The World Bank has called on Nigeria and other African countries to develop national agricultural data platforms that can provide the digital foundation needed to bring artificial intelligence into farming. The proposal seeks to transform existing investments in agricultural statistics into digital infrastructure capable of supporting tools such as crop mapping, yield forecasting, pest surveillance and targeted farming advice.

Nigeria is among 10 African countries where World Bank-backed agricultural surveys have generated detailed information on farms, crops, livestock, production, inputs and farming practices. According to the bank, these datasets, originally designed to strengthen agricultural statistics and policymaking, could now serve a bigger purpose by powering digital and AI-enabled agricultural services. The bank stressed that AI can only deliver useful results when supported by reliable and relevant data.

The proposed system would combine agricultural survey information with satellite imagery, rainfall and temperature records, soil maps, market data and government agricultural records. This could help AI models identify crops, estimate yields, detect drought or pest-related stress, predict potential production losses and help governments direct extension services and agricultural investments to areas where they are most needed. The World Bank cited research in Uganda showing that combining satellite imagery with household survey data can improve crop-yield estimates and reduce errors.

However, the bank noted that collecting agricultural statistics alone would not make Nigeria or other countries ready for AI-driven farming. It said agricultural data must be properly standardised, documented, georeferenced, interoperable and securely accessible, while strong privacy protections are also required. Beyond data, the bank identified connectivity, computing capacity, local context and technical skills as key requirements for wider AI readiness, alongside effective governance and cybersecurity.

Rather than immediately pursuing expensive, large-scale AI platforms, the World Bank recommended that African countries begin with practical applications such as crop mapping, yield forecasting, drought monitoring, pest surveillance and targeted agricultural advisory services. It also encouraged regional cooperation, including a possible federated African agricultural data architecture that would allow countries to retain control of their information while sharing standards and expertise. For Nigeria, the push could mark a new phase in agricultural development—one where data does not simply explain what is happening on farms but helps governments and farmers make faster, more informed decisions.

source: punch