India’s artificial intelligence ecosystem is expanding rapidly, but the country still faces significant challenges in building the compute, talent, capital and domestic models needed to compete at the frontier of AI.
The issue has gained attention as AI leaders in the US debate whether the development of increasingly capable systems should be slowed or deliberately paced. For India, however, the immediate challenge remains building the capabilities required to participate meaningfully in the frontier race.
The IndiaAI Mission is working to expand the country’s AI infrastructure, including access to more than 10,000 GPUs. However, global technology companies are committing substantially larger sums to AI infrastructure, highlighting the scale of the investment gap.
Indian AI companies and researchers are also working on domestic models and applications. Sarvam AI, for instance, has developed large language models trained from scratch in India, while Indian companies are increasingly exploring AI agents and other applications.
At the same time, policymakers have stressed the need for greater investment. Finance Minister Nirmala Sitharaman recently said India needs more spending on AI infrastructure and training to build the capabilities required for wider adoption.
The debate therefore involves two connected challenges for India: developing competitive AI infrastructure and models while also building appropriate safety, evaluation and governance systems as AI capabilities advance.
