AI & The Future of Fundraising
If your fundraising team is small, you know the trade-off: there are more donors to thank, follow-ups to make, and stories to tell than there are hours in the day. Meanwhile, larger organizations may have entire teams dedicated to researching prospects and personalizing campaigns.
AI is starting to change that balance. The right tools can help a lean team spot useful patterns, handle repetitive tasks, and focus its time on the people most ready for a meaningful conversation. You don’t need a huge technology budget, or an AI strategy that does everything at once, to get started.
The key is to use AI as a practical assistant, not a substitute for the trust and care at the heart of fundraising.
Why AI could give smaller nonprofits an edge
AI adoption is growing, but not every organization has the same resources. In Salesforce’s 2025 Nonprofit Trends Report, 55% of surveyed nonprofits said they were using or piloting AI, up from 12% the year before. Yet adoption was lower among small organizations: 28% reported using AI, compared with 66% of organizations with 100 or more staff.
That gap can feel like one more reason small nonprofits are behind. It can also leave room to learn from what’s working, and to choose focused, affordable uses that solve real problems.
AI doesn’t have to mean a complicated platform or a fully automated fundraising operation. For a small team, it might mean turning a spreadsheet into a useful donor segment, drafting a first version of a thank-you email, or reminding a staff member to follow up after a gift. Those small wins can add up.
1. Automate the routine parts of donor outreach
Some donor communications need a personal conversation. Others are predictable, time-sensitive touchpoints that are easy to put off when staff are busy. AI-assisted tools and simple automation can help you keep those moments from slipping through the cracks.
For example, you could set up a welcome sequence for new donors, a giving-anniversary note, or a reminder to thank a supporter after a campaign. AI can help draft and tailor messages to your organization’s voice; an automation tool can send them at the right time. Your team can then review the content and step in when a donor replies, makes a significant gift, or needs a more personal response.
A helpful rule of thumb: automate the prompt, not the relationship. Let technology flag a supporter who deserves a call, but have a real person make the call.
You can explore examples of this approach in our guide to stewardship automation.
2. Use donor behavior to decide where to focus
Your database may hold useful clues about what supporters care about: how often they give, which campaigns they respond to, whether they engage with your emails, and when they last heard from you. AI can help organize these signals into groups your team can act on.
For instance, you might create segments for:
- New donors who could use a warm welcome.
- Previously active donors who haven’t given recently.
- Monthly supporters who may need a check-in.
- Long-time supporters who could be ready for a deeper conversation.
- Donors who engage with a particular program or type of appeal.
The goal isn’t to treat a model’s score as a verdict. It’s to use data as a starting point: “Who might need attention?” or “Which group should we test this message with?” Your knowledge of your community still matters.
A small nonprofit doesn’t need perfect records to begin. Start with a few reliable fields (gift date, amount, campaign, contact preferences, and last outreach) and improve your data as you go.
3. Find insights hiding in your existing information
AI can also help answer practical questions that would otherwise take hours of manual sorting: Are donors lapsing after their first gift? Which supporter groups respond to a certain appeal? Are mid-level donors renewing at a different rate from smaller donors?
The American Journalism Project shared an example from Centro de Periodismo Investigativo (CPI), a nonprofit newsroom in Puerto Rico. CPI experimented with AI to review donor data, explore churn, compare email subscribers with donors, and improve fundraising messages. Its analysis found retention rates as high as 76% among major donors, while small-donor churn ranged from 34% to 45%. Those findings helped the team think differently about where personal cultivation and donor-upgrade campaigns could make a difference. Read the full account of CPI’s experiments.
The process also surfaced a useful warning: AI can misread data or produce incorrect information. CPI found that careful prompts and human verification mattered. So treat AI-generated analysis as a hypothesis to check, not an answer to accept without review.
4. Create more relevant campaigns without starting from scratch
Small teams often know what they want to say but don’t have time to create several versions for different audiences. AI can help you get from a blank page to a first draft faster. Give it context about your organization, your audience, and the campaign’s purpose, then review and edit the result before sending.
One example covered by the Chronicle of Philanthropy was Suncoast Humane Society’s AI-assisted campaign to reconnect with lapsed donors and people who had adopted pets. The campaign used stories about two animals and included direct mail, email, social media, and blog posts. By September, the organization had received 197 gifts from 194 donors, totaling nearly $37,000-above its $25,000 stretch goal. The team still revised the AI-generated content and noted that incomplete donor records made it harder to track some responses. You can read the case study and its lessons.
That’s a useful model: AI can speed up campaign preparation, while your team brings the real stories, judgment, and final approval.
5. Make careful tests before you scale
Some nonprofit case studies report strong gains from AI-assisted targeting, but results vary, and a single organization’s experience isn’t a guarantee. For example, Dataro’s case study of Scleroderma & Raynaud’s UK reports a 39% increase in net revenue for one appeal, alongside a 37% smaller mailing list and a higher response rate. The case describes a one-person fundraising team using donor predictions to focus its appeal. It’s an encouraging example of what a small team can test, not a promise of what every organization will achieve.
For your own pilot, choose one clear goal: re-engage lapsed donors, improve the new-donor welcome, or test a recurring-gift upgrade. Compare the results with a previous campaign or, when practical, a holdout group that doesn’t receive the new approach.
Track more than opens and clicks. Look at response rate, gifts received, net revenue, average gift, unsubscribes, and staff time saved. That last measure matters: a campaign that raises similar revenue with fewer hours may still be a worthwhile improvement.
Keep donor trust at the center
It’s reasonable to have questions about privacy, accuracy, and whether automated outreach will feel impersonal. These concerns aren’t a reason to avoid AI; they’re a reason to use it thoughtfully. In Salesforce’s 2025 report, data privacy and security were leading AI concerns among nonprofits, and a third cited a lack of internal skills.
Before using a tool, decide what donor information it can access. Don’t paste sensitive or identifiable donor records into consumer AI tools unless your organization has approved the tool and understands its data protections. Limit access to the people who need it, follow donor communication preferences, and have a staff member review donor-facing content. Make sure a person takes over when a supporter shares a personal story, asks a sensitive question, or warrants a one-to-one conversation.
A practical way to get started
You don’t need to change your whole fundraising program. Try this simple first-month plan:
- Choose one time-consuming task. For example, drafting thank-you emails or identifying donors who haven’t given in a year.
- Check the data you already have. Confirm that key fields are consistent and that contact preferences are recorded.
- Run a small, low-risk pilot. Use one audience and one message rather than changing every campaign at once.
- Review the results with your team. Look at both fundraising outcomes and time saved. Note what the tool got right, and what needed correction.
- Keep what works and adjust what doesn’t. Write down your process so you don’t have to learn the same lesson twice.
If you’re looking at tools to support donor insights and follow-up, see Donation Accelerator’s fundraising services and Donor Relationship Manager software.
Key takeaways
AI can help a small nonprofit make better use of limited time, not by replacing fundraisers, but by helping them prioritize, follow up, and learn from donor behavior. Start with one manageable task, check your data, protect donor privacy, and keep people involved in important decisions.
Your team brings the mission and relationships. AI can help make more room for both.
