Despite its status as a global tech hub, India lags far behind the likes of the US and China when it comes to homegrown AI. That gap has opened largely because India has chronically underinvested in R&D, institutions, and invention. Meanwhile, since no one native language is spoken by the majority of the population, training language models is far more complicated than it is elsewhere. So when the open-source foundation model DeepSeek-R1 suddenly outperformed many global peers, it struck a nerve. This launch by a Chinese startup prompted Indian policymakers to confront just how far behind the country was in AI infrastructure--and how urgently it needed to respond.

Historically known as the global back office for the software industry, India has a tech ecosystem that evolved with a services-first mindset. Giants like Infosys and TCS built their success on efficient software delivery, but invention was neither prioritized nor rewarded. Meanwhile, India's R&D spending hovered at just 0.65% of GDP ( 25.4 billion) in 2024, far behind China's 2.68% ( 476.2 billion) and the US's 3.5% ( 962.3 billion). The muscle to invent and commercialize deep tech, from algorithms to chips, was just never built. Isolated pockets of world-class research do exist within government agencies like the DRDO (Defense Research & Development Organization) and ISRO (Indian Space Research Organization), but their breakthroughs rarely spill into civilian or commercial use.