AI for Country Strategic Planning

Country Strategic Plans (CSPs), which outline WFP’s priorities and actions in a specific country to address hunger and support food security, are built by carefully analyzing a wide range of information, including various reports, policy documents and lessons learned. This thorough analysis is essential for identifying gaps and making strategic decisions tailored to the needs of each country office. However, reviewing all this information manually is time-intensive, and decision-making can be constrained by limited time and access to insights. These challenges highlight the need for more efficient ways to manage complex information, ensuring staff time is used effectively without compromising the quality of strategic planning.

AI for Country Strategic Planning (AI4CSP) leverages Large Language Models (LLMs) to efficiently analyze and extract key insights from complex documents, such as Country Strategic Plans, reports, evaluations and WFP strategies and policies. This approach reduces the time required for manual analysis, optimizing the process of developing Country Strategic Plans. By identifying gaps and modeling potential strategic shifts, the initiative supports more informed decision-making, ultimately enhancing strategic planning and ensuring stronger alignment with WFP’s priorities and goals.

The project will have the greatest impact during the early stages of developing Country Strategic Plans, specifically the inception and formulation phases. It will help WFP more effectively participate in Humanitarian Response Plans, Common Country Analysis (CCA) and the United Nations Sustainable Development Cooperation Framework (UNSDCF) processes. By using evidence-based modeling, the project will demonstrate how different programming decisions could affect outcomes in collaboration with partners, ultimately strengthening the overall CSP formulation process.