AI-generated advice as a reinforcement layer in climate-smart agriculture

Climate-smart agricultural (CSA) practices are central to food-system decarbonisation, yet adoption often falls short of farmers’ stated intentions, weakening the impact of incentives and extension under capacity constraints. We test whether spatially targeted, AI-generated advice can narrow this intention-action gap in a randomised field experiment with 1529 row crop farmers in Iowa, Illinois and Indiana during the cover crop decision window. Farmers assigned to receive four AI-generated emails were 4.45 %age points more likely to plant cover crops than controls (z = 2.81, p = 0.005), despite high baseline intentions in both groups. Effects operated on the extensive margin: there was no detectable change in the share of land planted among adopters. Survey responses indicate high engagement and a shift from untested optimism to more calibrated trust after exposure. Supervised AI advice can provide a low-cost, scalable complement to existing extension, improving follow-through and modestly expanding uptake without displacing human expertise.