| TL;DR: AI can’t fix bad data. Garbage in, garbage out still applies. Your donor data is a story your supporters are telling you. Listen to it. Data security and governance need to be elevated to board-level conversations. The best AI tools for nonprofits are the ones that create efficiency, not complexity. Before adopting any AI tool, ask yourself: What do I actually want this to do? |
There’s a lot of hype around AI right now. And if you’re a fundraiser trying to figure out what’s real and what’s noise, you’re not alone.
In a recent episode of The Responsive Lab, our host, Scott, had an honest conversation with Clay Buck, founder of Next River Fundraising Strategies, about what AI actually changes when it comes to nonprofit data. Clay has been in fundraising for nearly 30 years, working everything from database administration to chief development officer roles. He’s seen technology revolutions come and go. And his perspective on AI and nonprofit data is both grounded and refreshing.
We covered a lot of territory in this conversation, including:
- Why data quality matters more than ever
- How to think about data as an asset
- And what fundraisers should consider before jumping into any new AI tool.
Below, we’ve pulled out the key insights and expanded on them to help you think through AI and your nonprofit’s data strategy.
(Or you can also just check out the video here!)
AI Doesn’t Change the Fundamentals of Nonprofit Data
Let’s start with the big picture.
When asked what AI actually changes about nonprofit data, Clay’s answer was direct: “It both changes everythingand changes nothing.”
Here’s what he meant. AI is a powerful tool for analysis, trend identification, and even prediction. But it’s still completely dependent on the quality of the data you feed it. If your data is messy, inconsistent, or incomplete, AI won’t magically fix that. It will just amplify the problem.
As Clay put it in the podcast, “Garbage in, garbage out is still one hundred percent true.”
This isn’t a new challenge for fundraisers. But it’s become more urgent. If you’re planning to use AI for segmentation, donor analysis, or predictive modeling, for example…your data needs to be clean, accurate, and well-organized. Otherwise, you’re building on a shaky foundation.
What This Means for Your Team
Before you invest in any AI tool, take a hard look at your data. Ask yourself:
- Do we have consistent naming conventions and source codes across years of giving history?
- Can we confidently trace a donor’s journey over time?
- Is our data well-documented, or do we rely on institutional knowledge that’s left when staff turns over?
If you can’t answer yes to these questions, AI won’t solve your problems. In fact, it might create new ones.
Your Donor Data Is a Story. Are You Listening?
One of the most thoughtful moments in the podcast came when Clay reframed how we should think about donor data.
“Any information that a donor provides us is the story they’re telling us,” he said.
Think about it. When a donor gives you their full name, spouse’s name, email, phone number, and home address, they’re signaling something. They want to be known. They want to hear from you. They’re inviting you into a relationship.
On the other hand, when a donor gives you the bare minimum, that’s information too. Maybe they’re not ready to commit. Maybe they want to stay at arm’s length for now. Either way, the data they share is telling you something about their level of trust and engagement.
Trust Is the Foundation
This connects to a bigger theme Clay raised: trust.
Trust sits underneath every data decision a nonprofit makes. According to the 2026 Edelman Trust Barometer, nonprofits, measured globally as NGOs, are trusted by 58 percent of the public, placing them ahead of government and media but behind business. [1]
That relative trust matters, but it is not guaranteed. The same report shows trust is increasingly personal and local, with people placing more confidence in organizations they feel close to and understood by.
So, when a donor gives you their personal information, including their name, contact details, and credit card number, they’re trusting you to protect it. They’re trusting you to use it responsibly. And they’re expecting something in return: personalization.
As Clay noted, personalization isn’t a nice-to-have anymore. It’s a must-have. Donors expect you to know who they are. If you send something without their name on it, they notice. And that erodes trust.
So before you think about what AI can do with your nonprofit data, think about what your donors are trusting you to do with it. That trust is the foundation everything else is built on.
