Generative AI can be applied in various agricultural extension and advisory services, including farm mechanization, food processing, water management, crop monitoring and livestock management. Most training data sets contain copyrighted works, raising legal questions about their use, especially in agricultural extension services, where training data includes copyrighted images of soil, climate and plant conditions. In case the fair use defence fails, this working paper argues that the adoption of three key recommendations — creating clear data-sharing agreements, implementing remuneration programs such as revenue sharing or royalty payments and using a royalty-based compensation model — could help resolve copyright-related legal disputes and enable the wide-scale application of LLMs, and generative AI in climate-smart agricultural extension and advisory services.
