WFP, in collaboration with Google Research, has developed SKAI, an AI-powered satellite imagery analysis tool that significantly accelerates disaster damage assessments. Using advanced machine learning, SKAI automates the identification of damaged buildings and infrastructure, providing critical insights in under 48 hours, 13 times faster and 77 percent cheaper than manual methods. In crises such as the Türkiye-Syria earthquakes and Pakistan floods, SKAI supported rapid assessments, enabling faster, more efficient humanitarian responses. By reducing reliance on manual analysis, the tool ensures that WFP and its partners can quickly determine the extent of damage, prioritize assistance, and allocate resources effectively.
Activity Type AI Tools/SolutionsResearch/Reports/AssessmentsThe 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 Enterprise Language Model (ELM) is an AI-powered corporate search and knowledge discovery capability designed to help staff quickly access operational information across multiple internal platforms, including the WFP intranet, document repository systems, policies, manuals, and other corporate knowledge sources. By enabling natural language queries and surfacing relevant information in seconds, ELM reduces the time spent searching across fragmented systems, supports faster decision-making, and improves access to institutional knowledge across headquarters, regional offices, and country offices. The platform is designed to assist users in discovering and navigating existing information sources while maintaining the appropriate governance, source attribution, and access controls.
Activity Type AI Tools/SolutionsThe Communications Division, particularly the Media Team, is responsible for drafting and issuing time-sensitive press releases, operational updates, statements, and social media content across HQ, Regional Bureaux, and Country Offices. There is a clear opportunity to standardize and accelerate editorial workflows by embedding AI-assisted guidance directly into the drafting process. A Teams-based assistant could guide authors through structured communications templates, provide automated tone, clarity, and style checks with brief rationales, suggest headlines, spokesperson quotes, and social media content, and support compliance with attribution and editorial standards. This would help reduce drafting time and revision cycles while maintaining consistency and quality across outputs, allowing communications teams to focus more on strategic messaging, editorial judgment, and storytelling rather than repetitive editing tasks.
Activity Type AI Tools/Solutions