"Four different sources, same message: Nonprofits are ready for AI-but the systems around them are not. The data is clear: 84% of AI-powered nonprofits lack funding to further develop and scale AI solutions. 87% of funders admit they don't understand their grantees' tech capacity. 90% of nonprofits don't fund AI literacy or infrastructure. And yet, the organizations seeing the biggest results are those that fine-tune AI with their own data, test quickly, and integrate community feedback."
"For the last five years, our organization has helped nonprofits worldwide build tech solutions in partnership with leading tech companies. It worked. It made a difference. But by 2025, it became clear: What brought us to this point won't take us to where we want to go. We could keep matching tech needs with builders. Or we could bet on something bigger-teach nonprofits how to prepare for an AI-native future, so they can be capable of building and scaling impact themselves. We chose the latter."
Technology is advancing faster than current impact models, forcing nonprofits to choose between optimizing existing approaches or rebuilding for an AI-native future. A leadership decision shifted strategy from matching tech builders to teaching nonprofits how to prepare for and scale AI-driven impact themselves. Recent reports show major capacity gaps: 84% of AI-powered nonprofits lack funding to scale, 87% of funders don't understand grantees' tech capacity, and 90% of nonprofits don't fund AI literacy or infrastructure. Organizations that fine-tune AI with their own data, test quickly, and integrate community feedback achieve the largest results. The primary bottleneck is organizational capacity, not technology.
Read at Fast Company
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