4 September 2026. Financing Generative AI for Agricultural Advisory.
Artificial Intelligence is rapidly reshaping African agriculture, with generative AI offering personalized, real‑time advisory across crops, livestock, weather, and markets at a fraction of traditional extension costs.
Yet unlocking this potential for smallholder farmers requires financing to move beyond pilots and building shared data and digital public infrastructure that ensures accuracy, trust, and accountability.
This plenary brought both challenges into a single dialogue, drawing on the work of the Institute for Agriculture and AI, launched through a partnership between the Gates Foundation and United Arab Emirates. The institute is essentially an AI-powered agricultural advisory and research hub. Its goal is to turn advanced AI and agricultural data into practical tools for farmers, governments and NGOs, particularly in Africa, Asia and other climate-vulnerable regions. Its work includes:
🌱 Crop, soil and weather advice tailored to specific locations
🔬 AI models for crop-disease and pest detection
🗣️ Voice-based agricultural advisers that can work in local languages
🤖 Geo- and time-aware AI/LLM systems that provide localized farming recommendations
📊 Building large, open agricultural datasets for AI research
🎓 Training agricultural ministries, NGOs and other organizations to deploy these systems
🚜 Supporting country-level pilots and real-world deployment
Rwanda's Local AI Goals
1 September 2026. Side event AFS Kigali. AI and agricultureRwanda is already testing new AI tools to help farmers who do not have smart phones or good internet. According to local reports highlighted by Vision Media Rwanda, “One of the tools being tested is Tunga, an AI-powered voice assistant integrated into the agriculture ministry's call centre.” Farmers speak in Kinyarwanda to get fast crop and fertilizer advice. Rwanda wants to use these tech tools to reach more people with fewer field workers.
The government also wants to build on digital platforms such as e-Soko and Smart Nkunganire. More than 1.5 million farmers are registered on Smart Nkunganire, which allows them to order subsidised seeds and fertilisers through USSD.Wearing Scientific goggles
Interview with Prof. Hlamalani (Hlami) Ngwenya Associate Professor; Head of the Research Chair: Communication for Innovation, University of the Free State (UFS), South Africa, within the Centre/Department of Sustainable Food Systems and Development.
Background
Prof. Hlamalani (Hlami) Ngwenya’s “Wearing Scientific Goggles” approach is a way of encouraging practitioners to look at their everyday work through a scientific and reflective lens, rather than treating research and science as something that happens only in universities or laboratories.
The approach recognises that practitioners are often innovators and possess valuable tacit knowledge—insights gained through experience that are rarely documented, validated, or shared as formal knowledge.
- By applying structured inquiry, reflection, evidence gathering, pattern recognition, systems thinking, and documentation to their daily practice, practitioners can transform experience into credible knowledge products that can inform theory, policy, and practice.
- In this sense, the approach seeks to bridge the gap between theory and practice, empower practitioners as knowledge producers, and strengthen the “Science of Delivery” by making real-world implementation knowledge visible and scientifically useful.
The “Wearing Scientific Goggles” (WSG) approach has important implications for the use of Artificial Intelligence (AI) in African Agricultural Extension and Advisory Services (AEAS) because it shifts the focus from “using AI as a technology” to critically examining, learning from, and improving AI-enabled practice.
Applied to AI, this means extension officers should not simply accept AI-generated recommendations but should become co-investigators of AI in practice—testing whether recommendations are agronomically sound, locally relevant, understandable, culturally appropriate, and useful to different categories of farmers - preferably using local languages.
The Wearing Scientific Goggles approach implies that the use of local African languages in agricultural chatbots should be understood as an object of critical inquiry and continuous learning, rather than simply a technical translation problem. Extension officers, farmers, developers, and researchers should jointly test whether AI-generated advice in local languages is linguistically accurate, agronomically sound, culturally appropriate, locally intelligible, and practically useful. This requires evaluating AI performance across languages and dialects, incorporating farmer feedback and local knowledge into iterative development, and treating language choice as an issue of inclusion, equity, and knowledge sovereignty.
Related
Your initiative was chosen from close to 1,500 submissions from 146 countries across the four award categories – Digital Inclusion, Digital Government, Digital Frontiers and Digital Pioneers – and reviewed by an international jury of experts. To reach the final 15 in a field of this size is a real distinction, and it places your work among the most compelling initiatives in digital inclusion brought forward this year. Mariia Shakura Project Officer International Telecommunication Union (ITU)The achievements of all the finalists will be celebrated at the Digital@UNGA Awards ceremony in New York on 21 September 2026





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