The World Food Programme’s (WFP) AI Strategy 2025-2027 sets a bold path for leveraging artificial intelligence to strengthen humanitarian response. AI is already enabling WFP to predict food shortages, accelerate emergency response, optimize supply chains, and allocate resources efficiently. The strategy – a first for a UN programme - provides a structured framework to scale these benefits further. It’s built on five key pillars: delivering impactful AI solutions, developing a robust AI infrastructure, ensuring strong governance and ethics, fostering an AI-driven culture, and forming strategic partnerships. These pillars ensure that AI is embedded responsibly across WFP’s operations, aligned with global UN AI governance principles, and designed to maximize impact while safeguarding humanitarian values. By embracing AI at scale, WFP aims to build a future where technology plays a central role in the fight against hunger.
Activity Type Policy/Regulatory GuidanceWFP’s Drone and AI-powered Emergency Preparedness (DEEP) solution enables rapid post-disaster assessments by automating the analysis of drone imagery. Using machine learning algorithms, DEEP quickly identifies and maps damaged infrastructure, allowing emergency teams to prioritize response efforts with greater accuracy. The technology has already been deployed in disaster-prone regions such as Mozambique, the Philippines, and the Caribbean, where it has significantly reduced the time required for damage assessments - from weeks to just hours. This AI-driven approach enhances coordination, strengthens disaster preparedness, and accelerates recovery efforts for affected communities.
Activity Type AI Tools/SolutionsSCOUT is a digital solution that automatically generates optimized global/regional-scale plans and strategic analyses for WFP's corporate inventory, supporting key decisions on what to buy, where from, when, and how to store and deliver it to operations. In 2024, SCOUT enabled seizing seasonal purchase opportunities for sorghum in Western Africa through longer-term sourcing & delivery planning, allowing WFP to secure USD 2 million in cost efficiencies and reducing off-season purchases by 37 percent compared to previous 3-year trends. The Supply Chain division is currently working on a project to use machine-learning technology for demand forecasting. This will allow further improving the accuracy of the forecasts that SCOUT will use to produce optimized supply plans, reducing the risk of over/understocking.
Activity Type AI Tools/Solutions
Using GenAI to build actionable, personalised insight for UN Mobility managers to enhance decision making, drive cost savings and efficiency in a scalable way.
The anticipated global impact could be as much as +70% of cost savings and reduce 20% of manual effort and cost savings for WFP and UN Agencies.