Advances in artificial intelligence (AI) will be the most important contributor to the transformation of agri-food systems in Africa. OpenAI’s ChatGPT application exemplifies the rapid pace of progress in AI capabilities in the last year alone. Artificial intelligence and other automation technologies present game-changing opportunities for the continent’s smallholder farmers, particularly when delivered through low-tech delivery channels, intermediary networks and through partnerships with value chain stakeholders to subsidize costs.
A report from Genesis Analytics provides a sneak peek into that future. Data from sensors, satellites and drones allow for optimal land use based on crop suitability.1 Automated systems, including irrigation, ensure efficient use of resources.2 AI-powered advisory services provide farmers with timely, tailored advice to boost yields and manage pests, reduce crop failure, spoilage and enhance food security.3 Precision agriculture minimizes costs and environmental impact by using resources efficiently.4 Traceability tools reduce certification costs, expanding market access. AI-driven risk analysis facilitates access to critical financial services such as credit and insurance.5 The report identifies the types of solutions with existing pockets of adoption that impact smallholder farmers in Africa.
However, the realization of these benefits in general is far from automatic. Most of these solutions are concentrated in Kenya, South Africa and Nigeria.6 Even where solutions exist, smallholder farmers without access to the networks, hardware and capital necessary to use these solutions will not benefit. There is a risk that larger farms, enabled by technology, will overtake smaller farms in productivity and endanger rural livelihoods. Gender disparities in technology adoption can exacerbate household disparities, and concerns about data governance and potential workforce displacement due to AI-enabled automation exist.7
To navigate these challenges and fully realize the potential of AI, four areas must be prioritized:
- Building strong data and technology infrastructures: The power of AI is in the data. As businesses control much of this asset, creating incentives to share this data is critical. By lowering the cost of on-farm technology like sensors and drones, governments can level the playing field. Developing agriculture-specific open source software infrastructure can support AI tools that adapt to local African environments at scale.
- Champion farmer-centric solutions: For AI to have a broad impact, solutions must be rooted in local contexts. This means tools in local languages, imported through trusted human intermediaries. Empowering agricultural cooperatives to participate in the development of AI solutions and become procurement agents can boost AI adoption. Unlocking government demand for air conditioning extension digital advisory services will go a long way in addressing the economic viability of these solutions.
- Balancing innovation with demographic and environmental transitions: With a growing youth population, empowering youth in Africa to transition into new job opportunities in the AgTech value chain is urgent. Climate change calls for environmentally friendly AI solutions, with AgTechs taking responsibility for their environmental footprint.
- Adherence to ethical standards in the use of artificial intelligence and data: As with any new technology, ethical challenges are inevitable. Impact assessments can prevent biases and participatory governance such as data trusts ensure fair use of data. Remedies for potential harms and specialized ethical assessment tools are essential. Emphasizing farmer-centric data governance, empowering organizations to support farmers, and establishing a regional AI lab can improve the accuracy and accountability of the AI ββmodel in African agriculture.