AI in Fundraising: Fundraisers Aren’t Being Replaced. They’re Being Unlocked
What if fundraisers could spend less time on admin and more time with donors? This article explores how AI is making that possible, not by replacing people, but by supporting them. It’s a shift from task-heavy work to relationship-led fundraising. And that’s where fundraising earns its purpose.
If you work in fundraising, you’ve probably had the thought. Maybe quietly, maybe out loud to a colleague: is AI coming for this job?
It’s a reasonable thing to wonder. And the honest answer is: not in the way most people fear. AI isn’t coming for fundraisers. It’s coming for the hours around them; and that’s a very different thing.
A fundraiser managing a donor portfolio spends a lot of their week on work that isn’t relationship building. Research before a meeting. Drafting a follow-up. Pulling a giving history. Writing a stewardship report. Preparing a brief for a board member making a thank-you call. Logging notes after a conversation.
None of that is the job. The job is the relationship; the instinct for when a donor is ready for a deeper conversation, the memory of what matters to them, the judgement about how to frame a gift opportunity. That part is irreplaceable. The scaffolding around it isn’t.
And it isn’t just fundraisers carrying that scaffolding. In larger teams, prospect researchers build the briefs, gift processors keep the records clean, and stewardship coordinators maintain the thread of the relationship between visits. In smaller shops – which is most of the sector across Australia and New Zealand – one or two people are doing all of that work themselves. Regardless of team size, the pattern is the same: a significant portion of every week disappears into work that matters operationally but doesn’t move a single donor closer.
AI is well suited to that scaffolding work: research summaries before a meeting, first drafts of acknowledgement letters, giving history analysis, event invitation copy tailored to donor segments, pledge reminder sequences. The kind of work that consumes hours every week without anyone noticing.
Strip that away and what happens? People carrying multiple roles can carry them better. A fundraiser doing their own prospect research can do it faster and deeper. A small team maintaining stewardship across a large database can maintain it more consistently. Not because they’re working harder; but because the drag has been removed.
AI doesn’t threaten fundraising teams. It threatens the assumption that each person can only do so much.
The fundraisers who carry institutional knowledge about why someone gives, who know when to pick up the phone, who understand that a relationship is never just a transaction; those people become more valuable in a team that uses AI well, not less. They’re the ones who know whether the output is right. They’re the ones providing the context the tool can’t guess.
The decision leaders are facing right now
For those in leadership, the question looks different; and the stakes are higher than they might appear.
When AI makes a team more productive, there are broadly two ways to respond. The first is to maintain the same level of ambition and do the same work with fewer people. The second is to raise ambitions to match the new capacity; to pursue the relationships that haven’t been resourced, the donor segments that have been underserved, the stewardship moments that have slipped through. One pockets the savings. The other advances the mission.
The risk in the first approach is less visible than it might seem. The people who hold donor relationships, who carry years of accumulated knowledge about why someone gives and what they care about, who know where the undocumented decisions live in a CRM; that knowledge doesn’t show up on a spreadsheet – it shows up when it’s gone.
Every fundraising team carries a deep layer of tacit knowledge: an embodied, unspoken sense of how the organisation works, and what the French sociologist Pierre Bourdieu might call its habitus. Which donors prefer a phone call to an email. How to read a room at a cultivation event. Why a particular trust gives and what it quietly expects in return. None of this is written down. It doesn’t need to be, as long as the people who carry it stay. But it is load-bearing; and organisations that have moved quickly to reduce headcount in other sectors have discovered, too late, that what they lost wasn’t task output. It was this accumulated organisational wisdom that kept everything aligned.
This brings us to what may be the most important question in fundraising AI adoption right now; not ‘what can AI do?’ but ‘what are we actually trying to do?’
This is what AI strategist Nate B. Jones calls the intent gap. The concept gained traction after Klarna, the global payments company, deployed an AI agent that handled millions of customer service conversations and saved $60 million. It also, as Klarna’s own CEO publicly admitted, broke something far more valuable. The agent had been told to be efficient; to resolve tickets quickly, minimise handling time, move on. It followed those instructions perfectly. What had never been encoded was the relational wisdom that experienced human agents carried; the habitus of the job. The understanding that a long-standing customer expressing frustration deserved something different from a new one making a routine enquiry. That slowing down was sometimes the right answer. That the goal wasn’t ticket velocity; it was the relationship that might last a decade. The AI optimised for exactly what it was told to optimise for, and eroded everything it hadn’t been told to protect.
The parallel for fundraising is direct. An AI told to be efficient will get you faster letters, quicker research, and cleaner processes. If efficiency is the intent, it will deliver. But if the intent is to build deeper relationships, to raise more for the cause, to steward donors in ways that sustain giving over a lifetime; that is a fundamentally different instruction. And AI cannot infer organisational intent. It has to be given it explicitly, deliberately, before any of the tools are switched on.
Once that question is answered clearly, the opportunity becomes much more interesting than cost cutting. The fundraising sector runs lean already; there was never much to cut. The more compelling question is what becomes possible when people are freed to focus entirely on the work that actually requires them.
Which donor relationships have been underloved because there weren’t enough hours? Which prospects haven’t been properly researched? Which stewardship moments have been missed; not from lack of care, but from lack of time? Those are the questions that raise more money and keep more donors.