India’s adoption of artificial intelligence (AI) is defined by speed and compression rather than slow, linear uptake, according to Rahul Patil, chief technology officer at Anthropic, who said the country’s scale and openness allow new technologies to move from idea to impact far quicker than in most markets.
“India’s story is not about gradual adoption. It is about compression. Things happen very rapidly and very quickly,” Patil said on February 16 after announcing the opening Anthropic’s India office Bengaluru office.
He pointed to the country’s ability to absorb and deploy new technology across millions of users and use cases in a short span of time.
Patil said this effect is visible in how developers, startups, and public institutions are already using large language models (LLMs) for real work, rather than experimentation alone. He described AI as the fastest improving technology he has seen across multiple tech cycles, calling it potentially the most transformative shift of the next 100 years.
That pace, he said, is what drew him to Anthropic, which is focused on building advanced models at global scale with an emphasis on reliability and safety.
Advantage India
The country has one of the world’s largest developer communities, with a significant share of new global developers coming from India.
Approximately, every one out of three new developers on GitHub is an Indian.
It also combines that talent with market scale, multilingual complexity, and a track record of public digital infrastructure, creating conditions where AI applications can be tested, refined, and rolled out rapidly.
“India is among the most optimistic countries about AI,” he said, adding that adaptability at scale and intellectual openness enable the country to leapfrog technology cycles rather than follow them incrementally.
As AI models continue to improve at speed, Patil said, applications that appear barely viable today are likely to become fully workable in a matter of months, reinforcing the case for builders in India to think bigger and move faster.
Anthropic’s AI approach
At the core of Anthropic’s approach, Patil said, is a simple test for every model and product: whether it helps people do real work better.
He cited examples from healthcare and life sciences, where AI tools are already being used to detect early warning signals in chronic care and to improve the efficiency of clinical research, potentially reducing the time taken to bring medicines and vaccines to market.
“Think about 100 years of innovation getting compressed in 10 years of medicine and life-saving drugs and health-related stuff getting compressed down to 5-10 years, the R&D of these things are also going to accelerate massively,” Patil added.
Anthropic’s Demand Areas
Beyond coding, which Anthropic’s Claude models are widely used for, Patil said the company is seeing growing demand from domains such as finance, legal work, policy research, biology, and chemistry.
Patil also highlighted Anthropic’s focus on safety, saying releases are frequently delayed until the company is confident that models behave responsibly as their capabilities increase.
As models become more powerful, investments in safety, and alignment have to scale in parallel.
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