The Use-Case Capital, Still At the summit, Amodei made an audacious claim. If deployed effectively, AI could help India achieve economic growth rates of 20-25%. He acknowledged how absurd that number sounds. India has only briefly touched growth in the mid-20s—and that was after the pandemic, largely due to a low-base effect. Still, he paints a "very bullish picture" of the possibility of such growth. The core idea was diffusion. Frontier models are improving exponentially in software engineering, mathematics and early biomedical reasoning. But even if model development stopped today, most of the economic upside would remain unrealised because adoption always lags invention. Nilekani agreed. Building foundation models is one challenge. Spreading them across millions of users, institutions, and small businesses is another entirely. Drawing from India's digital public infrastructure experience, he argued diffusion is both art and science. It requires policy support, institutional trust, regulatory guardrails and careful negotiation with incumbents. This, Nilekani has always believed, is where India has an edge. Through platforms such as digital identity and real-time payments, the country has already demonstrated the ability to scale technology to the population level. For years, Nilekani has said that India should aim to become the "use case capital" of the world. At the summit, he doubled down. To prevent resentments around job losses and workers, or disappointment if AI fails to deliver the value, the focus, in his view, should be on large-scale, tangible outcomes. Farmers must earn more, children must learn better, and citizens must access healthcare and public services in their own languages. AI must move beyond elite labs and corporate pilot programmes. To push that vision, Nilekani announced a '100 Diffusion Pathways by 2030' initiative, a coalition that includes EkStep Foundation, United Nations Development Programme, People+ai, Anthropic, Google and the Gates Foundation. The goal is to build playbooks that combine technical design with regulatory and institutional lessons. "Right now in AI, there's a race to the top and a race to the bottom," he said. "And the race to the bottom is faster than the race to the top." India has the scale to be both the leader and the use-case capital of the world. But how it manages the accompanying shift in jobs may ultimately determine whether that ambition succeeds. |
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