Sooner or later, the question lands on a fundraiser’s desk. We are looking at an AI draft that pulls a detail the donor shared in confidence, and something makes us pause. Are we honoring this donor, or using what we know to handle them?
The question used to be easier to keep at arm’s length. We knew our donors well enough for an appeal to feel personal, but rarely well enough for the line between personal and manipulative to come up.
AI changes that. The AI reads giving histories, conversation notes, event attendance, email engagement, and the personal motivations that explain why each person gives. It assembles those dimensions into a portrait detailed enough to draft a letter that sounds like it came from a close friend.
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In Holding Fire: A Skeptic’s Framework for the Fundraiser with AI at Your Side, Stephen Christopher Nill, JD, lays out the Human-Centered AI Framework—his five-principles approach to keeping humans at the center of every donor interaction, even as AI quietly does the work no one fundraiser could ever do alone.
This book was written by a skeptic, for skeptics.
The depth of knowledge makes personalization possible. It also makes the ethics question unavoidable, and only the fundraiser can answer it.
The AI synthesizes all of this information into communications calibrated to each donor’s documented values and interests. The same capability that produces a deeply personal thank-you note can also produce a solicitation that pushes exactly the right emotional buttons at exactly the right moment. The choice between those two is ours.
One Test Forces a Pause at Every Decision
The test is simple to state and sometimes hard to apply: would the donor feel honored by this attention, or handled?
Consider a fictitious donor we’ll call Angela Torres. We know from her donor record that her sister runs a produce stand at the farmers’ market. Angela mentioned this during a casual conversation, and it was noted in her record because it helps us understand her connection to food-access issues. Now suppose the capital campaign is launching and early commitments are needed. Someone suggests using that detail to craft an appeal that connects Angela’s family story to the campaign ask.
The sentence would be accurate and personal, and it would use information Angela shared in a trusting moment to engineer a specific emotional response in a solicitation context.
Would Angela feel honored by the attention, or handled? If she knew we’d pulled that detail from a conversation note and woven it into a capital campaign ask to make the appeal feel more personal, would she think “they really understand me” or “they’re using what I told them to get more money out of me”?
The test won’t give a bright-line answer in every case, and that’s by design. It forces a pause at the moments when the line between personalization and manipulation gets blurry, and that pause is the whole point. A thank-you note that references Angela’s sister’s produce donations alongside her own giving honors two threads of the same family’s generosity. A capital campaign solicitation that deploys the same detail to manufacture urgency, by contrast, feels like handling.
This is also why every AI-generated communication requires human review. The AI doesn’t have an ethical compass. It will use whatever information is in the donor record to produce the most effective draft it can. Effective and ethical are not always the same thing, and recognizing the difference is human work.
The Human Center Holds the Line
The fundraising profession has a well-established ethical hierarchy that predates AI by decades and governs every decision. The donor’s interest always outranks the organization’s, which in turn always outranks the development professional’s personal interest.
When the AI prepares a briefing before a visit with a major gift prospect, the briefing should help us have a better conversation, one that’s more informed and more respectful of the donor’s time and interests. If we find ourselves using the briefing primarily to steer the conversation toward a specific ask amount, we’ve inverted the hierarchy. The briefing serves the relationship first and the solicitation second.
When a longtime donor mentions during a visit that a family member is ill and finances are tight this year, the hierarchy answers the question clearly. We express sincere concern. We do not make an ask, and we do not log the information as a timing signal for a solicitation six months from now. We respond as human beings, because we are human beings, and because the donor’s wellbeing is not a data point in pipeline management.
None of this is unique to AI-powered fundraising. Development professionals have navigated these questions since long before anyone had heard of ChatGPT. But AI changes the scale.
When we had 50 donors we knew personally, ethical intuition was usually sufficient. When the AI maintains detailed intelligence on 500 donors and can draft communications calibrated to each one’s documented values, the potential for well-intentioned boundary-crossing increases. The hierarchy gives us a scalable standard for ethical judgment.
The practical safeguard is an AI use policy adopted by the board, something I discuss in detail in my book. The policy covers what the AI does and what it doesn’t, how donor data is protected, the human review requirement for every communication, and disclosure practices for donors who ask. Having the policy in place before anyone asks demonstrates institutional integrity, and it gives the board a governance instrument rather than leaving ethics to individual judgment alone.
Donors, for their part, care about what their giving accomplishes and how respectfully and honestly they are treated by the people asking. A donor who receives a thank-you note that references a specific program interest and shares a concrete outcome is not going to investigate whether the first draft was written by a human or an AI. The donor will feel seen and connected to the mission.
A donor who asks how we knew about a specific interest and hears “I keep notes from our conversations so I can stay connected to what you care about” is going to appreciate the effort. The technology behind the relationship should be invisible to the donor, and it will be, as long as the human at the center of every decision applies ethical judgment that no technology can replicate.
Sometimes a draft just feels wrong. Maybe it pushes too hard, or it crosses the line from personalized to invasive in its use of donor information. We need to trust that feeling. The “honored or handled?” test is a practice, and it gets sharper the more we use it.
In my book, Holding Fire, I walk through the complete ethical approach, including the hierarchy, the disclosure question, data handling practices, and a sample AI use policy in the appendix. I also explore the deeper authenticity question, whether AI-powered fundraising can be honest in the way trusting relationships demand, and make the case that it can, precisely because the human remains at the center of every relationship.
Next week, I’ll close out this first series with the most practical post yet. Your first Monday morning with AI will be messy, and that’s exactly how it should be.
Stephen Christopher Nill, JD, founded CharityChannel in 1992, building it into one of the largest online communities of nonprofit-sector practitioners in the world. He has edited, designed, and published dozens of books for the nonprofit sector through CharityChannel Press. Over four decades, Stephen has built, administered, and advised fundraising programs in the United States and internationally that have raised billions of dollars. He has served as senior vice president of development at a hospital system, chief advancement officer at a West Coast university, director of development at a parochial school he helped to found, and founder and executive director of a charity that feeds the homeless in Southern California.
The Grant Professionals Association presented him with its first President’s Award. The Grant Professionals Certification Institute later honored him with the Pauline G. Annarino Award for foundational contributions to its existence. Stephen has been a frequent commentator on charitable giving for CNN, Fox News, MSNBC (now MS NOW), and other news shows.
He has provided training to attorneys on advanced charitable gift planning techniques on behalf of the State Bar of California’s continuing legal education program. As a lawyer and consultant, he advised hundreds of nonprofit organizations and educational institutions.
Stephen’s engagement with artificial intelligence reaches back to the 1970s, decades before the current wave. Holding Fire: A Skeptic’s Framework for the Fundraiser with AI at Your Side draws on that long history and on his career inside development offices.
He writes weekly to development professionals at charitychannel.com. These days he’s busy writing his first novel and composing symphonic music in his music studio.
