Why India Is Falling Behind in the Global AI Race: Ruchir Sharma's View

India is positioned as the losing side of the global AI trade. Investors are pouring capital into chips, computing power and infrastructure, areas dominated by American and Chinese corporations. Ruchir Sharma, chairman of Rockefeller International, explains that this position threatens one of India's main advantages.

A shortfall in homegrown research

The first gap is R&D spending. India spends significantly less on fundamental AI research than its competitors. That creates dependence: the country does not generate its own breakthrough models but imports technology. While OpenAI launches new GPT versions, ByteDance rolls out local solutions and Anthropic bets on long context, India plays the role of consumer, not architect.

This slows the local startup ecosystem. Small companies in India cannot compete in the global race because they lack access to the compute and funding that their rivals in the US or Europe get.

A threat to the IT sector and outsourcing

The second problem is more acute: AI threatens India's main export engine, software development and Business Process Outsourcing (BPO).

• Junior developers are already facing replacement: Copilot and Claude are taking over routine coding
• BPO operations (data processing, customer service) are next in line for AI automation
• Large Indian companies (TCS, Infosys, Wipro) are seeing pressure on margins and contract volumes
• IT services contribute 10% of India's foreign-currency exports; a loss here is a loss for the macroeconomy

The scale of the problem: millions of Indian IT professionals work for the global market. Automating a slice of that market moves jobs outside India or eliminates them altogether.

"India risks losing its advantage just as the whole world moves to AI," is

Sharma's reasoning.

The potential for a later recovery

Still, full pessimism is not warranted. Ruchir Sharma cites several reasons for optimism.

First, India's nominal GDP is growing 7–8% a year, faster than in developed countries. That gives it a buffer to reinvest and recover.

Second, a valuation reset. If Indian stocks trade at a discount today amid AI panic, a repricing could be sharp tomorrow, once the story changes.

Third, as AI moves from the race for models to practical productivity applications (business process automation, customer intelligence, supply chain optimization), India can retool itself. Instead of building models, India becomes an integrator and optimizer of AI for emerging markets in Africa, Southeast Asia and Latin America.

What this means

In the short term (1–2 years), India is in an unfavorable position: it is losing its export advantage in code, is not creating its own AI champions, and investors are pulling back capital. But over the medium term (3–5 years), the game could turn. GDP growth + a large engineering talent pool + demand shifting toward productivity applications = a chance to get back in the game.

For investors, this means a repricing lies ahead, but it requires patience.