India’s vast data is a strategic asset, not a free export to Silicon Valley. To become an AI superpower, the country needs to invest in talent and compute, and also use its data for AI development in the country. This approach can democratize AI, create local jobs and prevent foreign tech dominance, thereby ensuring that the value remains in India.
India is rapidly becoming one of the largest AI user bases in the world. Now the question is, how can it give superpower status on this scale instead of giving free training to Silicon Valley? This will be a difficult task for a country that has been largely affected by the boom. But let’s start with the basics: The three main building blocks of AI are talent, compute (which includes high-end chips and infrastructure), and data.
There is no dearth of engineers in India, but there is currently no large-scale basic research training or enough advanced processors in public labs and universities. What India has in abundance is data. India should start using it as a strategic asset and not leak it as a free export.
This is a special reason why big US tech companies are rapidly coming into the market. With nearly a billion people online and a huge, mobile-first population, India deals with tons of daily messages, voice notes, digital payments, and increasingly the kind of human feedback that makes AI systems better.
The world’s most populous country has the second-largest user base of both OpenAI’s ChatGPT and Anthropic PBC’s Claude after the US, despite accounting for only a small portion of these platforms’ revenue. This dynamic shows that right now the market for training purposes is more important than earning money.
There is a price for this free service and promotion being showered on Indian customers. This is a strategic attempt to grab the land of Silicon Valley for Indian languages, voices and behavior, which will first make foreign systems smarter.
India’s linguistic diversity also matters; there are more than 20 official languages in the country and dozens that are unofficial. If models are not adequately trained on local slang and cultural context, they will misunderstand users and will not be credible in classrooms, clinics, courts, and even customer support settings. Bridging this language gap is a key part of Prime Minister Narendra Modi’s promise to democratize AI and make its impact real to everyone, not just the English-speaking elite, from farmers to small business owners.
Also, companies like Meta Platforms Inc. or OpenAI that are selling an AI future that includes personal agents and voice powered ambient devices. He will not work in India unless he can hear and speak the local languages and understand the nuances properly.
Some startups, including Andreessen Horowitz-backed Poseidon AI and non-profit efforts backed by Big Tech, are already trying to crowdsource and create local language datasets. India cannot demand AI for all while outsourcing the work of building the language foundation. However, if done right, these datasets can become the infrastructure for its AI economy.
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