Every fundraiser knows the sinking feeling. A loyal donor gave two weeks ago and still hasn’t heard from anyone beyond an automated receipt. A major gift prospect’s visit is Thursday, and the preparation hasn’t started. A lapsed couple quietly drifted away months ago, and nobody noticed. When the portfolio holds dozens or hundreds of relationships, the most important details are the ones most likely to slip through the cracks.
A relationship-building system with integrated AI changes that equation by scanning every donor record each week and flagging the situations that need attention. It drafts communications grounded in the actual giving history, engagement patterns, and conversation notes in each file. In 20 minutes, every relationship that needs a touch has gotten one.
But the system’s output is only the starting point. We human fund development professionals decide which draft to send, which sentence to rewrite, which relationship to prioritize, and which recommendation to override. AI handles the scanning and drafting, and we handle the judgment and the relationships.
Now Available
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.
That tension between the machine’s preparation and the human’s discernment runs through every Monday morning review, and this week I want to walk through what it looks like in practice.
How the Briefing Puts the Workflow in Action
The Monday morning review starts the same way every week. Open the donor system and ask the AI to review the portfolio and flag what needs attention. It reads through every donor record, cross-references giving histories with engagement signals and contact logs, and presents a prioritized briefing.
The framework’s second element, the workflow, is the engine underneath this rhythm. The cycle repeats every week. AI scans, AI drafts, we review, we decide, we act, we update the record.
Some weeks the briefing flags eight or 10 items, and some weeks only three. The volume depends on where we are in the fundraising cycle. Year-end campaigns generate more activity than midsummer quiet periods. But the structure stays consistent. Every Monday, the rhythm is the same. Review the briefing, make decisions, edit drafts, update files. Twenty minutes later, every relationship that needed attention has gotten it.
Let’s look at a Monday morning where the briefing flags four donors, each at a different stage:
- A fictitious donor we’ll call Angela Torres gave $50 to the after-school nutrition program two weeks ago. She designated a specific program, which tells us something about her motivation, but she hasn’t heard from the organization since the automated receipt. The AI has drafted a warm welcome email connecting her gift to program outcomes, covering 22 kids in cooking classes last month, every one of them taking recipes home to make with their families. You read the draft, adjust one sentence, and send it. That’s touch one of seven in her first-year stewardship sequence.
- A fictitious donor we’ll call David Park has given every year for six consecutive years, always between $200 and $300. He attends the annual dinner. He opens every email. He has never received a personal phone call or a note beyond the standard acknowledgment letter. The AI flags him as a loyalty standout and recommends a personal conversation comprising a sincere thank-you and a chance to learn why he gives.
- A fictitious donor we’ll call Dr. Sarah Huang is a major gift prospect whose Thursday visit needs preparation. The AI has assembled a giving history, the themes from the last three conversations, a suggested approach for deepening the discussion, and a recommendation about pacing.
- A fictitious couple we’ll call James and Patricia Whitfield gave $1,000 just over a year ago and haven’t given since, but they attended the spring event, opened every newsletter this fall, and Patricia commented on a recent social media post. The AI has drafted a reengagement letter that leads with impact rather than a solicitation.
Four situations, four tailored approaches, and the AI drafted communications for each one, drawn from the actual donor records. The AI did the scanning and the drafting. The fundraiser spent 20 minutes deciding what to send, what to edit, and which relationship move to make next.
The framework’s first element, the healthy division of labor, is the principle underneath all of it. AI handles synthesis, pattern recognition, and drafting. We handle the human part: relationships, judgment, and every strategic call about timing and approach.
From Segments to Individuals
Most of us in fundraising have used segmentation. New donors get a welcome track. Lapsed donors get a reengagement track. Major gift prospects get personal attention. Everyone else gets the annual appeal. Segmentation was a massive improvement over sending the same letter to everyone.
But segmentation treats donors as members of categories rather than as individuals. Angela Torres and another new donor who gave $500 to a different program and has a daughter on the board both end up in the “new donor” bucket and receive the same welcome sequence. The Whitfields get the same reengagement letter as someone who made a single small gift three years ago and has shown zero engagement since.
The Monday morning review changes that equation through the framework’s fourth element, the scale shift. The kind of thoughtful, personally informed fundraising that used to be reserved for a handful of top prospects now extends deeper into the donor base. Angela gets a welcome email tailored to the after-school nutrition program she chose. David gets a phone call informed by six years of giving history. Dr. Huang gets a multi-section briefing synthesizing months of relationship intelligence. The same quality of preparation reaches every donor at every level, because AI handles the production work so we can do the relationship work.
The 20-Minute Habit That Compounds
The best drafts came from the richest records.
Angela’s welcome email mentioned cooking classes because someone noted her program designation when the gift came in. David’s briefing was specific and actionable because someone had been logging notes from events and conversations over six years. Dr. Huang’s file captured the conversations from three previous meetings, allowing her pre-visit preparation to synthesize their themes.
Every time we edit a draft and update a donor’s record with what we learned, the system gets smarter. A letter generator gives us the same output on day one and day 300. The Monday morning review produces output that gets more personal, more accurate, and more strategically useful the longer we use it. The framework calls this the virtuous data cycle, and it’s the reason this approach is different in kind from a one-time AI tool.
The stakes are worth the discipline. Acquiring a new donor costs roughly six times more than retaining an existing one. The Fundraising Effectiveness Project reported an overall donor retention rate of just 42.9 percent for 2024, and Dataro’s analysis of over 300 nonprofits found that roughly 70 percent of newly acquired donors never make a second gift. The Monday morning review is the discipline that keeps existing donors from slipping through the cracks.
One more framework element runs through all of this: permanent ethical vigilance. When the AI assembles Dr. Huang’s briefing and suggests an approach for Thursday’s visit, the fundraiser is the one who decides whether the recommendation serves her philanthropic goals or the organization’s revenue target. When the system flags David Park as a candidate for an upgrade conversation, we’re the ones who decide that this week’s call is about gratitude rather than solicitation. AI can personalize, and it can manipulate. The human at the center of the framework is what keeps the difference clear.
The Monday morning review takes 20 minutes every week. It touches every donor who needs attention and catches the ones quietly slipping away. It’s the framework in practice, with AI handling the scanning and drafting, we humans handling the judgment and the relationships, and the whole system getting smarter with every pass.
In my book, Holding Fire, I walk through these four donor relationships in full detail. I cover Angela’s first 90 days, David’s transformation from overlooked loyalist to engaged partner, Dr. Huang’s multi-month major gift process, and the Whitfields’ reengagement. Each one demonstrates how the framework turns 20 minutes of discipline into relationships that last.
Next week, I’ll dig into the information most donor databases are missing, and why that gap outweighs the data we already have.
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.