India and the Global AI Race: Is the Loser Verdict Missing the Bigger Picture?

Published: May 2026

Ruchir Sharma's assessment at the Indian Express Adda on 2 May 2026 has been widely circulated: most foreign investors view India as a loser in the AI race. He described India as an "anti-AI play" in the eyes of global capital: a market that sat out the defining technological shift of this decade while the US, Korea, and Taiwan built their positions. The FPI data lends weight to the concern. Foreign investors have withdrawn more than Rs 1.8 lakh crore from Indian equities in 2026, already exceeding the record annual outflow of 2025.

The verdict of "absent," however, deserves closer examination. India is not building foundational AI models or designing chips. What it is doing is structurally different, and more consistent with how India has always entered technology cycles than most coverage of this debate acknowledges.

India's AI Footprint: Key Numbers at a Glance

Where the "Anti-AI" Concern Has Merit

The foreign investor case is not without foundation, and it is worth stating clearly before addressing the counter-argument.

India has no counterpart to OpenAI, Anthropic, or Google DeepMind in the foundational model layer. It has no AI chip designer comparable to NVIDIA, and no advanced semiconductor foundry comparable to TSMC. The two roles are distinct: NVIDIA designs chips, TSMC manufactures them for the world. India is absent from both. It has no agentic coding platforms in the league of Cursor, Windsurf, or Cognition. These are the layers where global AI valuation is currently concentrated. India is absent from all of them.

India's R&D spending as a percentage of GDP also remains well below the US, China, Korea, and Taiwan. Without sustained public and private investment in foundational research, India's position in the AI stack will remain downstream of where the highest-value work happens.

What India Actually Contributes to Global AI

India's AI participation is not at the foundational layer. It is at three other layers that are essential to making global AI work in practice, and each is growing at measurable scale.

The Structural Argument: India Has Done This Before

India did not build the hardware, chips, or operating systems of the 1990s technology cycle. It arrived after those foundational layers were established and dominated the services layer, combining skilled manpower with cost efficiency to become the world's largest IT services hub. That transition took a decade to become visible and two decades to become undeniable.

The AI cycle is following a structurally similar pattern. The foundational model and chip layers are being built in the US, with contributions from Korea and Taiwan. India is not in those layers. But the services layer (enterprise AI deployment, domain-specific model fine-tuning, AI systems integration, and data centre operations) is the next phase of the AI value chain. That is where India is positioning, and the data suggests the positioning is already underway at scale.

The difference this cycle is that India is not starting from near-zero infrastructure. The GCC ecosystem, the talent base, the data centre investment, and the IT services AI pivot are all happening simultaneously. That convergence is what most FPI sentiment analysis is not fully capturing.

What This Means for Indian IT Stocks and FPI Sentiment

The FPI narrative around India and AI is partially valid and partially incomplete. The valid part: India has no foundational AI champions, R&D investment is insufficient, and Indian IT companies face genuine disruption risk to legacy services revenue from AI automation.

The incomplete part: the services and infrastructure layers that India is building are not peripheral to the global AI economy. They are where the majority of AI implementation will happen as enterprises move from experimentation to deployment at scale. The companies best positioned to capture this opportunity are the same ones that captured the 1990s enterprise IT services wave.

For context on the FPI selling pattern that has accompanied this debate, see Finnovate's detailed analysis: FPI Outflows: What the Data Shows and the cross-asset return context in Passive Fund Flows and India's Equity Positioning.

Key Takeaways

• Ruchir Sharma's "anti-AI play" characterisation reflects genuine foreign investor sentiment. India is absent from foundational model, chip, and agentic coding layers where global AI valuations are concentrated.
• TCS reported annualised AI revenue of $2.3 billion in Q4 FY26, with 1,833 AI-led patents filed. The IT services AI pivot is already generating measurable revenue, not just strategy announcements.
• India hosts 1,800-plus GCCs employing approximately 2 million professionals, with 80% of new GCCs prioritising AI and ML, placing India at the centre of global enterprise AI fine-tuning and implementation.
• Microsoft has committed $17.5 billion over CY2026-2029 for cloud and AI infrastructure in India. Google has pledged around $15 billion for its Visakhapatnam AI hub. Amazon has announced over $35 billion across India businesses by 2030, with AI and cloud as primary stated goals. Reliance has added $11 billion for a 1 GW data centre.
• India's AI entry mirrors its 1990s IT services entry. Not at the foundational layer, but at the implementation and services layer that scales once foundational infrastructure is established globally.
• The FPI concern about legacy IT disruption is valid. Whether it is fully pricing in India's growing services and infrastructure AI position is the investment question that remains open.

FAQs

1. Has India lost the AI race?

India is absent from foundational AI layers (large language model development, chip design, and advanced semiconductor foundries) where current AI valuations are concentrated. However, India is building positions in enterprise AI services (TCS: $2.3 billion annualised AI revenue in Q4 FY26), AI fine-tuning through 1,800-plus Global Capability Centres, and AI data centre infrastructure, where Microsoft, Google, Amazon, and Reliance have each announced major India investment commitments. Whether that constitutes losing depends on which layer of the AI economy generates the most durable long-term value.

2. Why are FPIs selling Indian equities and how is AI connected?

Foreign investors have withdrawn more than Rs 1.8 lakh crore from Indian equities in 2026. The AI connection is twofold: India's absence from foundational AI layers makes it a less compelling AI-era investment story versus the US, Korea, and Taiwan; and India's IT sector faces genuine disruption risk from AI automation reducing demand for traditional software services. For detailed FPI flow analysis, see FPI Outflows: What the Data Shows.

3. What is a GCC and what does it have to do with AI?

A Global Capability Centre (GCC) is a wholly-owned offshore unit set up by a multinational company in India to run strategic business functions globally. India hosts over 1,800 GCCs employing approximately 2 million professionals. These have evolved from cost-arbitrage centres into AI implementation hubs. Now 80% of new GCCs now prioritise AI and machine learning, handling enterprise-level model fine-tuning, domain-specific AI application development, and AI validation work for Fortune 500 companies.

4. Should investors be concerned about Indian IT stocks because of AI?

Indian IT companies face real disruption risk to legacy services revenue from AI automation. This is a genuine structural concern, not a temporary headwind. At the same time, TCS's $2.3 billion in annualised AI revenue signals the pivot toward enterprise AI services is underway. The medium-term uncertainty is genuine, and the transition timeline remains unclear. Please consult a SEBI-registered investment adviser before making any decisions related to IT sector investments.

5. Why are global tech companies investing so heavily in India's AI infrastructure?

Microsoft has committed $17.5 billion over CY2026-2029 for cloud and AI infrastructure in India, building on an earlier $3 billion commitment. Google has pledged around $15 billion over 2026-2030 for its Visakhapatnam AI hub. Amazon has announced over $35 billion across India businesses by 2030, with AI-driven digitisation and cloud as primary stated goals alongside logistics, exports, and jobs. India offers lower data centre construction and operating costs versus comparable locations, high-quality bandwidth, geopolitical stability, and a large domestic AI consumption market that is growing rapidly.

Disclaimer: This article is for general information and educational purposes only. It does not constitute investment advice, a recommendation, or an offer to buy or sell any securities or financial instruments. Company-level data (TCS AI revenue, patent filings) is sourced from TCS's own investor communications. GCC data is sourced from Zinnov, Nasscom, and Flexiple industry reports. FPI data is sourced from NSDL and media reports. Investment commitment data for AI data centres is sourced from company announcements and Bloomberg. Past performance and historical analogies are not indicative of future outcomes. Please consult a SEBI-registered investment adviser before making any investment decisions.