Harness AI for efficient, localised humanitarian action
The humanitarian sector is hurting. Teams are shrinking. Budgets are being slashed. And yet, conflicts, disasters, and climate change are driving displacement and humanitarian needs to record levels. It’s a moment of impossible choices, and of urgent innovation. AI won’t solve every problem, but it can help us do more with less, faster and more locally.
Our 5th AI for Social Good webinar kicked off in June and focused on Harnessing AI for Efficient, Localised Humanitarian Action.
Here are three key takeaways from our expert panelists:
Where there’s data, there’s opportunity.
“Wherever you have data, you can leverage AI.” - Brent Phillips, Humanitarian AI Today
Brent shared how even simple AI tools can dramatically improve how information moves between local humanitarian settings and decision-makers. From translating relief updates to identifying patterns in needs assessments, AI is already helping humanitarian teams do more with less. His reminder was clear: we don’t need to wait for perfect infrastructure. The sector can - and should - be using existing data to enhance response right now.
2. Start small, start internally.
“Test on your organisation first before imposing on recipients.” - Rory Crew, CALP Network
Rory detailed CALP Networks’s deliberate and low-risk approach to AI adoption. Rather than racing toward flashy external tools, they focused on internal efficiencies: summarising reports, streamlining content development. The result? Greater trust, shared literacy, and ethical guardrails, all without risking harm to recipients. It’s a blueprint for responsible AI: experiment internally before scaling outwards.
3. Let local leaders lead.
“We want to empower the nonprofits to say what they need and what kind of users they want to approach.” - Carol Sánchez, Tech to the Rescue
Tech to the Rescue connects NGOs with pro bono tech partners, but they don’t start with tools. They start with local voices. Carol’s key message: nonprofits know their communities best. Rather than top-down solutions, AI projects should begin with local actors defining the problem, the user, and the context. When they do, the results are more impactful, inclusive, and sustainable.
The big takeaway?
If your organisation is exploring AI for social impact and in particular, for humanitarian action, start with people, not platforms. Start small, listen closely, and build with—not just for—the communities you serve. The opportunity is real, but so is the responsibility.
Didn’t make it or want to watch it again? Access it on our free AI resources webpage: https://www.polisync.org/ai-for-social-good-resources
Or watch it on our YouTube Channel here.
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Want to learn new GenAI tools? Sign up for our new, free Certificate in Applied AI for Social Good - an online, four-module, learn-at-your-own-pace course designed to help nonprofits integrate AI tools into their work effectively and responsibly www.polisync.org/ai-certificate
