Transform AI Curiosity into an Active Fundraising Strategy

I wasn’t thinking about how to raise more money or connect with lapsed donors the first time I logged onto ChatGPT. I just wanted AI to generate a Harry Potter picture of my son. 

It was novel technology. I was curious. And AI delivered. 

The picture was so cool that I immediately saw the potential to use AI for strategic purposes at the nonprofit organization where I worked at the time. Very quickly, I went from dabbling in Harry Potter fan art for my son to real research for our team. 

My second-ever prompt: “Using data from our employee survey, help us identify gaps in our staff experience.” It was a good test: Could help make sense of raw information and reveal where improvements were needed? I removed identifying details, uploaded the survey information, and asked the tool to identify lead and lag indicators to guide next steps. AI surfaced patterns faster, organized concepts more clearly, and supported better decision-making than I could do on my own. 

When AI Becomes More Than an Experiment 

I moved quickly from curiosity about what AI tools could do in a personal, low-stakes way to wondering, “What else could AI help us do?” 

That question changed how I viewed AI’s role in our work. 

As nonprofit teams are asked to do more with less, many of us are looking to AI to close the gap by making insights easier to surface, decisions easier to support, and action easier to take, all while reaching more donors who may otherwise get no personalized contact. Wouldn’t we all like a boost in research capacity? Better strategies for donor retention? Real-time feedback on how our results compare to similar institutions?  

For me, AI became most useful when I stopped seeing it only as a tool and started treating it as a thought partner. AI does not replace human judgment, experience, or personal relationships. It does help bridge the divide that often exists between having good information and being able to act on it. 

One early AI use case I brought to the development committee at my last organization was to create a gift acceptance policy. It was time to retire my joke personal policy—”If I don’t have to feed it, I’ll accept it”—with formal documentation. I asked Claude to identify five peer institutions with gift acceptance policies and prompted it to draft a comparable policy for our organization. It was a simple redraft of existing materials that we could draw on easily with the help of AI and it provided proof to our board that AI could be a useful partner in our work. 

I should mention that I brought the first draft to our development committee for discussion and refinement, not for their rubber stamp of approval. The policy could not be completed without their feedback. Adopting new technology and processes always should include your stakeholders: board, volunteers, and staff. 

In the early days, I also learned that AI is only as useful as the data behind it. When I used AI to identify potential planned giving prospects in the database where I worked at the time, the initial results looked impressive. But as I reviewed the list, I noticed some names were the spouses of major donors, volunteers, or leaders who were being identified separately because of our database structure. The tool didn’t fail. It revealed a data issue we needed to address so that AI wouldn’t give us flawed results. 

That experience reinforced a principle every organization should remember: AI does not replace human review. It accelerates the work but we still have to bring judgment, context, and stewardship to the results. 

AI Helps Fundraisers See What’s Next

Today, I use AI most often to help our team stay strategically personal. Fundraising is relationship work. The value of AI is not in making that work less personal. The value is in helping us prepare better, follow up faster, and use the information we already have more thoughtfully. Here are two valuable “strategically personal” applications of AI that can make a difference for your fundraising team: 

• Pre-visit preparation: AI can summarize relevant donor history, highlight recent engagement, and suggest informed questions so fundraisers walk into meetings with clearer context.
• Post-visit documentation: AI can turn meeting notes into structured summaries that capture key themes, commitments, and readiness for solicitation.

Every fundraiser knows the challenge of getting contact reports completed while details are fresh. Using AI within our existing fundraising environment helps draft consistent notes tied to current constituent information and actionable next steps, which supports better follow-up and stronger accountability. 

AI has helped us think more clearly about prospect identification, lapsed donor outreach, and planned giving opportunities. It’s also useful for portfolio strategy. Let’s say a major gift officer is managing a 150-person list. Even a small increase in capacity can matter. Can time-saving AI tools make it possible for them to manage 160 people? Or 165? That’s a meaningful capacity increase, and it matters. 

It’s also worth naming the harder ceiling: Most organizations have far more donors who are open to a personal relationship than they have staff capacity. No amount of efficiency gets a single gift officer to a meaningful list of 1,000. The goal isn’t to overwork or replace the fundraiser. The capability of AI is to give that fundraiser more time for the relationships they carry, and the information to make that relationship more meaningful. 

Ready to Turn AI Curiosity in a Fundraising Plan? 

For organizations just getting started with AI, my advice is simple: Begin with the work you already do. Pick one recurring task that takes time, requires consistency, and benefits from better information. 

Here are a few action items that can help: 

• Start inside trusted systems. Use AI tools connected to your existing fundraising workflows and data protections whenever possible. 
• Pick one practical use case. Try pre-visit briefs, contact report drafts, lapsed donor lists, gift acknowledgment language, or planned giving indicators. 
• Clean up the data as you learn. Treat AI outputs as a way to identify where your data structure, coding, or records may need attention. 
• Keep humans in the loop. Review outputs carefully, especially when they relate to donors, prospects, or strategic decisions. 
• Bring leaders and volunteers along. Use a clear, low-risk example to show how AI can support the work and invite participation. 
• Build fluency gradually. Help staff learn how to ask better questions, evaluate responses, and use AI responsibly within daily work. 
• Focus on mission impact. Track where AI saves time, improves follow-up, strengthens donor engagement, or helps your team act with more confidence. 

Don’t think of AI as a tool to create shortcuts around the heart of fundraising. Instead, AI should make more space for the truly meaningful work you do. Used responsibly, with good data, clear guardrails, and human judgment, AI can help nonprofit teams become more focused, prepared, and confident in the work that matters most. 

To see how fundraisers are using AI strategically, check out the infographic, AI by Your Side: Make Every Workday More Productive for Major Gift Officers with AI in Blackbaud Raiser’s Edge NXT®.