Where AI Fits in the Major Gift Cycle

The first time I opened ChatGPT was November of 2022. The tool had just launched publicly, and I was curious the way most people were: what can this thing actually do? So I sat down and typed probably the worst prompt I've ever written. Something like: write an appeal letter for me.

What came back was exactly what you'd expect from a terrible prompt. Bland, generic, and at one point, comically incomplete, with placeholder text that said things like "insert organization name here" and "insert mission cause here." I remember thinking: that's not going to help anybody raise any money.

But instead of closing the tab, I kept going. What would happen if I gave it more context? I told it about the organization, the mission, the audience, the tone, the transformation I wanted readers to experience. The results got better. Not perfect, but better. It was a useful little experiment.

The problem was that appeal letters weren't my job. Major gift fundraising was. And major gift work isn't primarily about writing letters. It's about building relationships with donors, preparing for conversations, figuring out who deserves your attention in the first place, and thinking strategically about where each relationship might go next. Using ChatGPT to draft appeal copy didn't fit into any of that.

That's when I started asking a different question. Not: can this tool write things for me? But: where can this tool actually support the real work of major gift fundraising?

That question sent me down a path that's taken years to walk. Simple prompts, complex prompts, custom GPTs, small workflows for research and documentation and visit preparation. And over time, something real happened: these tools were freeing up hours every week. Hours I used to spend digging through data and organizing information behind my desk. Hours I could now spend meeting with donors, preparing more thoughtfully, and thinking more clearly about the relationships I was responsible for.

That's the idea behind the program I'm developing called the AI Advantage for Major Gifts, which I introduced last week. If you'd like to follow along as it takes shape, you can join the waitlist at letstalkfundraising.com/majorgifts. But today, I want to take a step back and look at the bigger picture: where, specifically, does AI fit into the major gift cycle?

Major Gift Fundraising Is Already a System

Before we can talk about where AI fits, it helps to be clear about what we're working with. Major gift fundraising isn't a collection of hunches and instincts, though intuition certainly plays a role. It's a system, built on best practices that have been developed and refined over the last thirty or forty years, codified through processes like the CFRE body of knowledge.

That system follows a recognizable cycle. It starts with prospect identification, where we're asking: who in our orbit has both the capacity and the inclination to make a major gift? From there, we move people into qualification, where we determine whether the interest is real and mutual. If it is, we enter cultivation, the long middle of the work, where we're building trust and deepening engagement, figuring out whether this person is ready to move toward an ask or still needs more time. Then comes the solicitation itself, and finally stewardship, where we deliver on the impact that gift made possible in a way that earns the next one.

This cycle exists because fundraising runs on systems. Without them, knowledge lives inside individual people instead of inside institutions. Without them, there's no consistency, no replicable model, no way for the sector to learn from itself. The system is what allows good major gift work to scale beyond any single person.

But here's the thing about systems: they require processes. And every stage of the major gift cycle generates its own administrative work. Research before a visit. Documentation after. Data analysis to identify who belongs in the pipeline. Portfolio reviews to figure out who's ready to move forward. That work is real and necessary, and it supports the relationship. It just isn't the relationship itself.

The Quiet Problem With Administrative Work

The administrative side of major gift fundraising has a way of quietly becoming the whole job. I've seen it happen. I've lived it. You spend half your week, sometimes more, sitting behind your desk working through data or organizing your notes or writing up contact reports, and before you know it, you haven't had a meaningful donor conversation in days.

That's not because the administrative work doesn't matter. It does. But it matters because it supports the relationship, and when it starts crowding out the relational work instead of enabling it, something has gone wrong with the system.

This is where AI enters the picture for me. Not as a replacement for the strategy, and not as the relationship manager. But as a quiet assistant that takes some of the friction out of the process so that more of your time and energy can go toward the work that actually moves things forward.

Where AI Fits, Stage by Stage

Prospect Identification

This is where the major gift cycle begins, and it's one of the most labor-intensive parts of the work. Early in my career, I took on a campaign at an organization with 150,000 members and no prior major gift program. We needed to identify who, from that enormous database, we should actually be talking to. It took me about two months of careful, manual analysis to narrow it down to roughly 300 qualified prospects. That campaign raised $4.2 million against a $3 million goal, which was remarkable for an organization that had been raising less than $200,000 a year.

But if AI had existed in that form back in 2012, that two-month process probably would have taken a week. Because AI is a genuinely exceptional pattern recognition tool. Feed it a large, well-organized dataset (I'd suggest a minimum of around 4,000 records for the analysis to be meaningful), and it can identify correlations and micro-trends that would take a human analyst far longer to surface. Who's opening emails. Who's responding. Who's showing up in ways that a traditional recency-frequency-monetary model would never flag.

You can also use AI to define and refine your ideal donor profile before the analysis begins. Give it your parameters, review its reasoning, and let it run. The key is that you stay in the loop. You're not handing the algorithm the final word; you're using it to get to a defensible starting point much faster. And you don't need to speak SQL or know how to build a scoring model from scratch. You need to understand the logic, confirm the output makes sense, and apply your judgment to what it's telling you.

