,000 GPUs, pooled as public infrastructure so startups don’t have to buy them outright.

That’s significant. Compute is the oxygen of AI. Without GPUs, you can’t train or scale. The government also promises grants, procurement support, and partnerships — framing AI not just as a commercial asset but as a strategic resource, as important as telecom or energy.

But is it enough?

Where Startups Can Win

Indian AI startups cannot outspend OpenAI. But they can carve moats in three areas:

1. Localization. India’s messy diversity — languages, dialects, regulations — is hard for global players to prioritize. Startups that tune AI to these realities can stand out.

2. Vertical AI. Specialized tools for kirana logistics, agri-supply chains, compliance, or education. OpenAI will not optimize for a small-town accountant or a sugarcane farmer. A local startup can.

3. Integration. Embedding AI into workflows of SMEs, schools, or government services. In India, trust and relationships often matter more than raw model quality.

The risk is clear: fail to build these moats, and Indian startups will end up as resellers or distributors for global giants — as they did in the internet era.

The Big Question

India’s AI startups do have a shot. But not at becoming “the OpenAI of India.” That playbook is closed. Their chance lies in becoming indispensable locally, even as the giants fight globally.

Otherwise, history will repeat itself. India will once again be the world’s favorite user base. Millions of prompts, billions of interactions — but the real value capture, the capital, the intellectual property, the influence — will flow elsewhere.

So the question hanging over India’s AI moment is this: Will we settle for being the market, or will we build — even if we build differently?

Interested in learning more about AI? Check out our previous coverage here:

• From Hype to How: 5 Lessons from the 2025 State of AI Report

• Reflections on OpenAI

• The Acceleration Era: AI After 2022 and What It Means for Builders

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Peeyush and Mohit

Disclaimer: The views, thoughts, and opinions expressed in the text belong solely to the author, and not necessarily to the author's employer, organization, committee or other group or individual.