The way forward for India in the AI race

The scale of the gap between India and the world’s leading AI ecosystems came into sharp focus last week when Anthropic, one of the leading large language model (LLM) startups, announced a $65 billion funding round that valued the company at $965 billion. Its chief rival, OpenAI, has raised about $180 billion in funding to date.

To put this into perspective, the Indian startup ecosystem raised a total of $64.2 billion in funding between 2022 till May 2026 as per YourStory Research. The combined capital raised by Anthropic and OpenAI alone is several times larger than the amount raised by the entire Indian startup ecosystem over the past few years. These figures also raise questions about the state of AI innovation in India. Beyond Sarvam AI, there are very few AI companies that enjoy this recognition.

The reasons are manifold, including lack of risk capital, limited governmental support, and shortage of talent.

AI has made one thing clear: building frontier models requires enormous amounts of capital. Such investments are considered risky in India as one is not very sure of what would be the returns. The billions of dollars required to build data centres can be overwhelming for many investors.

Estimates suggest that between 2026 and 2031, the data centre market in the US could attract $839 billion in cumulative investments. Today, global companies such as Amazon, Google, Meta, and Microsoft are already investing billions of dollars to build the infrastructure required to support the next generation of AI systems.

“Building an LLM model requires a considerable amount of risk capital and the Indian ecosystem does not possess such resources,” says V Balakrishnan, Chairman, Exfinity Ventures, an early-stage venture capital firm.

There is clearly a distinct lack of risk appetite among Indian investors, and at the same time, there are limited avenues for attracting large capital from overseas investors.

Just to bring home the point, the IndiaAI Mission has a budget of around Rs 10,000 crore, which translates to around $1.2 billion.

Industry observers believe the government could have played a larger role in jumpstarting the AI ecosystem in India by allocating greater resources for building this infrastructure.

Another main requirement for AI companies is the availability of data. A mechanism to provide anonymised datasets could have helped Indian AI companies build more capable LLMs.

The absence of having a sovereign LLM model also raises strategic concerns. Dependence on foreign AI platforms creates vulnerabilities, especially when nations are weaponising their trade advantages. Restriction on rare-earth magnet exports or higher trade tariffs cannot be ruled out in an increasingly fragmented geopolitical environment.

There are others who argue that there is no need to build an LLM model which would be similar to that of reinventing the wheel, and one could always use the existing models available.

Instead, India could focus on leveraging existing foundation models to create applications and services tailored to local and global markets.

Talent remains another major concern. At a recent meeting with a venture capital firm in Bengaluru that has its origins in Silicon Valley, a partner remarked that there are just around 700 world-class AI specialists in the world, and the majority of them are residing in the United States and China.

Given this scenario, India may be several steps behind in the global AI race, and the question arises what would be the way forward. Is there a way that the country can leapfrog technologically and emerge as a significant AI player in its own right?

The biggest hope comes from the vast technical talent pool in the country. The expectation is that this technical talent will build a long line of applications on the existing AI models. This is already happening with numerous Indian tech startups that have pivoted towards becoming AI-first companies.

Arkam Ventures in its report titled - India AI: The Asymmetric Opportunity, highlighted the deep engineering talent available within the country. “We have a rare combination of deep engineering talent, a large domestic market, and structural cost advantages compared to the Western counterparts. What is particularly exciting is that Indian founders are no longer just adopting global technologies; they are increasingly building original products and platforms that can compete globally,” said Arkam Ventures Managing Director Bala Srinivasa.

This confidence comes from the experience of building population-scale digital infrastructure for billion plus people. The country's success in creating platforms such as Aadhaar and UPI demonstrates its ability to design and operate technology systems that serve hundreds of millions of users.

There is also the presence of the Indian IT industry which has more than four decades of experience serving global customers. The industry has successfully navigated multiple technological shifts, from enterprise software to cloud computing, and is well-positioned to adapt to the AI era as well.

If the government brings about coordinated action involving all the key stakeholders, India could still emerge as a credible AI player.

“India’s AI story will be won at the intersection of public infrastructure depth, frugal model architecture and founders who build systems that are by design, hard to replicate from anywhere else,” said Pari Natarajan, CEO of Zinnov, a global consulting firm, in a report.