Research and Visit Preparation

Before a qualification or discovery visit, I used to spend one to three hours on research. LinkedIn, board listings, news articles, whatever I could find to build a picture of who I was about to meet. That's time that had to come from somewhere, and it usually came from the evening before the visit or the early morning of.

With a well-crafted prompt, AI can compress that research into a few minutes. You can ask it to pull together what's publicly available on a person, synthesize it into a one-page professional brief, and flag anything that might be relevant to the conversation you're planning to have. The results aren't perfect, and you should always review what comes back for accuracy, but the time savings are significant. More importantly, the quality of your preparation improves because you're walking into the visit having actually read and thought about the brief, rather than still scrolling through LinkedIn in the parking lot.

Contact Reports and CRM Memory

The contact report is the institutional memory of the major gift relationship. If you leave an organization, or if a donor transitions to a new point of contact, what's in the CRM is what carries the relationship forward. But most of us know what contact reports actually look like in practice: delayed, abbreviated, scattered across sticky notes and iPhone memos, written at the end of the week when the details are already fading.

The gap between what fundraisers know they should be documenting and what they actually document is one of the most consistent sources of lost institutional knowledge in our field. AI can close that gap in a way that fits how we actually work.

The solution I've built for myself is a custom GPT set up to take voice input. Right after a donor visit, before I even start the car, I'll pull it up and do a full brain dump in voice mode. Everything I can remember, in whatever order it comes out, as messy and unpolished as it needs to be. The AI takes that and structures it into a clean, consistent contact report that goes into the CRM. No delay. No fog of memory. No sticky notes.

If you're working on a team, this matters well beyond your own record-keeping. Consistent contact reports mean your prospect research colleagues have something useful to work with. Your supervisor can actually understand what's happening in your portfolio. The institutional memory is real, not theoretical, and it doesn't disappear when someone leaves.

Portfolio Strategy and Strategic Thinking

This one is subtler, but it might be the most valuable application over time. AI can function as a genuine thinking partner in the strategic decisions we make about our portfolios.

When I'm trying to figure out the next move with a donor, I'll sometimes walk AI through the relationship history and ask it to reflect back what it's seeing, suggest alternatives I might not have considered, or help me think through the timing of an ask. It can't replace my judgment, and it certainly can't replace the intuitive sense you build over years of doing this work. But it can function something like the bumpers at a bowling alley: it won't guarantee a strike, but it can keep you from rolling a gutter ball.

AI can also help you look across your portfolio with a wider lens. Which relationships have stalled? Who might be showing signals that they're ready to move forward? Where are you spending time that isn't moving anything forward? That kind of pattern recognition, applied to your own work, can surface things that are easy to miss when you're inside the day-to-day of managing a full caseload.

What AI Is Not

I want to be direct here, because there's a version of this conversation that goes sideways if we're not careful.

AI is not the strategy. The major gift strategy, the one built on decades of best practice and tested in real campaigns with real donors, is still the strategy. AI supports that work. It doesn't replace it.

AI is also not a relationship manager. The donor relationship is still human, and it should remain human. The context, the intuition, the years of built trust that inform how you read a conversation and what you do with that reading: those things aren't in the model. Technology should serve people, not the other way around.

And there are real ethical responsibilities that come with using AI in this work. Be thoughtful about what you upload. Personally identifiable information about your donors has no business going into a public AI system. What you share with these tools should be something you'd be comfortable seeing in the world, because data breaches happen, and the professional responsibility you carry for your donors' information doesn't disappear when you're using a new tool. This isn't a reason to avoid AI. It's a reason to use it carefully, with the same judgment you'd apply to any part of the work.

What Becomes Possible

When I look at the major gift cycle now, I don't see AI as a disruption to what works. I see it as something that allows what works to run more smoothly. The prospect identification process that took two months can happen in a week. The visit preparation that required an evening can happen in fifteen minutes. The contact report that you've been meaning to write since Tuesday gets done before you leave the parking lot.

That recovered time doesn't disappear. It flows back into the work that matters most. More visits. Better preparation. Deeper conversations. Relationships that get the best of you, not what's left after a week spent behind a desk.

And I think that makes the work more sustainable, too. Not just more productive, but more sustainable, in the sense that you're doing the part of this job that drew you to it in the first place. The relationships. The mission. The conversations that matter.

If there's one idea I hope you carry from this episode, it's this: AI doesn't change what major gift fundraising is, but it can strengthen the systems that allow that work to happen. Every stage of the cycle, from prospect identification to stewardship, depends on processes. And when those processes are slow or fragmented or overly manual, the administrative work quietly crowds out the relational work. When those systems are clear and supported, something shifts. You spend less time managing information and more time being present with the people you're trying to serve.

That's the idea behind the AI Advantage for Major Gifts program I'm developing. If this conversation sparked something for you, I'd love to have you join the waitlist at letstalkfundraising.com/majorgifts. The people who join will be the first to hear when it opens, and the founding cohort will have a hand in shaping the structure of the program itself. Because the goal isn't another training course. The goal is to help you reclaim the time and energy to do what matters most: the relationships.