Artificial intelligence (AI), blockchain and digital farming technologies are creating new opportunities for agricultural development across Africa. However, farmers will only benefit fully if issues surrounding data quality, accessibility, ownership and economic value are addressed.
Digital agriculture is expanding through the use of sensors, AI-powered analysis and blockchain-based traceability systems. These technologies can help farmers monitor weather conditions, identify crop diseases, manage pests, improve production decisions and track agricultural products throughout the supply chain.
The opportunities are particularly significant in horticulture, where fruits and vegetables are highly perishable and delays in decision-making can result in substantial post-harvest losses.
In a study published in Frontiers in Sustainable Food Systems, researchers examined how AI and blockchain could work together to support more sustainable and inclusive agricultural value chains.
The research reviewed studies published between 2005 and 2025 and identified a gap between the technical capabilities of digital farming tools and the practical conditions experienced by farmers, particularly smallholder producers.
The researchers propose combining AI’s predictive capabilities with blockchain’s ability to maintain verifiable digital records. However, they emphasise that four important areas require greater attention before these technologies can deliver widespread benefits.
1. Reliable Data Is Essential for Smart Agriculture
Digital agricultural systems depend on accurate information to generate useful recommendations.
Blockchain technology provides a shared digital record system through which approved participants can store and verify information. In agriculture, this can support traceability by recording where crops were produced, when they were harvested and how they moved through the supply chain.
However, blockchain cannot guarantee that the information initially entered into the system is accurate.
For example, an incorrectly calibrated sensor could record inaccurate soil moisture or temperature readings. Similarly, incorrect information entered by farm workers could become part of a permanent digital record.
When AI systems use unreliable information, their predictions and recommendations may also be inaccurate.
The researchers therefore highlight the need for stronger data verification processes, reliable sensors and appropriate quality controls throughout agricultural information systems.
2. Digital Tools Must Deliver Practical Decisions
Although digital farming technologies can generate large amounts of information, that information does not always translate into useful decisions.
An AI system might identify crop stress or predict a potential pest outbreak, but its value is limited if the farmer receives the information too late to respond effectively.
Smallholder farmers across Africa also operate under different conditions. Some have access to smartphones and reliable internet connections, while others face expensive mobile data, limited connectivity and inadequate digital skills.
The researchers argue that agricultural technologies should be designed around the conditions in which farmers operate.
Practical solutions could include offline functionality, local-language interfaces, voice-based services and simple mobile communication systems.
Involving farmers in the design and development of digital agricultural tools can also help ensure that the technology addresses actual production challenges.
3. Farmers Need Greater Control Over Agricultural Data
As farms become increasingly connected, agricultural data is becoming a valuable resource.
Information about soil conditions, crop performance, fertiliser application, water consumption, yields, weather and market transactions can support AI development, agricultural research, lending and insurance services.
However, the increasing value of this information raises questions about ownership, privacy and access.
Farmers generate much of the data used by digital agricultural platforms, but they may have limited influence over how that information is collected, shared or commercially used.
The researchers warn that without appropriate data governance, digital agriculture could reinforce existing inequalities rather than create more opportunities for smallholder producers.
They propose clearer rules governing data access, ownership and reuse, alongside arrangements that allow farmers and their organisations to participate in decisions about their information.
Community-governed data arrangements and farmer cooperatives could help strengthen farmers’ bargaining power and participation.
4. Technology Must Provide Measurable Economic Benefits
The adoption of digital agriculture also depends on whether farmers receive tangible value from using these systems.
Although sophisticated dashboards, digital records and automated reports may improve information management, farmers still need to consider the cost of devices, connectivity, training and technology services.
For adoption to be sustainable, digital tools should contribute to measurable improvements in farming operations.
Potential benefits include:
- Reducing crop and post-harvest losses.
- Improving yields and production efficiency.
- Lowering agricultural input costs.
- Supporting better market prices.
- Improving access to new buyers and markets.
- Strengthening supply-chain traceability.
These benefits are particularly important for smallholder farmers operating with limited financial resources.
The researchers emphasise that technology developers, exporters, retailers and other agricultural stakeholders should ensure that farmers share in the economic value created by the data and digital systems they help support.
Building a More Inclusive Digital Agricultural System
The research proposes an integrated framework that combines agricultural data collection, AI-powered analysis, blockchain-based verification, automated decision support and continuous feedback.
However, effective implementation also requires appropriate governance structures.
Questions surrounding who can access farm information, who is responsible for AI-generated recommendations and how farmers are protected must be addressed as digital systems expand.
Governments, technology developers and agribusinesses are encouraged to work with farmers to establish systems that are reliable, accessible and economically beneficial.
The researchers conclude that Africa’s agricultural future will not depend simply on introducing more applications or advanced technologies. Greater value will come from ensuring that digital tools respond to farmers’ actual needs and help them make better production and business decisions.
As investment in smart farming and agricultural technology grows, combining reliable data, practical AI applications and transparent information management could help strengthen Africa’s horticultural production and supply chains.
