TLDR: A recent stakeholder dialogue organized by CGIAR focused on the integration of generative AI, such as chatbots and voice assistants, into digital agricultural extension services. The discussion highlighted the potential for scalable, personalized advice for farmers while also addressing critical challenges related to equitable access, farmer-centric design, and avoiding assumptions about farmers’ existing knowledge.
Generative Artificial Intelligence (gen AI) is rapidly gaining traction within the agricultural sector, with a particular focus on its application in digital extension solutions. A recent stakeholder dialogue, organized by CGIAR and published by the International Food Policy Research Institute (IFPRI) on October 7, 2025, delved into the opportunities and challenges presented by these advanced technologies. The event, supported by funders like the Gates Foundation and the United Kingdom, aimed to ‘ask the right questions’ regarding the deployment of gen AI in supporting smallholder farmers.
The core promise of gen AI in agriculture lies in its ability to offer scalable and personalized advice to farmers through conversational agents like chatbots and voice assistants. These tools are envisioned to supplement and enhance the work of human extension agents, potentially bridging knowledge gaps and improving agricultural practices across diverse regions. CGIAR, a global research partnership dedicated to a food-secure future, emphasizes transforming food, land, and water systems amidst the climate crisis, making digital innovation a key area of interest.
However, the dialogue also brought to light significant challenges in designing and deploying such AI tools equitably and effectively. A primary concern is the uneven rate of adoption among smallholder farmers. Many farmers in developing regions may lack the necessary access to fundamental digital infrastructure, including mobile phone technologies, internet connectivity, or even reliable electricity. Even among those with access, comfort levels with new AI tools can vary widely, potentially leaving some farmers behind.
Furthermore, the discussion critically addressed the risk of entrenching a ‘deficit-based assumption’ about new technologies. This perspective often presumes that farmers inherently lack knowledge, and that this gap can be ‘fixed’ externally through content or ‘nudges’ engineered by AI developers. Experts at the dialogue underscored that this approach can inadvertently downplay or ignore crucial farmer needs, overlooking their unique social, economic, and technical contexts, as well as the rich, community-based knowledge systems they already rely upon. The dialogue stressed the importance of a farmer-centric approach that respects and integrates existing local knowledge rather than replacing it.
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In conclusion, while generative AI offers transformative potential for agricultural extension, the stakeholder dialogue highlighted the imperative for thoughtful, inclusive, and context-aware development and deployment strategies to ensure that these innovations truly benefit all farmers and contribute to a more food-secure future.
