| Summary: | This presentation explores how artificial intelligence can advance gender-responsive climate information services in Kenya. Drawing on a five-year analysis of over 9,000 iShamba advisory queries from women farmers, the study identified referral, language, and regional biases that influence inclusivity and service quality. These insights informed a field validation with 130 farmers—88 women and 42 men—across Kiambu, Meru, Kakamega, and Nakuru counties. Results demonstrate that refining AI advisories through human-centered design and reinforcement learning improved accuracy and contextual relevance from 62% to 83%. The findings underscore both the transformative potential and the risks of AI in delivering equitable digital climate services.
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