India, long considered a consumer rather than an innovator in emerging technology landscapes, is now staking a bold claim in artificial intelligence with its National Artificial Intelligence Mission. Recent moves, including budgetary commitments and the appointment of Bengaluru-based startup Sarvam to develop the country´s first sovereign large language model, mark a notable shift in ambition. Sarvam’s partnership with IIT Madras, alongside access to government-funded compute resources and talent, positions it as a technically strong contender in the global artificial intelligence race.
This momentum comes against a backdrop where the United States and China dominate artificial intelligence investment and model development. According to Stanford’s 2025 AI Index Report, the US leads in private sector investment—outpacing China by a significant margin—and has birthed a surge in foundational model development. Meanwhile, India had been largely absent from leading roles in both funding and model creation. The evolution of large language models, notably since the transformational Google paper ´Attention is All You Need,´ has fueled this global arms race, with the US and China setting the pace and Europe trailing behind.
Successfully launching a comprehensive national artificial intelligence initiative requires a nuanced, multi-step approach. Key stages range from designing transformer-based foundational architectures suited for diverse domains, to aggregating and curating massive heterogeneous data sources—encompassing manuscripts, literature, and digital resources. Elaborate preprocessing will be essential to ensure data cleanliness and quality. Fine-tuning large language models for domain-specific tasks and local languages, coupled with robust processes for model training and knowledge updating, stand out as critical technical challenges. Building user communities through adaptive learning modules, ensuring smooth deployment with minimal model hallucinations, and orchestrating government partnerships for compute resources are vital pillars. While optimism abounds with fresh investments and heightened interest from Indian product and platform builders, the journey remains fraught with complexity. The mission’s success hinges on cohesive engagement among the government, private sector, and broader society, as well as ongoing access to clean, validated data for all stakeholders.
As India embarks on its most assertive artificial intelligence undertaking yet, the effort marks not only a bid to catch up with global leaders but also an opportunity to design a uniquely Indian strategy for inclusive artificial intelligence innovation. The road ahead promises both exhilarating breakthroughs and formidable obstacles as India strives to translate ambition into lasting technological leadership.
