Dennis Fois is CEO of Bloomerang, a giving platform for growing nonprofits, focused on technology that helps organizations scale impact.
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Most people assume nonprofits are behind on technology. After spending time watching how fundraising professionals and executive directors are actually engaging with AI today, I’d argue the opposite is true. They’re asking exactly the right questions. The tools just haven’t been worthy of them.
For years, the technology industry sold nonprofits on systems that promised insight and delivered complexity. Getting a meaningful answer out of your donor database required either a trained analyst or a pain tolerance. The data was there, but the intelligence wasn’t. So organizations made decisions on instinct, memory or whoever had been around long enough to know where the bodies were buried.
AI is changing that, but not in the way most people talk about.
The dominant conversation about AI in the nonprofit sector focuses on content generation: Write my appeal letter, draft my thank-you note and help me brainstorm a campaign theme. These are real time-savers, but they’re also the least interesting thing I believe AI can do. If you’re using AI as a more eloquent search engine, you’ve bought a sports car to let it idle in a parking lot. You’ve bought a calculator when what you actually needed was a thinking partner.
What I’m seeing across our customer base tells a different story. When fundraising professionals engage with our AI co-pilot, they’re not primarily asking it to write things. They’re asking it to help them understand which donors are drifting, where the momentum is building and what the data is actually telling them. They’re using AI to finally have the conversation with their data that the tools never allowed before.
That matters more than it might seem. Nonprofit leaders aren’t waiting to be shown how to use AI strategically. They’re already oriented that way. The sector’s challenge was never a lack of curiosity or ambition. It was that the technology consistently failed to meet them there.
The shift that’s coming is the move from AI as a content tool to AI as a continuous thinking partner, and it’s closer than most people realize. This isn't something you open when you need a draft, but something embedded in how your organization operates every day: surfacing which major donor hasn’t been contacted in 90 days, flagging a campaign that’s underperforming before the window closes, alerting a new development associate to the full relationship history of a donor they’re about to call for the first time.
This is what agentic AI actually means in practice—not robots replacing fundraisers, but fundraisers who finally have a system that keeps up with them, handles the administrative weight of continuity and follow-through, and keeps the mission-critical relationships from slipping through the cracks when someone leaves or a quarter gets chaotic.
Under the hood, this shows up in simple but powerful ways. For example, a data agent can keep a fundraiser’s data foundation clean and usable, eliminating duplicate records, filling gaps and maintaining data without constant manual upkeep. A communications agent can add personalized notes to constituent records based on your meeting history and provide tailored follow-up communications, so no thank-you note is ever forgotten.
Knowing that AI can function as a thinking partner is the easy part. The harder question is: "How does my team actually get there?"
The answer starts with data. AI is only as good as the information it draws from. For a fundraising team, that means treating donor data as a living strategic asset that is consistently accurate and updated. When donor data is clean and unified, AI moves beyond reporting history to predicting what comes next. Organizations that neglect this step will find that even the most sophisticated tools generate incomplete or wrong answers.
There is also a cultural shift that must be driven by leadership. The teams that benefit most from AI are those where experimentation is normalized and staff understand the model clearly, which is that AI handles the administrative weight so humans can focus on the relational work that only they can do. That starts with two actions leadership should take: establishing a clear AI use policy with guardrails around data privacy, and reinforcing that AI is an amplifier for human judgment, not a replacement.
Many AI tools for nonprofits today allow a development team to ask plain-language questions of their donor data and receive strategic guidance immediately, which can completely change the way in which a team operates. And it’s a meaningful change. We've seen teams achieve up to 47% cumulative revenue growth and improve donor retention rates by focusing on the right tools that help them decide what matters and act with confidence.
But the path from one-off tool to embedded thinking partner doesn’t happen overnight. It starts with harnessing clean and reliable data, having honest policy conversations and having a willingness to let AI into the day-to-day rhythms of work.
The organizations that will reshape the industry moving forward aren’t necessarily the largest or the most tech-forward. I believe they’re the ones where someone is already asking better questions of their data and looking for a more systematic and informed way to operate. Those leaders exist everywhere in this sector. They’ve always been there. AI didn’t create their readiness, but it finally gives it somewhere to go.
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