The Meeting You Weren’t Ready For
You’re sitting across from a prospect, and you don’t have what you need.
You have a giving history to your organization. You have a wealth screening score; a capacity rating, a modeled estimate, maybe a giving likelihood number. But what you don’t have is the actual story: how this person built their wealth, what causes they’ve supported and to what extent, which boards they serve on, who in your network might know them, or what might connect them to your mission. So you’re reading the room, fishing for what they care about, and doing your best with less.
You’ve also — hopefully — had the opposite experience: you’re sitting down for a meeting, and you or your prospect research team have had the time to prepare a full, in-depth dossier — the kind of profile that changes a meeting. Good intelligence makes a massive difference.
The problem? There’s never enough time, and there’s too much data, to always have that good intelligence. A thorough write-up on a single prospect takes thirty minutes at minimum, and potentially hours. Cross-referencing public records, reading through news articles, tracing affiliations, checking giving histories. So you and your researchers triage. Your top ten prospects get the full treatment. The next hundred in your portfolio get a score and a best guess.
That’s starting to change. AI models can now do the data assembly, go out to the open web, find and read information across dozens of public sources, synthesize it into a coherent profile alongside data from proprietary sources, and cite every fact and figure back to where it came from. The output isn’t another score. It’s closer to what the best prospect researcher would hand you if they had unlimited time: whether their wealth is inherited or earned, what they’ve given elsewhere and whether any of it might align with your organization, who on your board might actually know them, or why they’d say yes to your mission in the first place. Sourced, verified, and ready before your meeting starts.
To be clear: AI does not replace the prospect researcher or the gift officer. The judgment a skilled researcher brings — the ability to look at a profile and really know what matters — is inherently human work. And no model is going to read the room, build the relationship, or know when to make the ask. What AI replaces is the bottleneck. It makes sure that when you sit down to prepare for a meeting, the intelligence is already assembled, already cited, and already current, so your time goes toward thinking and strategizing instead of gathering.
This is the move from scores to stories. And development teams that have made the shift are finding donors that others miss.
When You Know More, You Make Better Asks
The “speed of research” sounds like an operational detail, something for the back office to worry about. But for gift officers, it means better preparation on more prospects, and that translates directly into better conversations and better asks.
OutVote, a civic engagement organization, saw research time per donor drop by 87% after adopting AI-powered research tools (they tracked it; before, it took their team thirty minutes per prospect to generate a profile, and after, it took under a minute). That alone would be useful. But what mattered more was what the faster research uncovered. The platform revealed that a supporter who had been giving $2,500 actually had the capacity for a five-figure contribution. With verified, cited data on their giving history and wealth indicators, OutVote could approach that next conversation with confidence instead of guesswork. The donor’s capacity was always there. It just wasn’t visible at the speed the team was working.
Aspire Research Group, a prospect research firm, experienced the speed shift at a different scale. Their team needed to build a curated prospect list for a client focused on economic justice, but the organization had no mailing list, no board connections, and no existing donor network. A completely blank slate. Using AI-powered research, Aspire generated a targeted prospect pool and then used cited bios and contextual summaries to evaluate whether each prospect’s philanthropic priorities and policy positions aligned with the client’s mission. The disqualification turned out to be just as valuable as the discovery: when a prospect’s giving history or public positions didn’t match, the team could rule them out in minutes rather than spending days on manual review only to reach the same conclusion. They researched over 550 donors and delivered more than 400 fully vetted, high-quality prospects to their client. This meant that the principals receiving the list could walk into their first conversations already knowing whether the alignment was real and where the conversation should go.
Both of these stories illustrate the same principle. When the research is fast enough to be comprehensive at scale, you stop triaging which prospects deserve your attention and start evaluating all of them. You catch the $2,500 donor who should be a $25,000 donor. You build a list of 400 vetted prospects from scratch instead of settling for the 50 your team had time to research manually. The depth of your intelligence stops being limited by the hours in the day.
The Warm Introduction You Didn’t Know You Had
Ask any veteran gift officer what matters more — a prospect’s net worth or a warm introduction — and you’ll get the same answer. Relationships close gifts. The challenge is seeing the relationships that already exist in your network.
Rodman for Kids is a nonprofit serving over 100,000 children annually with a team of eight. Jessica Feenan, their Director of Development, was spending up to ten hours a week manually tracing connections and mapping networks. The question she was trying to answer is one every development shop deals with: which of our existing supporters, board members, and volunteers are connected to the people we’re trying to reach, and how? Who went to the same school? Who served on a board together? Whose kids are in the same community? These are the connections that turn a cold outreach into a warm introduction, and warm introductions are how major gifts actually happen.
When the team adopted AI-powered relationship mapping, they automatically surfaced over 3,000 connections across their network that they had no efficient way of seeing before. The team raised more than $2 million in the year that followed, but the bigger change was in how their team worked day to day. Instead of walking into meetings wondering who might know whom, they started every conversation with that context already in hand: here’s the connection, here’s the path, here’s how to open the door.
The Conversation This Data Also Opens
A note from the editor — Viken Mikaelian, PlannedGiving.com
There’s one conversation Will doesn’t mention—the one that often produces the largest gift of a donor’s lifetime.
The same intelligence that sharpens a major gift ask is exactly what opens a planned giving conversation. Age, estate indicators, long-term giving patterns, board affiliations, the arc of someone’s philanthropic life—that’s not just prospect research. That’s a legacy profile. The data is already pointing in that direction. The question is whether anyone is looking for it. And the gift officers who recognize it as such are the ones who eventually hear: I’d like to leave something behind.
Planned gifts aren’t a separate discipline. They’re what happens when a major gift relationship matures—and the gift officer was paying attention. The data Will describes gets you to the meeting. What you do with it determines whether that donor becomes a major donor—or a transformational one.
Scores Told You Who Could Give. Stories Tell You How to Close.
The pattern across all of these organizations is the same. When intelligence is cited, current, and contextual, gift officers work differently. They ask at the right level because they understand capacity and its context. They tailor the case because they know what the prospect cares about. They get the meeting in the first place because they can see who in their network can make the introduction.
For years, development teams have worked around the limitations of their prospect research and wealth screening tools, supplementing opaque scores with hours of manual research—or, more often, going into meetings with less information than they’d like. AI-powered research changes that equation. A cited, current profile built from the open web—a real story about who someone is—is a fundamentally stronger foundation for a gift conversation than a black-box score from a third-party database.
Gift officers have always known that the best meetings start with the best preparation. The difference now is that the preparation doesn’t have to take hours, and it doesn’t have to be limited to your top prospects. When every donor in your portfolio comes with a story instead of a score, you stop triaging who deserves your full attention and start giving every conversation the intelligence it deserves.
The tools have finally caught up to what gift officers have always needed. The only question is whether you’ll use them before your next meeting—or after it.
