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Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn

By Kristin Davis, Eliot Jones-Garcia, and Niyati Singaraju August 26, 2025 Generative artificial intelligence (gen AI) applications—which produce text, images, code, and other content based on surfacing patterns in vast datasets—promise many benefits for agrifood systems (e.g., reaching more people at less cost, availability around the clock, real-time data). One promising area for gen AI is agricultural extension services. Gen AI

Grounding AI in practice: What extension gets wrong, what extension gets right, and what AI can learn

By Kristin Davis, Eliot Jones-Garcia, and Niyati Singaraju

Generative artificial intelligence (gen AI) applications—which produce text, images, code, and other content based on surfacing patterns in vast datasets—promise many benefits for agrifood systems (e.g., reaching more people at less cost, availability around the clock, real-time data).

One promising area for gen AI is agricultural extension services. Gen AI tools such as chatbots accessed via tablets, computers, and smartphones can help services to reach more people with information tailored to their specific circumstances, drawing on real-time data. This form of automated “last mile” delivery offers a way to advise farmers spread out across rural areas at a fraction of the cost of deploying field staff, if these farmers can access and use digital tools.