The use of digital agriculture is expanding across Africa. Tools like artificial intelligence (AI), sensors and blockchain are helping farmers receive information about weather, pests, markets and farm management. AI can analyse images and other farm data to detect problems or support decisions. Digital traceability systems can record where food comes from and what happens to it along the supply chain.
These technologies offer considerable opportunities, particularly in horticulture. Fruits and vegetables are highly perishable, so a decision made at the wrong time can result in substantial losses.
But does better technology on its own produce better farming?
We are researchers specialising in horticultural science, post-harvest technology, agricultural engineering, crop quality and sustainable food systems. In a recently published paper, we investigated this question.
We reviewed studies published between 2005 and 2025 to examine how AI and blockchain are used in farming, their potential benefits and the barriers farmers face. We found that many existing approaches focus heavily on what the technology can do, such as tracking produce, automating processes and verifying digital records. They pay less attention to the people expected to use these systems, the conditions under which they operate and the rules governing how agricultural information is collected and shared.
What’s missing are clear rules about who controls farm data, how farmers benefit and how digital systems can meet the needs of smallholder farmers.
Based on these insights, we propose combining AI’s ability to predict problems with blockchain’s ability to protect records. Together, they could help farmers make better decisions and track their produce. The aim is to support more sustainable horticultural production and distribution, ensure that smallholder farmers can participate and benefit, and establish clear rules for how information is managed and decisions are made.
We identified four issues that need much more attention.
1. Smart technology needs good data
As agricultural decisions become increasingly data-driven, checking the quality of the data becomes crucial.
Blockchain is a shared digital record book. It allows approved users to store and check information. Farmers can use it to record information about their produce and share it with buyers. One attraction of blockchain is that records stored on it can be difficult to alter. In agriculture, this can strengthen traceability. For example, a blockchain can record where a crop was grown, when it was harvested and how it reached the buyer. Approved users can then check these records.
But blockchain has an important limitation. It can protect information after it has been recorded. It cannot guarantee that the original information was correct.
A sensor measures things such as temperature, moisture or light. But what happens if it gives an incorrect reading? A farm worker might also enter the wrong information.
Putting that information on a blockchain does not correct it. It may simply create a secure record of inaccurate information. An AI model trained on poor-quality data could produce an unreliable recommendation. An AI model is a computer system that learns from data to identify patterns, make predictions or suggest actions.
Our research identifies this as an important weakness, particularly in agricultural blockchain systems. The reliability of the final record still depends on the quality of the information entering the system.
2. Farmers need decisions, not simply more information
Our review found that digital tools can produce large amounts of information. But that information is not always useful to farmers. Imagine that a system correctly predicts that a crop is under stress, but the farmer receives the warning too late to do something about it.
African smallholder farmers also operate under very different conditions. Some have smartphones and reliable internet access. Others work where connectivity is weak, mobile data is expensive or digital skills are limited. These are among the barriers to digital agriculture identified by the UN Food and Agriculture Organization.
Therefore, technology cannot simply be designed elsewhere and handed to farmers for adoption. Farmers and other users should be involved in its design. Some services may need to work offline. Others may require local languages, simple text messages or voice-based communication.
3. Who owns the farmer’s data?
Digital agriculture is also creating a valuable agricultural resource: data. A farm can generate information about soils, crop performance, pest outbreaks, fertiliser use, water, yields, weather and market transactions. Combining information from thousands of farms can make it more useful. The data could help train AI models, develop agricultural products, assess risk or support lending and insurance decisions.
That raises an important question: who controls and benefits from the data? Agricultural data governance already raises concerns about ownership, privacy, access and the bargaining power of farmers dealing with digital service providers. Farmers generate valuable data but have limited power over how it’s subsequently used.
If farmers provide the information that makes a digital system valuable but have little control over what happens to it, digital agriculture could reproduce existing inequalities rather than remove them.
4. Farmers need a reason to adopt the technology
A technology may improve traceability, generate sophisticated reports or produce impressive dashboards. But farmers still have to invest time learning the system and may have to pay for devices, connectivity or services. There must be a clear benefit. Economic value needs to be part of the design from the beginning.
That benefit could be reducing crop or post-harvest losses, lowering input costs, improving yields, obtaining better prices or gaining access to new markets. This matters particularly for smallholders operating with limited capital. Cost, inadequate digital skills and weak infrastructure can all restrict adoption. If exporters, retailers, technology companies or regulators receive most of the benefits while farmers carry much of the cost of supplying the data, sustained adoption becomes difficult.
What needs to change
These four issues don’t mean Africa should turn away from AI, blockchain or other useful agricultural technologies.
Our research proposes a framework in which data collection, AI, blockchain-based verification, automated decision support and feedback work together.
There is another layer surrounding all of them: governance. This means setting clear rules. Who can access farm data? Who checks decisions made by AI? Who takes responsibility when something goes wrong? How are farmers protected? For example, community-governed data arrangements are one possible response.
Farmers could have a meaningful role in deciding how their data are collected, shared and reused. Farmer groups could help. By working together, smallholders may have more say over how their data are used.
Before expanding digital agriculture, governments, technology developers and agribusinesses should ask whether the information is reliable, whether farmers can act on the recommendations, who controls the data and whether the technology delivers measurable benefits.
Africa does not need more technology for its own sake. Farmers need tools that work in their conditions and help them make better decisions. The next breakthrough may not be another app, algorithm or blockchain. It may be making the technologies we already have genuinely useful to the people growing the food.
- is an Honorary Research Fellow, University of KwaZulu-Natal
- This article first appeared in The Conversation
