Artificial Intelligence for Environmental Sustainability: Applications, Opportunities, and Challenges in India

Abstract

Artificial intelligence (AI) is increasingly deployed across India's environmental and climate policy landscape, from village-level weather forecasting and cyclone prediction to precision agriculture, forest and biodiversity monitoring, and renewable-energy grid optimisation. This review surveys current AI applications for environmental sustainability in India, situates them within the national AI policy architecture — anchored by the IndiaAI Mission, approved in March 2024 with a budget outlay of roughly Rs 10,372 crore — and examines the opportunities and constraints shaping their scale-up. Documented applications include the India Meteorological Department's Gram Panchayat-level weather forecasting system, the high-resolution Bharat Forecasting System, AI-assisted cyclone forecasting, satellite- and drone-based precision-agriculture tools reaching farmers directly, and city-level heat-resilience systems such as Ahmedabad's Heat Action Plan. Alongside these opportunities, the review identifies significant challenges: the energy and water footprint of AI infrastructure itself, data and digital-access gaps in rural India, algorithmic and geographic bias in models trained on limited local data, and governance gaps in accountability and standards for AI-enabled environmental decision-making. The review concludes that AI's net contribution to India's environmental sustainability goals will depend on deliberately pairing AI deployment with the renewable-energy build-out, rural digital-infrastructure investment, and governance frameworks needed to ensure its benefits are both environmentally net-positive and broadly accessible.