IOM, Google Cloud Unite for AI Crisis Planning

IOM

In the aftermath of conflict, disaster, or forced displacement, the speed of the humanitarian response can change lives. The International Organization for Migration (IOM) has collaborated with Google Cloud and mapping specialists Network Geographic Information Systems (NGIS) to reimagine IOM's existing LOCALISE planning system, ensuring that support reaches affected communities faster and more effectively than before.

At the heart of the work is a simple idea: the sooner teams on the ground can understand what a community needs, the sooner people can start rebuilding their lives. Using AI-powered tools built into LOCALISE, what used to take weeks of analysis can now be done in days - giving responders more time to focus on people rather than paperwork.

"People who are uprooted from their homes deserve timely support that protects their rights and dignity," said Amy Pope, Director General of IOM. "This initiative gives our teams better tools so they can plan faster, work more closely with local communities, and make sure that help reaches people when it matters most."

Effective humanitarian response has always depended on understanding the specific needs of the communities it serves. The upgraded LOCALISE Toolkit makes this considerably easier, incorporating community voices and local expertise directly into the planning process - ensuring that the people most affected by a crisis have a genuine voice in shaping the response.

The tool will first be piloted in two locations before a global rollout. By automating the use of AI for IOM's Displacement Tracking Matrix (DTM) and in gathering up-to-date images and maps of basic services like electricity, schools, hospitals, and water, teams will be able to quickly identify suitable sites and plan support based on real conditions on the ground.

Once available worldwide, IOM missions, governments, and partner organizations will be able to deploy it in cities, towns, and rural areas alike - planning and delivering assistance more efficiently wherever it is needed most.

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