Elevate Data to a Board-Level Conversation
Here’s something that might feel uncomfortable: your data needs governance.
Clay has worked with several organizations to establish data oversight committees at the board level. This isn’t just about compliance. It’s about treating data as what it truly is: a strategic asset.
“We need to start valuing data as an asset at the same level we would any other asset,” Clay explained. “Our buildings, our technology, our people, anything that we consider an asset, data needs to be at that same level.”
This is especially true in a world where AI tools are becoming more common. Who is responsible for your data? Who decides how it’s used? Who ensures it’s secure?
If you don’t have clear answers to these questions, now is the time to start that conversation. And it should happen at the highest levels of your organization, not just in your development department.
A Practical Starting Point
If your organization isn’t ready for a full data committee, start smaller:
- Designate someone as the data steward. This person is responsible for data quality and documentation.
- Create a simple data dictionary that explains your codes, fields, and conventions.
- Review your data privacy policies and make sure they’re up to date.
These steps won’t solve everything, but they’ll lay the groundwork for smarter AI adoption down the road.
The Best AI Tools for Nonprofits Create Efficiency
So, what AI tools should fundraisers actually be excited about?
In the podcast, Clay was clear: the tools that matter most right now are the ones that create efficiency.
“I do think it’s the efficiencies that are gonna really impact us the most first,” he said. “Because that’s really where the nonprofit sector needs so much and where fundraising needs so much.”
Think about the daily grind of fundraising. You start your day with a hundred tasks demanding your attention. Emails to send, donors to call, reports to run, notes to update. Most of that is important, but a lot of it is what Clay called dither, the busy work that eats up your time without moving the needle.
AI tools that can reduce dither are genuinely valuable. Tools that prioritize your donor outreach, sync your emails to your CRM automatically, or surface insights without hours of manual analysis. These are the tools that free you up to do the work that actually matters: building relationships.
But Here’s the Catch
Not everything is dither.
Clay made a passionate point about this in the podcast: “Writing thank you notes is not busy work. Writing thank you notes, sending thank you notes is fundraising.”
The goal isn’t to automate everything. The goal is to automate the right things so you have more time for the human stuff. The handwritten note. The personal phone call. The moment of genuine connection that reminds a donor why they gave in the first place.
Before you hand something off to AI, ask yourself: Is this dither, or is this important?
And going along with Clay’s thoughts, this is exactly the mindset we had as we developed our own AI products: Is this helping with the dither/the tasks that don’t need a human?
Take Virtuous Insights, for example. Instead of fundraisers spending hours manually pulling reports and cross-referencing data, AI does the heavy lifting:
- Blends first-party CRM data with third-party wealth and demographic information automatically
- Surfaces donors at risk of lapsing or ready to upgrade
- Identifies major gift prospects with the highest potential
What used to take hours of manual analysis now happens in the background, giving you clear signals about where to focus.
Then there’s Virtuous Momentum. Instead of gift officers starting each day wondering who to reach out to and manually drafting emails, Momentum handles the noise:
- Delivers a prioritized donor list each morning based on urgency and potential
- Drafts personalized outreach in your tone
- Creates intelligent donor plans that adapt in real time
The goal isn’t to replace your judgment. It’s to clear away the administrative work so you can spend your time on what only you can do: the human connection that turns a donor into a lifelong partner.
How to Evaluate AI Tools Without Getting Overwhelmed
If you’re feeling pressure to adopt AI, you’re not alone. There’s a lot of noise in the marketplace right now, and it can be hard to know what’s worth your time.
Clay offered a simple framework for cutting through the hype:
Step 1: Define what you want AI to do.
This sounds obvious, but it’s the step most people skip. “AI” is a big term that covers a lot of ground. Before you evaluate any tool, get specific. Do you want help with donor segmentation? Email drafting? Data cleanup? Portfolio prioritization?
Step 2: Ask yourself, will this help me raise more money?
