The recently concluded AI summit was a signal moment in the country’s digital journey. With packed halls, global CEOs, innovators, policymakers and researchers under one roof, the event underlined India’s ambition not merely to consume Artificial Intelligence but to shape it. A key highlight was the buzz around home-grown large language models (LLMs).
Players such as Sarvam AI and BharatGen unveiled models tailored for Indian languages, governance needs and sector-specific use cases. The emphasis was clear — that India’s AI story must go beyond English-speaking urban elites and address agriculture, healthcare, education and public service delivery. If these models deliver on scale, costs and linguistic diversity, they could democratise AI in a way global platforms have not fully achieved. Equally significant was the adoption of the Delhi Declaration which is a voluntary, non-binding framework endorsed by over 88 nations. The declaration seeks to anchor AI development in shared values. In a world increasingly fractured over technology governance, even a voluntary alignment signals recognition that AI’s risks and rewards are global. Global technology leaders such as Sam Altman, Sundar Pichai and Vinod Khosla had interesting observations to make. On one hand, they suggested that AI is edging closer to systems with ‘superintelligent general intelligence’. On the other, they were candid about the disruption ahead. Jobs will change, work will be redefined and productivity gains may not translate neatly into wage growth.
For India, that warning should be the real takeaway. If AI enables companies to do more with fewer workers, or with differently skilled workers, the ripple effects on income distribution and demand could be profound. The response must begin with education. Schools and colleges need to urgently rejig curricula to prepare students for a world where humans collaborate with machines. Foundational digital literacy, critical thinking, interdisciplinary learning and ethical reasoning must move from the margins to the core. Coding alone will not suffice; understanding how to work alongside AI systems will be as crucial as building them. Industry, too, must shoulder responsibility. Companies deploying AI at scale should commit to structured workforce transitions, identifying roles at risk, mapping emerging opportunities and investing in training. The cost of transition cannot be borne solely by displaced workers.
Finally, regulation requires foresight. Allowing industry to craft its own guardrails may spur innovation in the short term. But as AI diffuses at population scale, stronger institutional frameworks will be necessary to manage risks, from bias and misinformation to systemic shocks in labour markets. The experience of social media is instructive. Policymakers globally reacted years after platforms became ubiquitous, by which time data breaches and manipulation had taken root. India must ensure not to repeat that lag.
Published on February 23, 2026