AI Fundraising Essentials: Demystifying AI for Nonprofits

Leadership

Dec 22

The conversation around artificial intelligence (AI) has shifted rapidly from speculation to practical application, and nowhere is this more true than in the nonprofit sector. For many organizations, AI is already proving itself to be a powerful tool for boosting efficiency, streamlining operations, and ultimately securing more funding.

Despite widespread interest (as of 2025, more than 85% of nonprofits are exploring AI usage), fewer than a quarter of organizations have adopted a formal AI implementation strategy.

To prevent risks associated with improper AI use and realize the promise of these powerful fundraising tools at your nonprofit, you’ll first need to establish a strong foundation of AI knowledge and governance.

Ready to face the challenge of AI fundraising head-on? Explore these essentials of effectively leveraging AI to fuel your nonprofit’s mission.

Know Your Tools: Predictive vs. Generative AI

Before adopting any AI solution, you should understand that "AI" is an umbrella term covering two distinct types of technology, both with specific roles in fundraising: predictive AI and generative AI. As DonorSearch’s AI fundraising guide points out, the most effective AI strategies involve both of these working in collaboration.

You can think of the difference this way: one type of AI is focused on analysis, and the other is focused on creation. Let’s dive deeper into each type.

Predictive AI

Predictive AI tools analyze vast amounts of historical data, recognize complex patterns, and generate forecasts or projections about future outcomes. In fundraising, they help you understand donors more deeply by identifying trends in wealth and philanthropic data that provide strategic prospecting insights. Predictive AI is designed to answer crucial strategic questions like: “Who is most likely to make a major gift?” or "When is the optimal time to reach out to a donor about giving again?"

Generative AI

Generative AI solutions take the information they are trained on and the specific prompts users give them to create original content. This content can range from email newsletters and social media posts to first drafts of grant proposals and thank-you notes. While it automates the early stages of creation, make sure to review and refine it so it aligns with your organization’s brand and target audience.

By clearly defining the capabilities of AI tools for nonprofits, your team can move past simple experimentation into a collaborative workflow. This collaboration frees up your staff’s time and energy to focus on more complex, human-centric tasks that cannot be replicated by algorithms.

Let Predictive AI Guide Your Strategy

A key benefit of AI for nonprofits is its ability to turn unstructured donor data into accurate, actionable insights. This is the domain of predictive AI, which should fuel your fundraising strategy.

A robust predictive platform allows you to make more strategic decisions about your fundraising pipeline that can maximize both efficiency and impact.

Predictive AI helps you:

Prioritize Prospects: AI can assess a prospective donor’s giving history, wealth markers, and non-profit affiliations to calculate their likelihood of making a major gift. This turns prospect identification into data-driven science, enabling your major gift officers to focus their limited time and resources on the most promising leads.
Refine Segmentation: Beyond identifying major donors, predictive AI helps with advanced segmentation. It can recognize subtle patterns that indicate when a mid-level donor might be ready to increase their gift, or which first-time donors are most likely to contribute on a recurring basis. This analysis ensures you are not wasting time on broad, generic outreach but rather targeting the right audiences with the right messages at the right times.
Optimize Channel Performance: AI models can analyze supporter behavior across different channels—from email open rates to how they engage with your nonprofit's website—to forecast which marketing method is most likely to succeed for a specific donor or segment.

Using these tools strategically means realizing that the AI shouldn’t be making final decisions for you, but rather providing a deeply informed recommendation alongside your team’s prior knowledge and organization-specific expertise.

Leverage Generative AI for Personalized Action

Once predictive AI provides the strategic blueprint, generative AI steps in to help you execute necessary outreach quickly and efficiently. The core goal of using generative AI is to level up your communications and create a more personalized supporter experience.

This technology is a significant resource for:

Drafting and Outlining: Generative AI is excellent for creating message templates, first drafts of appeal letters, or even initial talking points for introductory conversations with potential large-dollar donors. This saves time and money by automating initial content production, freeing up your team for higher-level strategic thinking.
A/B Testing and Refinement: Your team can use the AI to generate multiple versions of a subject line or email copy to see which one resonates most with supporters. Running this content through a refinement process with your internal experts ensures your messaging is tailored and on brand, leading to better results.
Targeted Personalization: When combined with the insights from predictive AI, generative tools can help you segment and personalize content to ensure that supporters are engaged effectively no matter where they are in their journey with your nonprofit.

While generative AI excels at tactical work, it lacks the deep, emotional connection to your mission that fuels effective donor stewardship. It should always be used as an outlining and brainstorming tool rather than a creator of a final product.

The Overarching Essential: Responsible AI and Human Oversight

Your nonprofit’s AI strategy isn’t complete without a formal commitment to responsible usage. While AI is essential for the future of fundraising, the human element (especially oversight) remains critical because the risks of improper AI use, such as data breaches, legal difficulties, or loss of supporter confidence, are all too real.

To minimize these risks and maximize the benefits of this technology, your organization must establish a clear AI usage policy. Key tenets include:

Data Security and Privacy: Implement security precautions like limited access permissions and regular system updates to protect sensitive donor information.
Inclusivity: Since AI models can perpetuate biases found in their training data, all outputs must be reviewed to ensure your communications are fair, equitable, and representative of your community.
Transparency and Trust: Be open with your board members, staff, and supporters about how your organization uses AI, particularly when processing their data. This deliberate communication is foundational for establishing and maintaining donor trust.
Legal Compliance and Risk Management: Stay current on all AI-related laws and regulations that apply to your nonprofit. This allows your nonprofit to navigate rapidly-evolving AI compliance standards, following the proactive risk management approach recommended by Jitasa.

When you incorporate ethical oversight and compliance into your strategic plan, you ensure that AI is supporting your mission without compromising your values.

By defining your goals, understanding the functions of AI, and committing to a culture of responsible usage, you’ll be ready to build an effective AI strategy for your nonprofit. This approach will allow your team to focus on what they do best: building meaningful relationships and advancing your mission.

Sarah Tedesco, Executive Vice President of DonorSearch

Sarah Tedesco is the Executive Vice President of DonorSearch, a prospect research and wealth screening company that focuses on proven philanthropy. Sarah is responsible for managing the production and customer support department concerning client contract fulfillment, increasing retention rate and customer satisfaction. She collaborates with other team members on a variety of issues including sales, marketing and product development ideas.