The recent AI Summit in New Delhi brought together a wonderful community of global tech leaders who strongly proposed that India can be an AI powerhouse. AI pioneers talked about LLM models, investors spoke about trillion-dollar opportunities, while policymakers stressed strategic autonomy. Now that the dust has settled, a key question is whether Indian AI startups can convert promise into reality? To be fair, there are several promising startups that are using AI as their core IP instead of mere bolt-ons.
Sarvam AI and Krutrim are building multilingual foundation models tailored for India’s diversity. Neysa is pushing generative AI into enterprise content automation and business intelligence. In healthcare, Qure.ai accelerates diagnostic interpretation with AI, while Gnani.ai tackles speech recognition for Indian languages, CoRover focuses on conversational AI for enterprise outreach, and Fractal is using AI to generate analytics for retail and consumer packaged goods.
The ecosystem is also gaining capital momentum. According to the India Deep Tech Alliance report, AI startups captured $1.2 billion across 188 deals in 2025, a 58 per cent year-on-year jump. India’s AI market was valued at roughly $9.5 billion in 2024 and projected to surpass $130 billion by 2032. Other projections say AI could add up to $1.7 trillion to India’s GDP by 2035.
Government support is visible. The IndiaAI Mission has allocated over ₹10,300 crore over five years and provided tens of thousands of GPUs to broaden access. State and Central government policies are experimenting with infrastructure funding, data initiatives, and incentive schemes to spur AI research and startups.
But we must remain cautious. Computing remains expensive, while India lags in chip manufacturing and domestic GPU capacity. The government has announced semiconductor projects and we should see strong progress over the next few years. High-quality labelled data across Indian languages is severely limited. Indian talent in AI is exceptional but is globally mobile. Early-stage investors are unsure if they should back capital-intensive foundational platforms or application layers.
We are unlikely to outspend the US or China on foundational AI research. But we can execute strongly in applied, multilingual, high-volume contexts that global players still struggle to serve. The real AI summit lies ahead as we climb from prototype to production, from optimism to operating leverage. AI offers India an opportunity to ramp up from back-end service providers to technology innovators.
(The writer is a serial entrepreneur and best-selling author of the book ‘Failing to Succeed’; posts on X @vaitheek)
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Published on March 2, 2026
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