Not directly, necessarily. But will it remove friction? Will it give you time back? Will it improve your data quality? If the answer is no, it might just be a shiny object.
Step 3: Be discerning.
Clay emphasized that discernment is one of the most important skills fundraisers will need in the coming years. There’s a lot of information out there. Some of it is helpful, and some of it isn’t. Before you commit to a new tool or strategy, pause and ask: Is this valid? Is this true? Is this right for us?
If something feels oogie (yes, that was Clay’s word), trust your gut. That’s a signal worth paying attention to.
One Practical Step You Can Take Today
If you’re overwhelmed by the AI conversation and don’t know where to start, here’s Clay’s advice: define what you want AI to do.
That’s it. Before you buy anything, before you sign up for any trial, before you even attend another webinar, sit down with your team and answer this question: What would we want an AI tool to actually accomplish?
Maybe it’s helping your major gift officers prioritize their portfolios. Maybe it’s cleaning up years of inconsistent data. Maybe it’s just automating email syncing so you can stop copying and pasting.
Whatever it is, get specific. Because once you know what you’re looking for, it’s a lot easier to evaluate whether a tool will actually help.
Final Thoughts: This Is Still a Human Business
AI is going to change some things about fundraising. It already has. But at its core, this is still a business about people.
“What never changes is human behavior and human motivation,” Clay said at the start of the podcast. “This is fundamentally a human business. People are always people.”
Your donors are not data points. They’re living, breathing, values-driven individuals who have chosen to trust you with their generosity. The best technology in the world won’t change that.
So as you think about AI and nonprofit data, keep that at the center. Use AI to serve your donors better, not to replace the human connection that makes giving meaningful.
Frequently Asked Questions
Can AI fix bad nonprofit data?
No. AI is only as good as the data you feed it. If your data is messy, inconsistent, or incomplete, AI will amplify those problems rather than solve them. The principle of “garbage in, garbage out” still applies. Before adopting any AI tool, focus on cleaning up your data, establishing consistent naming conventions, and creating clear documentation.
How should nonprofits think about data governance?
Data should be treated as a strategic asset, just like your buildings, technology, or people. This means elevating data governance to a board-level conversation. Start by designating a data steward, creating a data dictionary that explains your codes and fields, and reviewing your data privacy policies. Clear ownership and accountability around data will set your organization up for smarter AI adoption.
What’s the difference between “dither” and important fundraising work?
Dither is the busy work that eats up your time without moving the needle, like manually syncing emails to your CRM, running repetitive reports, or updating fields that could be automated. Important work is the human connection that makes giving meaningful, like writing personalized thank you notes, making phone calls, or having face-to-face conversations with donors. The goal of AI should be to eliminate dither so you have more time for what matters.
How do I know if an AI tool is right for my nonprofit?
Before evaluating any AI tool, define what you want it to do. Get specific. Do you need help with donor segmentation? Email drafting? Portfolio prioritization? Then ask yourself: Will this help me raise more money? Will it remove friction or give me time back? If the answer is no, it might just be a shiny object. Trust your gut and be discerning about what’s truly right for your organization.
Does AI change the fundamentals of fundraising?
No. At its core, fundraising is still a human business. Donor behavior, motivation, and the importance of trust haven’t changed. AI is a powerful tool for analysis and efficiency, but it doesn’t replace the human connection that makes giving meaningful. The best AI tools serve your donors better and free you up to build deeper relationships, not replace those relationships entirely.
What should I look for in an AI-powered fundraising platform?
Look for tools that create efficiency without adding complexity. The best platforms help you prioritize outreach, automate repetitive tasks, surface actionable insights, and connect all your data in one place. They should reduce the time you spend on administrative work and increase the time you have for meaningful donor engagement. And critically, they should integrate with your existing systems and protect donor data with enterprise-grade security.
Sources:
[1] https://www.edelman.com/trust/trust-barometer
