Agri‑tech founders who want to serve smallholder and underserved farmers must build around the farmer, not around the technology.
Too many ventures start with a shiny app or a complex AI model and then struggle when farmers refuse to adopt it. The farmers who need help the most are often the least forgiving of solutions that do not fit their daily reality.
Globally, there are about 570 million farms, and around 90% are small farms (less than 2 hectares). These smallholders produce roughly one‑third of the world’s food.
Their contribution is especially critical in Asia and sub‑Saharan Africa, where they form the backbone of food systems. In Nigeria, more than 80% of farmers are smallholders, contributing about 90% of the country’s agricultural production.
Yet they frequently face post‑harvest losses ranging from 15% to 50%, depending on crop and region, due to poor storage and weak market linkages. When agri‑tech founders ignore these realities, they risk building solutions that look good on paper but fail on the farm.
Start with the farmer, not the code
The first thing founders must get right is their starting point. They must ask farmers what they need, not what they want to sell.
This means frequent visits to fields, cooperative meetings and local markets, listening to questions about prices, weather, pests and transport.
Many farmers will say they want “better technology,” but they will explain that they really need higher income, lower risk and less uncertainty. Solutions that emerge from these conversations are more likely to be used and trusted.
Design for literacy, connectivity and cost
Farmers often work in areas with limited electricity, patchy mobile networks and low digital literacy. An app that requires constant data, a smartphone and a fast connection will not serve the farmers who need it most. Founders must choose simple interfaces, offline functionality, voice‑based options, USSD or SMS, and designs that work on basic phones.
They must also price their services so that a small increase in income can cover the cost. A solution that seems cheap to an urban investor may still be out of reach for a farmer earning a few hundred dollars a season.
Align incentives with real‑world risks
Smallholder farmers are risk‑averse for good reasons. They cannot afford failed experiments when a bad season can mean hunger or debt.
Agri‑tech ventures must show clear returns within one or two cycles. Input‑financing models, pay‑as‑you‑grow irrigation, and bundled packages that include training and insurance have worked because they spread the risk and reduce the upfront cost.
When farmers see that a new tool or service can increase their yield or income without pushing them deeper into debt, they are more willing to try it.
Build trust through local actors
Farmers trust fellow farmers, local extension agents, cooperative leaders and input dealers more than they trust a new app or website. Successful agri‑tech models embed themselves in existing networks instead of bypassing them.
They train lead farmers, collaborate with cooperatives, and work with local agents who can explain and support the technology. This slows down scaling but strengthens adoption, because trust is earned slowly and lost quickly.
Make data work for the farmer, not just the investor
Data is often collected to show impact to investors, not to help farmers make better decisions. Agri‑tech founders should ensure that every dataset they gather can be turned into simple, actionable advice: when to plant, when to harvest, how to store, where to sell.
Farmers who receive timely, relevant information they can understand are more likely to keep using the service. Where possible, data should also be shared back with farmers in ways that give them leverage in negotiations with buyers or lenders.
Plan for the long haul, not the short sprint
Finally, founders must think like farmers. Farming is a long cycle of planting, waiting, harvesting and replanting.
Agri‑tech ventures that treat smallholders as a short‑term growth channel will burn out. Building durable systems that reduce risk, improve markets and strengthen communities takes patience, iterative learning and a willingness to adapt.
Start small, listen closely, and let the farmer’s reality shape the roadmap. When agri‑tech founders get this right, they do not just serve underserved farmers; they stand alongside them.
Stanley Ugwubujoh is a Data Analytics Manager with 15+ years of experience in agri-tech, fintech, and communications, where he builds data systems, analytics, and machine learning solutions that improve efficiency and decision-making. He is also a Tech Coach and co-founder of Noblex Initiatives, using fashion-inspired teaching to simplify technology for young learners while promoting data literacy and mentorship.
