This post was originally published on The Economic Times
India has the AI (artificial intelligence) money, models, and national infrastructure. Maharashtra, a major agricultural state, provides the operating manual: data exchange, geospatial intelligence, farmer-focused advice, traceability, and outcome-driven scale-ups. Combine them, and AI translates into higher yields, lower risk, and better prices for farmers.
Recently announced, Maharashtra’s new Agri-AI policy takes a unique approach to agricultural innovation in India. Instead of flashy apps, it starts with shared infrastructure. In the new Agri-AI policy, the state suggests an Agriculture Data Exchange (ADeX) as a federated, consent-based platform. It offers access to weather, soil, crops, market, and post-harvest datasets through standard APIs. It includes identification, authorisation, and consent to ensure responsible innovation. A key component of the policy is the Sandboxing Environment, which allows start-ups and public agencies to test models using anonymised or synthetic data that mimic real farming conditions before any money is spent on field deployment. Together, ADeX and Sandbox form a practical digital infrastructure that lowers costs, reduces risks, and speeds up scaling.
The second key component of MahaAgri-AI policy is geospatial intelligence as a shared public benefit. Maharashtra’s plan sets up a unified, AI-powered Remote Sensing & Geospatial Intelligence Engine. This engine processes satellite, <a data-ga-onclick="Inarticle articleshow link
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