India’s food system faces escalating climate risks amidst a growing population and widespread smallholder farms. This framework examines how geospatial AI—including satellite monitoring, climate risk mapping, and predictive analytics—can be seamlessly integrated into existing farmer networks to improve real-time knowledge dissemination and support scalable, climate-resilient agricultural practices across the country.
India’s vital agricultural sector supports nearly 50 percent of the nation’s population and is increasingly exposed to critical climate risks, including severe droughts, unseasonal floods, and massive pest outbreaks. While India has invested heavily in climate-resilient agriculture and foundational geospatial technologies, structural gaps remain between raw data generation and actionable use by smallholder farmers. Bridging this communication and information gap is absolutely critical to strengthening the country’s long-term adaptive capacity.
Leveraging the Extension Infrastructure
Since 2011, the Indian Council of Agricultural Research (ICAR) has led the flagship program National Innovations on Climate Resilient Agriculture (NICRA). Through its vast network of Krishi Vigyan Kendras (KVKs), NICRA has trained over 50,000 farmers in the use of drought-tolerant crops, advanced water management, and adaptive farming systems, while successfully fostering horizontal knowledge-sharing through village-level institutions. This established network provides a highly promising information delivery mechanism, but it has yet to fully incorporate real-time, dynamic geospatial intelligence.
In parallel, India has made significant advances in cutting-edge agricultural analytics. Government agencies and pioneering private firms now deploy AI-based monsoon forecasting, satellite-derived crop health indices, continuous soil moisture monitoring, automated pest surveillance, and real-time water stress mapping. Private platforms such as Cropin and foundational national systems like the Pest Surveillance System demonstrate the feasibility of predictive, data-driven agricultural advisories. However, access to these insights remains uneven, particularly among smallholder farmers facing limitations in digital literacy or connectivity.
A Framework for Integration
This framework builds a comprehensive policy model for systematically integrating geospatial AI tools into India’s agricultural extension infrastructure through the existing NICRA network. To achieve scalable success, the integration focuses on three strategic pillars:
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Institutional Design: Coordinating responsibilities seamlessly across central governmental agencies, ICAR research institutes, and localized KVKs to ensure a smooth flow of data.
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Technology Access and Knowledge Dissemination: Structuring who receives direct database access and determining how real-time, localized information can reach individual farmers at scale using accessible formats.
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Feasibility and Innovation: Constructing public-private partnerships (PPPs) to support scalable, financially viable, and sustainable operational models.
Through deep stakeholder consultations, this approach aims to produce actionable recommendations for piloting AI-enabled climate advisories in 10 to 15 high-vulnerability districts. Program success will be actively measured through local adoption rates, advisory accuracy, and tangible evidence of yield protection during extreme climate events, paving the way toward a more secure, climate-smart Viksit Bharat.
The author is from: MPA-Data Science for Public Policy & NXT Fellow 2026
