Almost ten years ago, Peter Byrnes tried to make a donation to a billion dollar nonprofit online. It took him four separate attempts to get the gift through. That kind of frustration is exactly what pushed him to launch Fundraise Up.

Peter has spent nearly a decade since then rebuilding what a donation experience can look like. Now he is watching a much bigger shift take shape, one that has nothing to do with donation pages at all.

In this episode of Missions to Movements, I sat down with Peter Byrnes, CEO of Fundraise Up, to talk about agentic giving for nonprofits, what happens as AI moves from helping donors discover causes to actually recommending, and eventually completing, donations on their behalf.

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Who Is Peter Byrnes?

Peter Byrnes founded Fundraise Up after his own frustrating attempt to donate online exposed how broken the checkout experience was across the sector. He built the company around the idea that the giving moment itself, not just the mission behind it, deserved serious design attention. Fundraise Up has used AI within its platform since launching in 2019, well before the term became common in nonprofit conversations, built on donor to organization behavioral data rather than donor to donor comparisons.

What makes Peter’s perspective distinct now is that he is one of the first people in the sector talking publicly about what comes after the donation form. He introduced the concept of agentic giving at the Bridge conference, describing a shift he believes is already underway even though most organizations have not started preparing for it.

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From Discovery to Recommendation to Delegation

Peter describes three stages in how donors find and give to causes. For most of the internet’s history, donors have been in discovery mode, searching for causes themselves and landing on an organization’s website directly. That has already started shifting into recommendation mode, where AI tools surface specific organizations in response to a donor’s question.

Peter tested this himself before our conversation, asking an AI assistant to help him donate to children affected by conflict in Sudan. The tool recommended organizations and asked clarifying questions about the campaign. When he asked it to complete the donation, it could not, but it tried. “I know I can’t do that today,” he said, “but I know it’s coming.”

The next stage, delegation, is what Peter calls agentic giving: AI not just recommending a cause but completing the transaction itself. He compares the shift to previous channel transitions in fundraising, from door to door asks, to direct mail, to phone calls, to the web, to mobile. Each one required organizations to prepare differently, and each one continues to coexist with the ones before it. Agentic giving, in his view, is simply the next one.

What AI Actually Evaluates When Recommending a Nonprofit

Storytelling has always been the currency of fundraising, and Peter is clear that AI systems do not weigh it the same way a human donor does. “AI cares about facts,” he explained. “Where is that located? What kind of impact does it have that’s backed up, that’s actually has some credibility?”

He breaks this down into four specific areas AI checks when evaluating an organization: identity, whether the AI has correctly identified the right organization at all; mission, whether it accurately understands what the organization does and for whom; evidence, whether impact claims are substantiated by real data; and eventually, transaction, whether there is a clear, authoritative path for a donation to actually be completed.

That last piece carries real financial risk if it is not addressed. Peter pointed to past incidents where unauthorized donation pages for nonprofits redirected legitimate traffic and funding into campaigns organizations were no longer running, creating a compliance and finance mess that took real staff time to untangle.

Why Consistency Is the New Trust Signal

AI systems cross-reference information across many places it lives online, including a nonprofit’s own website, annual reports, press coverage, and public tax filings like 990s. When those sources disagree, even on something as simple as which city or state an organization serves, Peter says the AI has no way to know which version is correct, and trust in the organization drops as a result.

“If your annual report says that you serve New York State, and then your website says you do New York City, and the other one says Brooklyn, it discredits all of them,” he said. “It lowers the trust, because which one is it?” The fix simply requires making the content that already exists say the same thing everywhere it appears.

Why This Is a Real Opportunity for Small Nonprofits

Peter believes smaller organizations are positioned to benefit from this shift more than most people expect. Traffic volume matters to AI trust signals, but it is not the only factor, and specificity often outweighs scale. An organization that clearly articulates exactly who it serves and how tends to rank better than a larger one with vague or inconsistent messaging.

I tested a version of this myself before our conversation, searching for a female-founded nonprofit focused on anti-human trafficking with a strong monthly giving program.

The AI surfaced four organizations, including one from my own hometown that I had followed for years without realizing it was female-founded. I could not get over that. That is exactly the kind of connection Peter is describing: specific, verifiable facts doing the work that used to depend entirely on a donor stumbling onto the right story at the right time.

Peter’s advice for any organization, regardless of size, is to think about who its ideal donor actually is and make sure every public facing document reflects that clearly, rather than trying to appeal to everyone at once. That kind of specificity is exactly what agentic giving for nonprofits rewards, even for organizations with a fraction of a larger nonprofit’s marketing budget.

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What This Means for Your Organization Right Now

Start by searching for your own organization the way a donor would, asking an AI assistant what it knows about your mission, your geography, and your impact. Peter’s team built a free agentic giving readiness assessment specifically for this, available at fundraiseup.com/agentic-giving, which shows where an organization currently ranks and what needs attention.

Once you see where the inconsistencies are, you can use AI itself to help identify and fix them across your website, annual reports, and other public materials. Peter is clear that some decisions should stay human no matter how far this technology goes, including disputes, major gift exceptions, and anything that changes the terms of a donor’s original consent.

You can find Peter Byrnes and follow his work on LinkedIn, and learn more about Fundraise Up’s agentic giving tools at fundraiseup.com.

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FAQ: Agentic Giving for Nonprofits

What is agentic giving? Agentic giving, a term Peter Byrnes of Fundraise Up introduced publicly at the Bridge conference, describes the shift from AI recommending nonprofits to a donor toward AI actually completing a donation on the donor’s behalf. Byrnes frames it as the natural next stage after discovery and recommendation, following a similar path to past shifts like direct mail, phone, and mobile giving.

How does AI decide which nonprofits to recommend to donors? According to Peter Byrnes, CEO of Fundraise Up, AI evaluates four specific areas: an organization’s identity, its mission, evidence supporting its impact claims, and eventually, a clear path to complete a transaction. Unlike human donors, AI does not weigh storytelling heavily and instead prioritizes verifiable, consistent facts.

Why does information consistency matter for nonprofit AI visibility? AI systems cross-reference an organization’s website, annual reports, press coverage, and public tax filings. Peter Byrnes explained that when these sources contradict each other, even on details like service geography, AI has no way to determine which version is accurate, which lowers overall trust in the organization.

Is agentic giving actually an opportunity for small nonprofits? Yes. Peter Byrnes argues that traffic volume is not the only signal AI weighs when evaluating trust, and that small nonprofits with clear, specific, and consistent messaging can rank well regardless of size. He points to specificity, knowing exactly who an organization serves and articulating that clearly, as a stronger trust signal than sheer web traffic.

How can a nonprofit start preparing for agentic giving today? Fundraise Up offers a free agentic giving readiness assessment at fundraiseup.com/agentic-giving that shows organizations how they currently rank and what to improve. Peter Byrnes also recommends nonprofits use AI tools themselves to audit their own online presence for inconsistencies before agentic transactions become widely available.