Applications of Artificial Intelligence to Global Food Security
How AI can improve food forecasting, donation logistics, beneficiary targeting, and hunger-relief operations.
Artificial intelligence is presented as an emerging tool for improving the way organizations understand and respond to food insecurity. The journal explores applications including predictive analytics for identifying potential food crises, supply-chain and logistics optimization, and data-driven beneficiary targeting. AI could help organizations anticipate food-price increases, droughts, and hunger hotspots, while also improving the matching of surplus food with areas of need and optimizing delivery routes to reduce waste.
For Nigeria's hunger-relief sector, the journal recommends a gradual and practical approach to AI adoption. Rather than requiring expensive, complex systems from the beginning, organizations such as Pink Food Bank could start with low-cost predictive models, mobile data collection, and better beneficiary databases. The research also identifies challenges around data infrastructure, technical capacity, connectivity, privacy, and trust. It therefore emphasizes staff training, partnerships with technology providers, shared data infrastructure, and human oversight of AI-generated recommendations.
