A New AI Power Map? India Challenges U.S.–China Dominance at Davos

DAVOS, Switzerland — India pushed back this week against claims it trails the United States and China in artificial intelligence, insisting it already operates in the “first group” of global AI powers with its own independent strategy, talent base and technology stack.

India’s IT and Railways Minister Ashwini Vaishnaw challenged the common U.S.–China “top tier vs second tier” framing. He cited Stanford rankings placing India third in AI penetration and preparedness and second in AI talent.

Vaishnaw said India is advancing across five layers of the AI stack — application, model, chip, infrastructure and energy — and will become a major exporter of AI-enabled enterprise services.

He argued that return on investment will shape AI leadership, not the size of frontier models. Mid-sized models of 20–50 billion parameters, he said, can deliver 95% of real enterprise value on cheaper hardware, accelerating AI diffusion.

Pressed on geopolitics, Vaishnaw rejected the idea India must align with Washington or Beijing. He said the future of AI power will be multipolar and ROI-driven, enabled by custom silicon, CPUs and lower-cost compute rather than a single mega-model or GPU monopoly.

India Challenges the U.S.–China AI Paradigm

Five years ago, AI barely registered in Davos debates. This year, it dominated — as a technology frontier, economic engine and geopolitical lever.

A moderator framed the conventional wisdom clearly: the U.S. and China sit in the top tier, while countries like India operate in a “second grouping,” forced to choose sides.

India dismissed that framing.

Vaishnaw said Stanford data supports India’s first-tier classification and credited progress across the five-layer architecture for positioning India as a services-led AI supplier to the world.

ROI vs Frontier: A Different AI Thesis

While Silicon Valley and Beijing chase giant frontier models and high-cost compute, India is betting the next phase of AI will be defined by ROI, deployment and productivity, not model size.

India is already building a “bouquet” of mid-sized models and distributing them across multiple sectors to lift efficiency and output — a contrast to the GPU-intensive hyperscale race.

Enterprise Implications for India’s Tech Sector

For India’s enterprise and startup ecosystem, the Davos argument has practical implications. If global AI advantage shifts from mega-models to deployment economics, India’s strength in IT services, process understanding and domain-specific problem solving becomes a competitive asset. Under that scenario, SaaS founders, enterprise tech players and export-facing digital companies could convert AI into productivity gains faster and more efficiently than capital-heavy competitors.

Geopolitics Without Choosing Sides

Asked how India navigates the U.S.–China rivalry, Vaishnaw rejected the premise that large models translate into coercive power.

“We have our own bouquet of models,” he said. “So does creating a large model give you geopolitical power? I don’t think so.”

He warned that the capital burn behind frontier models could push some players toward economic overreach or bankruptcy.

The shift toward what he called the “fifth industrial revolution” favors diffusion, affordability and enterprise integration — areas where India sees competitive advantage.

India as a Third Pole in a Multipolar Tech Order

Beyond economics, the Davos exchange underscored a broader strategic shift. Rather than choosing between Washington and Beijing in the AI race, India is positioning itself as a third pole: a country capable of building its own stack, setting its own ROI logic and exporting its own AI-enabled services. That multipolar approach aligns with India’s geopolitical rise over the last decade and its ambition to shape the next phase of the digital economy.

The ROI Era of Global AI

The Davos debate reflected a deeper transition. If 2020–2023 was the era of frontier models, GPUs and capital burn, the 2024–2028 period may be defined by:

• ROI over R&D burn
• enterprise deployment over demos
• services over scale
• diffusion over dominance
• multipolar AI over binary blocs

Those dynamics favor countries with talent depth, IT services capacity and enterprise penetration — categories where India already ranks high.

Whether India becomes a full AI superpower is still open, but at Davos, it sent a clear signal: it refuses to be classified as second-tier.