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

India is positioned as a lagging player in the global AI trade. Investors are directing capital to chips, computational power, and infrastructure—where American and Chinese corporations dominate. Ruchir Sharma, Chairman of Rockefeller International, explains: this position threatens one of India's main advantages.

R&D Deficit

The first deficit is spending on R&D. India spends significantly less on fundamental AI research than its competitors. This creates dependency: the country does not generate its own breakthrough models but imports technology. While OpenAI launches new versions of GPT, ByteDance deploys local solutions, and Anthropic bets on long context, India plays the role of a consumer, not an architect. This slows down the local startup ecosystem. Small companies in India cannot compete in the global race because they lack access to computational resources and funding that competitors in the US or Europe receive.

Threat to 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 capture routine coding
• BPO operations (data processing, customer service) are next in line for AI automation
• Major Indian companies (TCS, Infosys, Wipro) see pressure on margins and contract volumes
• IT services contribute 10% to India's foreign currency exports; losing here means losing for the macroeconomy

The scale of the problem: millions of Indian IT professionals work for the global market. Automation of a chunk of this market moves jobs outside India or eliminates them entirely.

"India risks losing its advantage at the moment when the entire world is transitioning to AI," —

Sharma's logic.

Potential for Recovery Later

However, complete pessimism is unjustified. Ruchir Sharma notes several reasons for optimism. First, India's nominal GDP grows at 7–8% annually—faster than in developed countries. This provides buffering capacity to reinvest and recover. Second, valuation reset. If Indian stocks trade at a discount today amid AI panic, a sharp revaluation could come tomorrow when the narrative changes. Third, when AI transitions from a race for models to practical application in productivity—automation of business processes, customer intelligence, supply chain optimization—India can retrain. Instead of developing models, India becomes an integrator and optimizer of AI for developing markets in Africa, Southeast Asia, and Latin America.

What This Means

In the short term (1–2 years), India is in an unfortunate position: losing export advantage in code, not creating its own AI champions, investors turning capital away. But in the medium term (3–5 years), the game could turn. GDP growth + vast engineering reserve + shift in demand toward productivity applications = opportunity to return to the game. For investors, this means: revaluation ahead, but patience is required.