OpenAI, Google, and Anthropic Are All Betting on India in 2026 — Here is What That Means

## Three Companies, One Week, One Country

In the span of five days at the India AI Impact Summit 2026 in New Delhi, something unusual happened. OpenAI, Google, and Anthropic — the three most important AI companies in the world right now — all made major India announcements simultaneously. Not one, not two. All three.

This is not a coincidence. It is a calculated bet. Understanding why they are all moving at the same time tells you something important about where AI is headed — and what it means if you are building or working in tech in India.

## OpenAI's India Move

Sam Altman came to New Delhi personally and met PM Modi in a bilateral meeting on the sidelines of the summit. The announcements:

**OpenAI + Tata Group: 100 MW AI infrastructure.** Branded HyperVault, green energy powered, with plans to scale to 1 GW. This is not a pilot. 1 GW of AI compute is a serious infrastructure commitment — the kind you make when you believe a market is going to be one of your largest.

**Two new India offices.** OpenAI is not treating India as a remote sales territory. Offices mean engineering, product, and research teams building locally.

**TCS partnership.** Tata Consultancy Services has 600,000 employees. Integrating OpenAI tools into TCS's enterprise operations means those tools reach hundreds of the world's largest corporations that TCS services.

**India is OpenAI's fastest-growing Codex market.** Altman said this directly. Indian developers are adopting AI coding tools faster than any other market. OpenAI is following its users.

## Google's $15 Billion Commitment

Sundar Pichai announced that Google is establishing a full-stack AI hub in India as part of a $15 billion infrastructure investment. Full-stack here means not just data centres — research, engineering, product development, and training infrastructure all locating in India.

Google has been in India for two decades. What is different now is the level. A $15 billion commitment signals that India is no longer a support and services location for Google. It is becoming a primary location for building things.

## Anthropic + Infosys, New Bangalore Office

Dario Amodei's Anthropic — arguably the most technically serious AI safety company operating today — announced a partnership with Infosys and opened a new office in Bangalore.

Anthropic choosing Bangalore specifically matters. Bangalore is India's engineering capital. This is not a sales office. It is a technical presence. Infosys, like TCS, gives Anthropic reach into enterprise customers across dozens of countries through a single partnership.

## Why All Three, Why Now

Three forces are converging simultaneously:

**Market size.** India has 1.4 billion people, 65% under 35, the world's largest English-speaking developer community outside the US, and one of the fastest-growing smartphone user bases. OpenAI's fastest-growing Codex market is not the UK or Germany. It is India.

**Compute economics.** With Reliance pledging gigawatt-scale sovereign compute and Adani investing in AI infrastructure, India is building the data centre capacity that AI companies need to serve their Indian users locally. Lower latency, better cost, regulatory alignment.

**Geopolitical positioning.** India is the largest democracy, a member of the Quad, and increasingly the swing vote in global AI governance debates. Having deep infrastructure and partnership ties in India gives Western AI companies a genuine stake in how India's AI policy develops. That is worth billions in itself.

**China competition.** Huawei, Alibaba, Baidu, and DeepSeek are actively courting Indian developers and enterprises. If OpenAI and Google do not establish deep roots now, they cede that ground. The India market is competitive in a way it was not three years ago.

## What the Infrastructure Numbers Actually Mean

Reliance/Jio: 120 MW of sovereign compute online by H2 2026, scaling to gigawatt capacity.
Adani: Major AI data centre investment.
Tata/OpenAI HyperVault: 100 MW, scaling to 1 GW.
Google: $15 billion over several years.

India is going from AI compute scarcity to AI compute abundance within 24 months. The cost of running models, training fine-tuned versions, and building AI-native products in India is about to drop significantly.

For a developer or startup building something AI-native in India today, this is the infrastructure tailwind arriving. The question is what you build while it is arriving.

## What This Means If You Are an Indian Developer

**Job market:** Every company that announced India operations needs engineers. Not outsourced support engineers — AI engineers, product engineers, infrastructure engineers. The demand is real, arriving fast, and pays at rates that have historically required relocating abroad.

**Startup opportunities:** With local compute coming, the economics of training and deploying models in India improve dramatically. Products that were too expensive to build locally become viable. The next wave of Indian AI startups will be able to build with fundamentally different cost structures than those that came before.

**Learning window:** The AI tools available to Indian developers today — Codex, Claude, Gemini — are the same tools available to developers in San Francisco. The gap is not access. It is velocity of adoption. The developers who build the most with these tools fastest will be disproportionately well-positioned.

**Enterprise integration:** TCS, Infosys, and Wipro are all now deep partners with the top AI companies. The work of integrating AI into India's largest enterprise clients is going to flow through Indian engineers. That is a significant volume of high-value technical work.

## The Honest Caveat

None of this automatically translates to benefit for Indian developers or Indian society. Big announcements at summits are not the same as distributed prosperity.

The risk is that $210 billion in infrastructure investment creates a compute layer that primarily services Western AI companies' India operations, rather than enabling Indian-built AI products at scale. The talent pipeline, the IP ownership, and the product layer all matter more than the data centre layer.

India has been good at building software for others. The question this summit raised — but did not answer — is whether this moment is different. Whether Indian developers will build the next wave of AI products, or be very well-paid to build them for someone else.

Both outcomes represent progress. Only one represents the shift that everyone in that room in New Delhi was implicitly hoping for.

The infrastructure is coming. What gets built on top of it is still an open question.