India is positioned to become the world's "AI use case capital" by deploying applied artificial intelligence at population scale, according to Infosys co-founder and chairman Nandan Nilekani — a shift that could make the country a principal beneficiary of AI productivity gains and inclusion over the next decade.
Speaking at the India Policy Forum in New Delhi, Nilekani said India may emerge as the principal beneficiary of productivity gains and inclusion from AI in the next decade, according to TNN. He acknowledged that India has low visibility in three parts of the AI stack: chips, infrastructure and large language models (LLMs) — the AI systems that generate human-like text. The opportunity, he argued, lies in applied AI.
"It's in the area of applied AI, that India will become a leader. We will become the AI use case capital of the world because we will actually deploy AI and make it useful, not just for a few businesses or a few people, but make it accessible and useful to a billion Indians," he said at the event, as reported by TNN.
He compared the push to India's experience with digital public infrastructure (DPI), the shared digital systems India has built at scale. "Applying AI to change the lives of Indians and population scale, just like we did with DPI, is really where it's going to go," he said.
The jobs outlook: large companies are most exposed
Nilekani, who also chairs think tank NCAER, cautioned about AI's impact on jobs, singling out large companies as the most vulnerable. "In some sense, the future will be small businesses, because in terms of job creation, because large companies, which are very well structured, will actually be the most vulnerable to job losses, because they're so well structured that every job is reduced to a few set of tasks. It's also easy to automate that and remove jobs. So large companies will probably be net job losers in the coming years," he said, according to TNN.
Small businesses, many of them single-person companies, are better placed in an AI-driven economy, he added.
| Factor | Large companies | Small companies |
|---|---|---|
| Structure | Highly structured, with every job reduced to a few tasks | Small, many are single-person companies |
| Automation exposure | High — tasks are easy to isolate and automate | Lower — work is not broken into easily automated task sets |
| Job creation outlook | Likely net job losers in the coming years | The future of job creation, according to Nilekani |
Instead of expecting a few companies to hire a million people, the economy will grow because a million companies have one person each. — Nandan Nilekani, as reported by TNN
What this means for technology leaders
For enterprise technology decision-makers, Nilekani's remarks define two axes of change. First, India's AI advantage will come from applying AI to real-world problems at population scale — not from building chips, infrastructure or large language models, where visibility is low, according to the TNN report. Second, the structure of job creation is expected to shift away from large, well-structured organisations toward small and single-person businesses.
For CTOs and enterprise software buyers, the implication is that applied AI tools must be designed for deployment across many small operations, not just a few large enterprises. Nilekani said India will deploy AI to make it "accessible and useful to a billion Indians," the same way the country scaled digital public infrastructure. Large companies, meanwhile, face the prospect of being net job losers as structured tasks become automated, according to Nilekani. The coming decade, in his assessment, belongs to the country that turns AI into use cases — and to the small businesses that deploy it.
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