AI in Smallholder Agriculture: Hype or Game Changer?

26 February 2026. AI in Smallholder Agriculture: Hype or Game Changer? by the Agri-Food Innovation Centre (SAFIC) of Strathmore University.

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Artificial Intelligence (AI) is rapidly transforming industries across the world  from healthcare and finance to education and logistics. Yet one important question remains: can AI meaningfully transform smallholder agriculture, or is it another wave of technological hype?

This question formed the foundation of the webinar, “AI in Smallholder Agriculture: Hype or Game Changer?”, convened by the Strathmore Agri-Food Innovation Center (SAFIC) Agri-Markets Data for Investment and Growth (AMDiG) Community of Practice. The discussion brought together experts in agricultural systems, digital finance, and responsible AI to explore whether emerging technologies can address the real constraints farmers face today.

• Dr. Denis Mujibi The Associate Center Director SAFIC opened the discussion by emphasizing that while AI has become part of everyday digital life, its relevance to farmers must be judged through practical outcomes. Smallholder farmers operate within complex ecosystems shaped by climate risks, fragmented markets, and limited access to advisory services. Many challenges, speakers noted, are not caused by lack of effort or knowledge but by broken information flows. Farmers often receive delayed, inconsistent, or inaccessible advice  limiting their ability to make profitable decisions. The discussion highlighted that improving how information moves across agricultural systems may be one of AI’s most important opportunities.
• SAFIC’s Principal Lead AI for Agricultural Transformation Mr. Joseph Gitonga, noted “Smallholder farmers operate under thin margins, climate uncertainty, fragmented value chains, and limited extension support. AI delivers the greatest value when it augments existing human systems rather than replacing them. Diagnostic and advisory AI tools are currently the most practical applications because they provide measurable and immediate outcomes.”

Rather than viewing AI as a universal solution, speakers agreed that its strongest value lies in augmenting existing human systems, particularly extension services. Diagnostic tools, localized advisory platforms, and decision-support systems were identified as early areas where AI can deliver tangible benefits. However, the panel cautioned that many digital agriculture initiatives fail because they provide information without enabling action. Technology must connect advice to inputs, markets, and financial services if farmers are to see real change.

• Dr. Elizabeth Wamicha an AI & Digital Innovation Researcher & Advisor – Qhala noted that “Trust in AI systems depends on transparency around how farmer data is collected, stored, and used. Farmer data literacy is critical so producers understand the value and risks associated with sharing their information. Farmers should be treated as knowledge contributors rather than passive data sources. AI development must shift from data extraction toward farmer empowerment and co-creation.”
• Digital finance specialist Jared Ochieng highlighted another critical challenge: despite increased access to financial services, many farmers remain financially vulnerable. Traditional credit systems rely on formal financial histories, leaving many smallholders “invisible” to lenders. AI offers an opportunity to incorporate alternative data  such as transaction patterns and behavioural indicators  to better understand farmer cash flows and risk profiles. Yet innovation must be approached responsibly. Without safeguards, AI-driven finance could deepen exclusion or expose farmers to new risks. Transparency, consumer protection, and ethical data use were identified as essential foundations.

A recurring theme throughout the webinar was trust. Experts emphasized that AI systems must be intentionally designed to include women, rural communities, and farmers with limited digital footprints. Poorly designed datasets risk reinforcing inequalities rather than solving them. 

Participants stressed the importance of treating farmers not merely as data sources but as collaborators in innovation. Building data literacy and ensuring transparency around how information is collected and used will be key to long-term adoption.

The webinar concluded with a clear consensus: AI has the potential to transform smallholder agriculture  but only if grounded in real farmer needs. Technology alone cannot solve systemic agricultural challenges. Success will depend on collaboration between researchers, innovators, financial institutions, policymakers, and farmers themselves. AI is neither pure hype nor an automatic game changer. Its impact will ultimately be defined by how responsibly, inclusively, and practically it is applied.