India's AI leap began with 1960s calculators and linguistic roots

History · Published 18 October 2026 Swipe more like this →

In short: Before the global generative AI boom, India was already pioneering machine intelligence to solve local problems. From early pattern recognition in the 1950s to building systems for Indian railway speech synthesis, the nation’s AI journey is a story of adapting high-tech tools to unique cultural and linguistic needs.

India's AI trajectory began decades before modern chatbots. Between 1954 and 1960, Rangaswamy Narasimhan led the development of the TIFRAC at the Tata Institute of Fundamental Research. The Computer Society of India was founded by him in 1965, during which time he also led early AI studies at TIFR. Simultaneously, in 1971, John McCarthy visited IIT Kanpur and donated a PDP-1 computer, while H.K. Kesavan informally permitted colleagues to introduce artificial intelligence into computer science classes.

The 1980s marked a shift toward structured national programs. The Indian Statistical Institute launched an Optical Character Recognition Project, one of the country's first machine learning attempts. In 1986, the Department of Electronics initiated the Knowledge Based Computer Systems Project with UN Development Programme support—India's first major AI research program. This era also saw the birth of computational linguistics; in 1984, the Akshar Bharati Research Group was established to focus on NLP and translation theories for Indian languages.

Modern growth is now driven by a mix of government policy and private investment. The 2018 National Strategy for Artificial Intelligence and initiatives like Digital India have fostered a bottom-up approach to AI. Today, the market is projected to reach $8 billion by 2025, with services potentially valued at $17 billion by 2027. Despite placing 10th worldwide for private sector AI funding, India has become a major consumption centre, holding the top percentage of ChatGPT mobile app users and ranking third for DeepSeek's user count in 2025.

The focus remains on 'transformative' applications. Projects like Eklavya (IIT Madras) help health workers treat toddler illnesses, while C-DAC’s GIST technology addresses the challenge of adapting Latin-script software to Devanagiri and other Indian scripts. However, this rapid expansion faces hurdles including data privacy concerns, skill shortages, and an increase in AI-driven cyberattacks.

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