Amitabh Kant says India can strengthen its position in artificial intelligence by scaling data-centre capacity, alongside leveraging Indian data and talent. He argues that while the global large language model (LLM) race is led by the United States and China, India can build an advantage through improved data infrastructure and AI applications.
In his remarks, Kant links competitiveness in AI to investment in the computing backbone used to train and run AI systems. The proposal he highlights involves a large-scale expansion of data centres, described as potentially reaching about $200 billion. The focus is on enabling broader access to the infrastructure needed for AI development and deployment.
Across the coverage provided, the core emphasis remains on infrastructure-led strategy: using domestic assets and new capacity to reduce dependency on external compute and to support local AI initiatives. The coverage frames the effort as a response to the current leadership of other countries in the LLM space, rather than as an immediate shift in global AI rankings.
