Harnessing artificial intelligence and machine learning for transformative African knowledge hubs: a road map for last-mile knowledge delivery and agricultural modelling
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This article explores the transformative potential of artificial intelligence (AI) and machine learning (ML) for developing and enhancing agricultural knowledge hubs across Africa. As agriculture remains central to food security and sustainable livelihoods on the continent, there is an urgent need to close the knowledge gap between scientific advancements and smallholder farmers. This study presents a guideline for integrating AI/ML technologies into agricultural knowledge hubs, highlighting their capacity to improve data aggregation, user engagement, interoperability, and the delivery of timely, context-sensitive knowledge to the last mile. In addition to detailing the technical infrastructure and policy recommendations necessary for success, the article also addresses challenges related to digital divides, data governance, and trust. Emphasizing inclusivity, collaboration, and ethical use, this road map seeks to guide national and regional stakeholders toward building resilient, intelligent knowledge systems that empower agricultural communities, foster innovation, and promote long-term development outcomes across Africa. The article was written as part of the Knowledge Management for Agriculture Development (KM4AgD) Challenge 2024, an initiative of the Forum for Agricultural Research in Africa (FARA) and collaborating institutions.
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artificial intelligence, machine learning, agricultural innovation, africa, knowledge