Prospect Research for Nonprofits: Turning “Maybes” into Gifts with AI

A donor checks a box on your survey saying they’re interested in learning more. Is that a future major gift, a planned gift, or simply someone who wants to stay informed?

You don’t have to guess, or ask your team to research every response by hand. AI can help you sort survey responses, connect them with relevant donor records and public information, and decide who might benefit from a personal follow-up. The goal isn’t to predict exactly who’ll give. It’s to help you spend your time thoughtfully and make your next conversation more relevant.

Start with the survey, not a wealth score

A survey gives donors a chance to tell you what matters to them. That’s valuable because financial capacity alone doesn’t tell you whether someone feels connected to your mission or wants to hear from you.

Keep your questions simple and optional. You might ask:

• Which part of our mission matters most to you?
• How would you prefer to support us: volunteering, annual giving, recurring gifts, a major gift, or a planned gift?
• What outcomes would you like to see from your support?
• How would you like us to follow up, and how often?
• Would you like to learn more about ways to support our work in the future?

Include “I’m not sure yet” and “Prefer not to say.” Those options make the survey more welcoming and help you avoid treating a non-answer as a lack of interest.

If you’re asking about planned giving, make the next step clear and low-pressure: “Would you like information about including our organization in your plans?” A “yes” is permission to offer information, not proof that someone has made a decision.

Let AI organize the clues

Once responses come in, AI can help your team bring together information that may be scattered across survey forms, event records, giving history, and your CRM. It can summarize open-ended answers, flag likely duplicates, group similar interests, and surface records that may need a closer look.

For instance, a donor might mention in a survey that youth education is a priority. Your CRM may show that they’ve attended your education program’s events and made several gifts over time. AI could highlight those details together so a fundraiser can decide whether a personal update about that program would be useful.

AI can also help summarize publicly available information that your organization has a legitimate reason to review, such as a donor’s publicly documented foundation involvement or philanthropic activity. Ask your vendor where information comes from, and require source links so staff can check the evidence. Avoid treating a model-generated summary as verified fact.

Prioritize with four separate signals

Rather than letting one number define a person, organize what you know into distinct signals. You can use a simple low, medium, or high rating to help staff review records, without suggesting that a score predicts a gift.

1. Capacity: Are there credible, relevant public indicators that someone may be able to make a larger gift? Treat these as clues, not a precise estimate of wealth.
2. Philanthropic propensity: Has the person supported your organization or similar causes? Look at documented giving and nonprofit involvement, where appropriate.
3. Affinity: Have they expressed a connection to your mission through survey answers, volunteering, event participation, or public statements?
4. Readiness and preferences: Did they ask for follow-up? Do you know what they want to hear about, and how they prefer to be contacted?

This distinction matters. A person may have the capacity to make a significant gift but no interest in your cause. Another may be deeply committed to your mission but not in a position to give more. Good prospect research helps you respond to the person, not just the profile.

Industry guidance from AFP Global distinguishes wealth screening from the fuller work of prospect research. For your team, the practical takeaway is simple: use AI to surface possibilities, then apply human judgment and relationship knowledge.

Use sentiment as a listening tool

AI can help identify themes in survey comments, such as enthusiasm about a program, uncertainty about how donations are used, or frustration with how often someone hears from you. That can help your team respond to what people are actually saying.

But sentiment analysis is imperfect. Sarcasm, cultural differences, short answers, and context can all trip it up. A label like “positive” or “concerned” is a prompt for a human to read the response, not a reliable measure of someone’s willingness to give.

Try this practical approach:

• Pick a small set of themes tied to your mission, such as impact, trust, communication preferences, or interest in planned giving.
• Ask AI to group comments by theme and summarize patterns.
• Have a staff member review a sample of the original responses and check whether the summaries make sense.
• Keep sensitive comments private, and don’t use inferred emotions to pressure someone into giving.

For example, if several donors say they want clearer updates on program outcomes, the best next step may be a useful impact report, not a donation request.

Turn a promising signal into a thoughtful next step

Imagine your organization receives 150 survey responses. A few donors ask about long-term giving. Others name a program they care about, and some simply want fewer emails. AI can help organize those responses and connect them to existing records. Your team can then review the most relevant details and choose an appropriate follow-up.

A simple process looks like this:

1. Check the record. Confirm the survey response belongs to the right person and that the CRM information is current.
2. Review the evidence. Look at the donor’s stated interests and history first. If you use public information, verify it and note its source.
3. Choose a useful next step. Offer the information the donor asked for, share an update about a program they care about, or invite them to a conversation.
4. Let the donor set the pace. Respect their contact preferences, and make it easy to decline or opt out.
5. Record what happens. Update the CRM so the next interaction builds on the relationship instead of starting over.

AI can help draft or personalize messages, but a person should review them. A warm note referencing a donor’s stated interest can feel personal. A message that reveals you’ve inferred their wealth or mined unrelated personal details can feel intrusive.

Tools like virtual fundraiser chatbots can offer donors a convenient way to get answers when staff aren’t available. They work best as an accessible front door, not a replacement for a real relationship or a way to push someone toward a gift they haven’t expressed interest in.

Build in privacy and human review

Prospect research involves personal information, so your process should be transparent and careful. Tell donors how you use their information, collect only what you need, limit access to donor records, and give people a clear way to update their preferences. Check your privacy policy, applicable laws, and vendor agreements before using new tools.

Don’t ask AI to infer sensitive traits or make decisions about who deserves attention. Don’t rely on a score to exclude someone from outreach or determine the size of an ask. Keep a human involved in decisions that affect a donor relationship, and let donors correct inaccurate information. APRA’s ethics and compliance resources offer a useful starting point for building responsible research practices.

Transparency matters to donors, too. In a Fidelity Charitable study, most surveyed donors said transparency about nonprofits’ use of AI was important. A plain-language explanation of where AI helps, and where a person makes the decision, can help maintain trust.

Make your first AI prospecting project small

You don’t need to automate your entire fundraising operation to get started. Pick one recent survey and a manageable group of responses. Ask AI to summarize themes, organize donor-stated interests, and flag records for human review. Compare its suggestions with what your fundraisers already know.

Then measure practical outcomes: Did your team find relevant follow-ups faster? Did donors respond positively? Did the process uncover inaccurate records or unwanted contact? Use what you learn to improve your questions and workflow before expanding.

That’s the real promise of AI prospect research: not turning every “maybe” into a gift, but helping your team notice promising signals, listen more closely, and take the right next step. Donation Accelerator’s fundraising services include planned giving surveys and automated donor engagement designed to help nonprofits uncover opportunities without adding more manual work.