By Bill Tedesco, CEO & Managing Partner, DonorSearch

Artificial intelligence (AI) is quickly becoming more prevalent in the nonprofit sector. As of September 2024, 58% of nonprofits leverage AI tools in their marketing efforts, and 68% use AI to analyze constituent data. This push for innovation exceeds for-profit implementation, as only 47% of business-to-consumer (B2C) companies have integrated AI into their communications, and 64% have incorporated it into customer analysis.

The two functions analyzed in the study above require different types of tools. If your nonprofit uses (or wants to use) AI for communications, you’ll leverage generative AI solutions. If your goal is to understand your supporters more deeply, predictive AI is your best bet.

However, the most effective AI fundraising strategies involve both types of tools working together. In this guide, we’ll dive deeper into the unique functions and benefits of generative and predictive AI before discussing how to use them in conjunction. Let’s get started!

Generative AI

Generative AI uses its intelligent pattern recognition and analysis capabilities to create original content. These solutions are “trained” by inputting large amounts of data. Then, when you enter a prompt into the tool, it generates an output of text, images, audio, or video.

Benefits

Using generative AI effectively will provide the following advantages for your nonprofit:

  • More consistent branding across channels in both visuals and messaging.
  • Easier content personalization to show donors you appreciate their individual support.
  • Increased innovation capabilities that allow you to try new marketing approaches or fundraising methods.
  • Improved accessibility since AI can create closed captions for videos, suggest alternative text for images, and take other steps to help all audiences gain value from your content.

Use Cases

Your nonprofit can leverage generative AI for a wide range of content creation purposes, including:A list of five nonprofit use cases for generative AI, which are discussed below.

  • Multi-channel marketing. As Getting Attention’s nonprofit marketing guide explains, this marketing approach allows you to connect with as many supporters as possible, but it’s time-consuming to create high-quality, consistent content across various platforms. Using generative AI can streamline this process and spread awareness of your mission.
  • Prospect reporting. AI-generated prospect reports summarize key information about individual potential donors to provide your major and planned gift officers with actionable insights for relationship-building.
  • Donor cultivation. Once you start the relationship-building process, you can use generative AI to develop educational resources and draft messages to keep prospects informed about your organization.
  • Fundraising appeals. Whether you’re soliciting a gift via email, direct mail, or a face-to-face meeting, AI will help you craft asks that resonate with your audience.
  • Donor stewardship. After a donor gives, you can also save time on choosing stewardship methods and writing thank-you messages with generative AI.

In all of these cases, generative AI should supplement human content creation, not replace it. Evaluate and revise your AI tools’ outputs to ensure they’re accurate, aligned with your nonprofit’s writing style, and tailored to your audience.

Predictive AI

At its base level, predictive AI analyzes data and creates models based on this analysis. Since these tools are also trained to recognize patterns, they can project future trends and make suggestions based on past data.

Benefits

The main benefits of predictive AI for nonprofits like yours include:

  • Informed decision-making capabilities for key processes like strategic planning and major donor outreach.
  • Optimized donor cultivation based on your AI tools’ recommendations for the best ways to engage specific prospects.
  • More effective fundraising asks that don’t request too much of your donors or leave money on the table.
  • Efficient resource allocation through suggestions for optimizing your team’s time and your organization’s funds when engaging donors.

Use Cases

Since predictive AI is most useful for constituent data analysis, here are some ways your nonprofit can leverage it effectively:

A list of three nonprofit use cases for predictive AI, which are discussed below
  • Donor prospect modeling. Standard prospect research only provides a general sense of donors’ giving capacity, affinity for your mission, and philanthropic tendencies. Predictive AI models go a step further by rating how likely a prospect is to give to your organization based on these factors so you can prioritize outreach to the highest-ranked candidates.
  • Engagement analytics. By showing you how supporters have responded to different types of outreach and fundraising appeals in the past, predictive AI can help you capitalize on your donor engagement strengths and improve where necessary.
  • Sector-specific fundraising needs. According to DonorSearch, “AI-supported analytics can especially help organizations in niche sectors like healthcare and higher education model their unique data and inform their strategies.”

Like with generative AI, predictive AI should enhance your organization’s decision-making rather than making decisions for you. Always maintain human oversight when using these tools and treat their outputs as one of several key factors that inform your nonprofit’s strategies.

How do generative & predictive AI work together in fundraising?

The short answer to this question is that predictive AI informs your nonprofit’s fundraising efforts, and generative AI helps you execute your strategy.

To help you understand this relationship more deeply, here is an example of the process a university might use to cultivate a relationship with a major donor, leveraging both generative and predictive AI tools along the way:

  1. The university’s major giving team conducts prospect research as usual. Once they’ve screened several potential donors, they use a predictive modeling tool to prioritize their prospects based on giving likelihood and an AI-powered prospect generator tool to create reports for their top prospects.
  2. A gift officer then schedules a one-on-one meeting with the highest-priority prospect on the list. Since the predictive models showed that the prospect responds well to emails, the officer uses an AI content generation tool to draft an email requesting the meeting and produce a meeting agenda with relevant talking points and questions.
  3. After the meeting, the prospect seems interested in the university, and they express a passion for the arts that’s also reflected in their prospect report. So, the gift officer continues using the content generation tool to draft weekly follow-up emails to the prospect over the next few months. Some of these emails include resources about the university’s visual and performing arts programs, while others introduce key players in those departments that the prospect communicates with to learn more.
  4. The gift officer generates a personalized invitation to a performance and behind-the-scenes tour of the university’s spring musical to give the prospect an inside look at the arts program. The prospect had talked at length about their children in the initial meeting, one of whom is involved in her high school drama program, so the officer invites the prospect to bring their daughter along.
  5. After seeing the musical, the prospect seems almost ready to give. The gift officer starts preparing the donation request, revisiting their predictive modeling tools to determine the right amount to ask for. Since the prospect has given to foundations in the past (and foundation giving is growing in popularity, according to Giving USA 2024), the gift officer lists donor-advised funds (DAFs) as a giving option to suggest. The upward trajectory in corporate giving that Giving USA also reported prompts the gift officer to research the prospect’s employer’s matching gift program and make a note about it in the request.
  6. The gift officer formats the request into a presentation using generative AI and delivers it to the prospect. The prospect responds well, and they work out a payment plan for a major gift to support the renovation of the student practice rooms and dance studios in the performing arts building.
  7. The donor’s prospect report shows that they’ve previously been recognized for their charitable gifts at donor appreciation events and in annual reports. So, the university generates an invitation for the donor to their next appreciation dinner and collaborates with them on a “Featured Donor” spot for its annual report to effectively steward them.

Of course, the exact ways generative and predictive AI affect your donor cultivation processes will vary depending on your nonprofit’s mission, prospecting results, and donor responses. With that in mind, this example will hopefully get you thinking about how you can integrate these tools into your efforts for more efficient and effective fundraising.