When institutional knowledge disappears, development organizations lose more than old reports. They lose hard-won lessons about what worked, what failed, and why.
Lindsey Moore's article in _Stanford Social Innovation Review_, When USAID Shut Down, Its Lessons Nearly Vanished. AI Helped Recover Them, looks at how AI helped recover lessons from decades of USAID evidence at a moment when that learning was at risk of being lost.
Why this matters
Development organizations generate enormous amounts of knowledge: evaluations, strategy documents, activity reports, learning briefs, monitoring data, and technical guidance. But much of that knowledge becomes difficult to reuse because it is spread across disconnected files, portals, and archives.
When teams cannot find prior learning, they risk repeating mistakes, missing useful patterns, or making decisions without the context that already exists inside the sector.
The SSIR article shows a practical use case for AI: not replacing development expertise, but helping recover, organize, and interpret institutional memory so people can apply it more effectively.
How it connects to DevelopMetrics
This is central to DevelopMetrics' work. We help organizations turn large, fragmented evidence bases into workflows that support real decisions, reports, and learning processes.
For us, responsible AI in development means:
- making evidence easier to find and compare,
- keeping outputs connected to sources,
- preserving context and limitations,
- and ensuring people remain responsible for interpretation and use.
The SSIR piece highlights why this work matters beyond any single tool. Development knowledge is valuable infrastructure. It should be easier to preserve, review, and apply.
Read the original article in _Stanford Social Innovation Review_: When USAID Shut Down, Its Lessons Nearly Vanished. AI Helped Recover Them.