Why We Need AI in Humanitarian Aid: Efficiency in Crisis Response

Why We Need AI in Humanitarian Aid: Efficiency in Crisis Response
Thomas Byrnes
Thomas Byrnes
Humanitarian & Digital Social Protection Expert | Director of MarketImpact

November 11, 2024
Last week at the Estonian Refugee Council International Humanitarian Aid event in Tallinn (November 7, 2024), I joined an enlightening panel discussion with Karin Maasel Maasel (CEO, Data Friendly Space) and Robbie Phillips (Humanitarian Science and Technology Lead, FCDO), expertly moderated by Kristen Davis (CEO, CinqC). I want to share why AI's efficiency gains are becoming critical for our sector.

The Problem: A Sector Under Pressure
Let me start with a stark reality I shared during the panel: in 2016, global humanitarian funding averaged $160 per person in need. Today, that figure has plummeted to $60. This dramatic decline means we must fundamentally rethink how we operate. As I explained, humanitarian agencies now face an impossible equation - increasing needs, decreasing resources, and growing complexity of operations.

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Data from OCHA FTS and Global HNO
In my 14 years working across national NGOs, the Red Cross Movement, and the UN, I've never seen humanitarian agencies so overstressed. We're trying to make complex operations work with diminishing resources, while the scale and complexity of crises continue to grow.

AI's Efficiency Multipliers:
Rapid Data Processing During the panel, I shared a recent example from my work supporting the North West Syria response Cash Working Group. A local staff member used AI to analyze a Telegram video of arriving refugees from Lebanon. Within minutes, AI estimated approximately 2,000 people (final count: 2,300) - a task that would have taken much longer through traditional counting methods. This wasn't just faster - it was actionable intelligence that enabled immediate response planning.
Force Multiplication of Limited Teams During the Turkish earthquake response, I shared how the IFRC's three-person information management team leveraged AI to develop Python scripts for market analysis. They used AI not to analyze data, but to rapidly develop tools that could scrape Turkish websites, pull information from national statistics, and create visualizations. This allowed a tiny team to provide critical market functionality data within hours - information that would have been useless if it took weeks to compile.
Processing the Previously Impossible One of the most powerful efficiency gains I highlighted was in processing vast amounts of previously untouched data. Meeting minutes, complaints mechanisms, and community feedback that often went unanalyzed due to resource constraints can now be processed and acted upon. As I noted during the panel, "These people are bearing witness, and we're finally able to listen."
Automated but Accountable A key point Karin and I discussed was how AI enables automation while maintaining transparency. Their Gannet system, for instance, shows exactly which sources inform its analyses - something general AI tools often lack. This means we can gain efficiency without losing accountability.

Looking Forward
The efficiency gains from AI aren't just about doing things faster - they're about enabling our sector to maintain its effectiveness despite severe resource constraints. As I emphasized in Tallinn, we need these tools not to replace human judgment, but to ensure our limited human resources can focus on decision-making and community engagement rather than data processing.

What's your experience with AI efficiency gains in humanitarian work? Have you seen similar transformative effects in your operations?

Please continue the discussion at aidgpt.org

#HumanitarianAid #ArtificialIntelligence #Innovation #Development #HumanitarianTech #Aid #EstonianRefugeeCouncil #Tallinn

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Josh Mandell
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Tech/Data/Digital for Foreign Affairs
8mo

Thanks, Thomas. Interesting read. You said that funding has decreased while the magnitude of challenges has increased. From what I can see, the UN and USAID budgets have increased steadily every year for 10 years. When you say budgets have decreased, where does that data point come from? I don’t doubt it’s true but I’m less familiar w the assistance side of programming. Thanks
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Thomas Byrnes

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Humanitarian & Digital Social Protection Expert | Director of MarketImpact
8mo

Thanks, Josh. You’re right about overall increases in some budgets like the UN and USAID. However, in the past two years, overall humanitarian funding has actually declined, while needs have surged, causing an even steeper drop per person.
For example, in 2024, the UN appealed for $46.4 billion to help 180.5 million people, but only 32.7% was funded by September, leaving a $30 billion gap. This imbalance means funding per person has dropped from $160 in 2016 to around $60 today. The pressure to do more with less is why AI tools are so essential—they enable faster, more efficient responses without replacing human judgment.
To track these trends, OCHA’s Financial Tracking Service (FTS) is an excellent open-source tool, showing real-time data on global humanitarian funding and gaps. You can explore it on the FTS website. https://fts.unocha.org/
Thanks for raising this—it’s a key part of the picture. Happy to discuss further!
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Nice read

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