AI for India: Ensuring An Equitable AI Future

India stands on the brink of an AI revolution. With one of the world’s largest and most diverse populations, a booming digital economy, and growing tech talent, the country is uniquely positioned to shape how artificial intelligence transforms society. But as we race to build smarter systems, we must pause and ask: Who is this intelligence for? And who might be left behind?

In India, the social impact of AI isn’t theoretical anymore. It is unfolding in real-time, across villages, classrooms, hospitals, and city streets. But its benefits  and its risks aren’t evenly distributed. If we want an AI-powered future that works for everyone, we need to build with care, context, and a deep sense of responsibility.

One of the most exciting frontiers of AI in India is healthcare. Startups like Qure.ai are using machine learning to interpret X-rays and CT scans, helping frontline health workers diagnose tuberculosis and strokes in low-resource settings. These tools are already being piloted by the government’s National TB Elimination Program, showing how AI can fill critical gaps in access.

In education and language, Sarvam AI is developing foundation models trained in Indian languages, a huge leap toward making generative AI accessible to the 90% of Indians whose first language isn't English. By building tools that understand Hindi, Tamil, and other regional tongues, Sarvam is laying the groundwork for inclusive digital experiences that reflect our linguistic realities.

In agriculture, platforms like SatSure are combining satellite imagery with AI to provide farmers with crop insights, weather warnings, and credit eligibility, often via simple SMS or app-based updates. If made accessible to smallholder farmers navigating climate change and unpredictable markets it can be a game-changer.

These are just a few examples of what’s possible when AI is used not to replace human expertise, but to extend it, especially in sectors where infrastructure is stretched thin. But AI is not neutral. It reflects the assumptions, data, and power structures of the people who build it. In India, this means we must be vigilant about how AI systems might encode, and even amplify, social inequalities.

Many Indian AI models are trained on skewed datasets that reflect dominant languages, urban biases, or gender and caste disparities. When faculty at IIT Madras noticed that international AI tools misinterpreted regional Indian language inputs due to poor dataset representation, they released AI models and datasets for 11 Indian languages. While this may seem like a small glitch, it can have big implications for public service delivery or moderation, and the initiative done jointly in collaboration with AI4Bharat aims to address this critical gap.

Meanwhile, job displacement remains a looming concern. While AI may create new roles, it threatens repetitive, low-skilled work, much of which forms the backbone of India’s informal economy. The rise of generative AI also brings uncertainty to India’s massive BPO and content creation industries, where entry-level jobs are most at risk.

Another area of concern is surveillance. Cities like Hyderabad and Delhi are deploying AI-based facial recognition in public spaces, often with little transparency or regulation. Civil society groups like the Internet Freedom Foundation have raised alarms about the impact on privacy and civil liberties, particularly for already vulnerable communities.

The good news is that India doesn’t have to copy-paste global AI models. We have the talent, data, and lived experience to build systems that are radically local, linguistically diverse, and ethically grounded. Initiatives like AI4Bharat are leading the way with open-source tools in Indian languages. The Ministry of Electronics and Information Technology’s support for Responsible AI projects reflects a growing recognition that transparency, inclusivity, and safety must guide both public and private innovation. India is also a member of the Global Partnership on AI (GPAI), contributing to global conversations on ethical and inclusive AI development.

Companies like Sarvam AI are proving that it’s possible to build India-first models that are not just technically sound, but socially relevant. This kind of context-specific innovation is the way forward. AI is neither saviour nor villain. It is a tool, and how we govern it will shape the social fabric of our country. In India, where disparities in language, access, and opportunity are deeply entrenched, we must design AI systems that uplift, rather than exclude.