If you’ve ever solicited major gifts for your nonprofit, you know that prospect research is critical for success. Whether you’re trying to bolster your annual fund or launch a capital campaign, prospect research allows you to pinpoint potential high-impact donors for these initiatives and develop data-driven strategies to cultivate and secure their support.

You might have also incorporated—or at least considered incorporating—artificial intelligence (AI) tools into various processes at your nonprofit, from creating marketing content to streamlining administrative work. AI can also enhance prospect research, allowing you to work smarter, not harder, at this critical activity.

In this guide, we’ll discuss how to strategically and responsibly incorporate AI into your nonprofit’s prospect research processes. But first, let’s look at the advantages of leveraging these tools.

Benefits of AI for Prospect Research

According to DonorSearch’s AI fundraising guide, using AI tools at your nonprofit (in prospecting and other activities) allows you to:

• Save time and money on otherwise resource-intensive processes.

• Automate mundane tasks so you can focus on more involved, human-centered aspects of fundraising.

• Personalize the supporter experience by simplifying segmentation and improving outreach targeting.

• Provide accurate, actionable insights to maximize fundraising effectiveness.

• Level up your marketing efforts by developing high-quality content that resonates with your audience.

• Tap into exciting new donation methods to boost donor engagement and help your organization grow.
• Measure your organization’s impact to assess progress over time and adjust your approach accordingly.

For prospect research, the benefits of automation and actionable insights are particularly important, as AI can help you find more qualified donors without the hassle of manual data entry and reporting. Plus, effective cultivation hinges on personalization, and your AI prospecting tools can set you up for success there as well.

Ways to Incorporate AI Into Donor Prospecting

Before you start using AI for prospect research, you first need to understand the difference between the two major types of AI tools for nonprofits: 

• Predictive AI solutions use machine learning to analyze trends and recognize patterns in data, allowing them to make predictions about future behavior.
• Generative AI solutions create content (text, visuals, audio, etc.) based on user prompts, which are also informed by the patterns these tools recognize in the data they’re trained on.

The best AI fundraising strategies involve both kinds of tools working together, so keep that in mind as you implement these tips.

1. Develop Predictive Models to Prioritize Prospect Lists

Have you ever created a list of prospective donors for a fundraising campaign, started contacting them, and hit dead end after dead end? And even when you finally find someone who is interested in contributing, you feel like you’ve wasted time and resources on outreach to everyone who didn’t want to give? 

Predictive modeling solutions are built to prevent this exact scenario. As you’ve likely realized, potential donors have to be able and willing to make a major gift to your nonprofit to be viable prospects. AI-powered predictive analytics tools can use your collected prospect research data to assess individuals’ giving likelihoods based on the following criteria:

• Capacity (wealth) indicators: Real estate ownership, stock holdings, business affiliations, political giving history

• Philanthropic indicators: Donation history (average gift size, frequency, recency, etc.) with your organization and other similar nonprofits
• Affinity (warmth) indicators: Passion for your mission, personal information (e.g., interests, values, or family ties), history of nonprofit involvement (e.g., volunteering, event attendance, board service, advocacy, and other non-monetary contributions)

Using this data, your predictive modeling tools will rate each candidate’s giving potential and prioritize your prospect list according to all three types of characteristics. This way, you can reach out to the prospects who are most able and willing to give first, boosting your success rates while saving time and money.

2. Generate Prospect Reports for Easy Reference

Personalization is essential for cultivating high-impact donors—not only in your communications themselves, but also in your overall strategy. To tailor your moves management process to each individual donor, you’ll need easy access to the most valuable information about them, which is where AI-driven prospect reporting comes in.

Prospect reporting tools use generative AI to summarize key data points on potential donors into actionable reports your team can use to guide your cultivation efforts. Make sure to update these reports regularly, especially before you request your first gift from a prospect. Major donor cultivation often takes several months, so it’s important to stay on top of any changes in their philanthropy or financial situation during that time to make your solicitations more effective.

3. Create Tailored Outreach Materials

More traditional generative AI tools (such as large language model chatbots) are also useful for cultivating prospect relationships, since they can help you develop tailored outreach materials. These can range from talking points to cover in your initial meeting with a prospect to email follow-ups or even LinkedIn messages.

When using generative AI for prospect outreach, always review and revise your tools’ outputs to ensure accuracy, align content with your nonprofit’s brand, and retain the human touch that’s critical to relationship-building. Also, reference your prospect research data (and integrate your AI tools if possible) to inform your materials.

A Note on Leveraging AI Responsibly

If you’ve experienced pushback or skepticism when trying to implement AI at your nonprofit, you aren’t alone. There are real risks associated with improper AI use—from data breaches to unintentional bias to legal noncompliance—so concerns around these tools aren’t unfounded.

However, your organization can minimize these risks and maximize the benefits of these solutions by committing to use AI responsibly. Create an AI policy at your organization that covers key considerations like:

• Data security. AI tools often process sensitive donor data, especially in prospecting, and protecting this information is critical for maintaining supporters’ trust in your nonprofit. Double the Donation recommends working with trusted AI providers, implementing access controls, and regularly updating your systems to increase data security.

• Inclusiveness. If AI tools are trained on biased data, these disparities can slip into your outputs and lead to unintentional discrimination. When reviewing AI outputs, have your team check that your results accurately reflect your organization’s constituent base and are free from bias.
• Transparency. Your community may have similar concerns to your internal stakeholders about your nonprofit’s AI use. Communicate clearly about what AI tools you use, what you do with them, and what precautions you have in place. This helps hold your team accountable and increase trust with current and potential supporters.

Additionally, remember that AI is meant to enhance prospecting, not take over the process. There are some aspects of fundraising (particularly relationship-building) that machines simply can’t do because a human touch is essential to them. Let your AI tools help with the behind-the-scenes work while keeping your team on the front lines of fundraising.

As you incorporate AI into your prospect research process, monitor your progress and collect feedback from your team so you can continually improve your efforts. If you have any questions along the way, don’t hesitate to reach out to your software providers or other AI fundraising experts who can help you make the most of these solutions.

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