IGAIP – The International Geneva AI Innovation Programme
How can AI expertise help address concrete humanitarian challenges? The IGAIP Programme takes a first step: In June 2026, the first projects were selected for funding. The IGAIP projects are focused on applied, sovereign AI applications that help UN agencies and other international organizations based in Geneva deliver their humanitarian aid mandates more effectively.
The IGAIP Programme aims to lower barriers to compute, frontier models, open data, and AI expertise to enable organizations of International Geneva and researchers to build and operate AI systems on their own terms, with transparency and interoperability at the core.
Current IGAIP Projects
From refugee self-reliance to public health, climate risk, and AI-assisted learning, the projects show how AI expertise can be directed toward concrete humanitarian challenges.
The projects started in July, 2026, and are expected to produce results by February, 2027.
Self reliance and job matching for refugees
Project: AI-Supported Interviews and Job Matching
Team: ETH Zurich, Prof. Dominik Hangartner together with the external page UN Refugee Agency, UNHCR
Labor market integration is central to the self-reliance of refugees. The currently used digital tools to help refugees find work rely on static forms to collect information on refugees' skills and constraints and to match them to local vacancies. This project aims to create a more effective and scalable solution. It will develop and evaluate two complementary AI-supported technologies for the UNHCR workflows—one is a safe, structured, multilingual interview agent that helps create high-quality refugee jobseeker profiles, the other an explainable matching algorithm that links these profiles to vacancy data.
Making better use of genomic data for global public health
Project: AI for Real-Time Integrated Genomic Analysis
Team: ETH Zurich, Prof. Tanja Stadler together with external page WHO
Genomic data are vital for public health, revealing transmission patterns, emerging variants, and mutations that may affect diagnostics, treatments, or vaccines. However, to be useful in practice, these data must be interpreted alongside epidemiological, biological, and event-specific information. This project will explore how AI can help combine such contextual knowledge with genomic data.
Risk mitigation for displaced people
Project: AI-Powered Early Warning and Profiling for Displaced Populations
Team: ETH Zurich, Dr. Christina Humer, Dr. Rita Sevastjanova together with the external page International Organization for Migration, IOM
Displaced populations, already uprooted by conflict or disaster, are highly exposed to the secondary risks of climate shocks that delay or prevent recovery. Yet frontline humanitarian responders currently lack integrated, rapidly deployable climate risk profiling tools at the displacement site level. To address this problem, the project will use existing AI climate models to pilot a generalizable system that provides predictive weather risk assessments for displacement sites based on GPS queries.
Support for AI Education
Project: Empowering Training, Education and Learning with AI
Team: ETH Zurich, Dr. Gerd Kortemeyer, Prof. Mrinmaya Sachan; EPFL, Pexternal page rof. Martin Jaggi together with the United Nations Institute for Training and Research, external page UNITAR and the United Nations International Computing Center, external page UNICC.
UN agencies such as UNITAR run training programmes for thousands of professionals across dozens of countries, yet developing curriculum-aligned materials and providing individualised learning support remain largely manual processes. The project addresses this gap by developing an integrated AI-assisted learning and content generation system based on Ethel, an open-source AI platform deployed at ETH Zurich and EPFL.