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Artificial Intelligence in Humanitarian Projects of the World Food Program
This study examines the potential of artificial intelligence (AI) to improve the effectiveness of the World Food Program (WFP). Focusing on complex humanitarian situations, it explores the ability of AI to address operational inefficiencies by streamlining logistics, reducing costs, and improving decision-making in crises. It begins by developing a conceptual framework based on case studies of AI use in such areas as earthquake relief in Nepal (International Red Cross), COVID-19 monitoring using BlueDot algorithms (World Health Organization), and the use of AI in UNICEF education initiatives, to demonstrate the effectiveness of AI technologies such as predictive analytics and machine learning. These examples highlight challenges in scalability and ethical governance of AI tools when applied to humanitarian projects. The study focuses on analyzing WFP AI-based projects and identifying challenges such as skills shortages, data privacy issues, resistance to technological change, expected high implementation costs, and weak digital infrastructure in crisis regions. While WFP projects such as SCOUT, SHAPES, and SKAI ensure more efficient and sustainable delivery of humanitarian aid, the limited adoption of AI by WFP highlights the need for further innovation.