Across Sub-Saharan Africa, a quiet revolution is underway. Smallholder farmers are increasingly leveraging Artificial Intelligence (AI), once a futuristic concept, to transform agriculture. AI now plays a crucial role in addressing the region’s most pressing challenges: food insecurity, environmental degradation, and economic inequality. 

The transformative power of AI in modern agriculture

Globally, AI in agriculture is projected to grow substantially at a compound annual growth rate of 23% between 2023 and 2028, increasing from $1.7 billion to $4.7 billion over that period. In Sub-Saharan Africa, the agri-food tech landscape has witnessed phenomenal growth, with private investments soaring from less than $10 million in 2014 to approximately $600 million in 2022.

AI’s rapid rise in agriculture is driven by a need for more sustainable farming, labor shortages, as well as rising costs and escalating food demand. 

AI technologies such as precision farming enable farmers to optimize resources and maximize crop yields. Satellite imagery, drones with high-resolution sensors, and geographic information systems help monitor crop health, soil moisture, and nutrient levels in real time. These technologies allow farmers to water their fields, and apply fertilizers and pesticides more efficiently, reducing costs and environmental impacts.

AI-powered computer vision also helps farmers identify weeds and pests, enabling targeted herbicide use to cut costs and minimize environmental impact. By analyzing drone or smartphone data, machine learning aids early disease and pest detection, safeguarding yields and reducing crop losses.

With more frequent and extreme weather events, predictive analytics powered by AI can also help anticipate risks and adjust planting schedules, while robotics and automation can address labor shortages caused by rural-urban migration, and autonomous tractors and drones help plant, monitor, and harvest with minimal human intervention.

Success stories in Sub-Saharan Africa

AI is already making a significant impact across Sub-Saharan Africa with innovative applications tailored to local needs. The World Bank Group has contributed by supporting various projects.

One such initiative is “Hello Tractor”, a platform that connects smallholder farmers with tractor owners and uses AI to streamline operations. In this project, machine learning is used to monitor tractor usage, forecast weather patterns, and enable communication via text messages in areas with limited internet access. Since 2014, Hello Tractor has digitized about 3.5 million acres, increasing food production by 5 million metric tons and creating over 6,000 jobs.

Another key initiative is the Kenya Agricultural Observatory Platform, which provides real-time data to 1.1 million farmers, delivering accurate weather forecasts and high-resolution agricultural insights. This technology is being scaled up through the Food System Resilience Program, benefiting approximately 6 million farmers across West Africa by optimizing planting and harvesting times and mitigating risks from unpredictable weather.

In Cameroon, an AI-powered mobile app is helping farmers identify crop diseases early by uploading photos of affected plants. Farmers receive instant diagnoses and treatment recommendations, which reduces crop losses and boost yields. This app can be used offline, making it accessible in areas with limited internet.

Other examples include AI-based soil testing kits in Ghana, which analyze soil samples and provide tailored fertilizer recommendations, and AI platforms in Tanzania which connect farmers directly with buyers, eliminating middlemen and ensuring fair pricing.

Challenges in implementing AI in agriculture in the region

Several challenges impede AI’s wider adoption, starting with the digital divide. Many smallholder farmers lack access to technology and infrastructure. Limited internet connectivity and high costs of related digital infrastructure hamper the dream of a tech-savvy agricultural landscape.

Another challenge is the lack of skilled workers. The current education system does not prioritize digital literacy and agricultural technology. Comprehensive training programs focused on data analytics and AI applications are essential to empower farmers to leverage modern technologies.

Financial constraints add another layer of complexity. The high initial investment for AI-solutions deters farmers who operate on slim profit margins. Innovative financial models, such as microfinance and government initiatives, could make the technology more accessible.

Effective AI implementation requires not only robust governance framework but also high-quality data that meets minimum requirements for volume, variety, veracity, and velocity. While data enables precision farming and predictive analysis, challenges such as insufficient data availability, inconsistent quality, and fragmented datasets often hinder progress. 

Additionally, there are concerns about data ownership, privacy, ethics and regulatory oversight. Establishing clear frameworks for data governance and ethical AI policies will help build trust and ensure AI benefits the larger community.

The road ahead: seizing opportunities

A strong policy framework is crucial to harness the benefits of AI into Sub-Sharan Africa’s agriculture. Governments, universities, tech companies, and local farmers must collaborate to share knowledge and ensure widespread access to advanced tools.

Policy priorities must be set across the short, medium, and long term, balancing quick wins with strategies aiming to build a robust AI ecosystem in the agriculture sector. These include:

Over the short-term (1-2 years): Focus on expanding digital infrastructure, including affordable internet and subsidized data plans in rural areas, while launching farmer training programs to demonstrate low-cost AI tools. Key initiatives include developing open data platforms, piloting AI solutions for precision farming, crop disease detection, and supply chain optimization, and providing financial incentives for early AI adopters.  

Over the medium-term (3-5 years): Strengthen data infrastructure through internet of things and satellite technology, integrate AI into agricultural education, and establish regulatory frameworks for data governance. scaling up successful AI pilots targeting climate resilience, pest control, and post-harvest losses, while fostering regional collaboration for knowledge sharing.  

Over the long-term (5+ years): Align AI initiatives with national development goals, invest in climate-smart solutions, and foster local innovation. Ensure inclusive access for women, youth, and smallholder farmers, and establish monitoring and evaluation systems to track AI’s impact on productivity, food security, and livelihoods.  

AI offers transformative potential for agriculture in Sub-Saharan Africa. It has the power to enhance efficiency, productivity, and sustainability. By promoting collaboration, enacting supportive policies, and investing in innovation, the region can leverage AI in achieving food security and fostering economic growth. The World Bank Group is committed to supporting this important journey.