Name: AI in Philanthropy: Separating Myth from Reality
Uploaded: 2026-09-24T18:30:43.979Z
Duration: 31 min 20 s
Description: AI in Philanthropy: Separating Myth from Reality

Transcript for "AI in Philanthropy: Separating Myth from Reality": Hello. Welcome. Welcome to the AI and philanthropy separating myth from reality webinar. I do see some some chatter going on. I think there's some issues going on. I can see our docs and resources section, and our q and a, but it sounds like, folks may not. Hopefully, maybe going live. You all could see it. I'm gonna get started with some housekeeping that hopefully we will address some of these pieces, and then we will get started. So webinar housekeeping. Hopefully, you're hearing me. The audio is broadcast through your computer. If you need captions, you can hover over the stage, and there's a little, CC button on the bottom of the screen to turn captions on and off. If you have any issues with audio or technical issues in mid midway through the presentation, maybe I freeze. Usually, just refreshing your browser is all you need to do. Worst case scenario, just leave and log back in. And if you miss something, yes, we are recording. So a recording of this entire webinar will be sent to you, by end it's usually end of day tomorrow. During the presentation, you can, click the q and a button. Sounds like it's working now. So over on the right, you should see chat and then docs. There's lots of documents there you can check out. We'd love for you to, look at some resources we have. And then there's a q and a. If you have questions during the session, that is the right spot. You'll see in a second, when I go through agenda, we have some clips from some experts that we are gonna share today. For those of you who might be attending with us, we are days away from, BBCon twenty twenty six, and so some of our experts and folks are already traveling for BBCon in the case of Lorraine, who's coming from overseas or finishing up their presentations and packing those of us in marketing, I know we're packing swag, things like that. So, this format's a little different today. So if you have questions, we do have some folks in the back that, in the back, if you're, you know, in virtual land that will answer those that can. If it's something really in-depth where I'm like, oh, I just really need Tim to answer this, we will do a post document or content piece that'll address some of those really tricky questions you might have for us if we, if we can't answer them today. Last kind of logistics here, you can adjust any settings using the toggle at the bottom of your event space, and you can also use the tab at the top to see your agenda, me, all those things. As I said, we expect you'll have questions. Please use the q and a. And if we don't have the answer, we will get you one in the coming weeks after. For those of you who I have not met or you haven't been in a webinar I've been on a while, my name is Amelia. I am the principal product marketing manager on the Agents for Good team here at Blackbaud, and I am in Minneapolis. So I'm excited to be traveling to Columbus next week for BBCon, and seeing some of you. So today's webinar is about myths, AI myths. And we have four different myths we're gonna just, discuss, and we have three different experts that are going I'm gonna share little clips about, from. So our first myth is that AI is replacing fundraisers. You might also hear this as it what it looks like when we have an agent on board. Does this mean we don't have other staff? Do we need interns still? How do we manage them? All those piece of puzzle. So we have a clip from Steven Churchill. Some of you might know Steven. He works really closely with our development agent customers, and he's gonna share a bit about what this looks like. Hey, everyone. We've all heard the buzz going around that AI is coming for jobs with fundraising included there, that soon algorithms are going to be writing appeals, running cultivation strategies, and closing gifts, leaving the fundraiser as optional. And there's a soft devotion of that same idea floating around that AI actually works best if you take the human out of the loop entirely. Don't slow it down with review, just let it run. But if given time to look in an incredibly busy fundraiser's day, you'll see the evidence against those claims stacking up fast. It is true that AI is genuinely excellent at the parts of fundraising that used to eat up a fundraiser's entire week. Those wealth screenings, prospect research tasks, drafting the first pass at those appeal letters, flagging a donor who's about to lapse, and even helping to keep your data in your CRM clean. Those are real wins, and nobody should be nostalgic for the hours fundraisers used to lose to manual data entry. But here's a mistake. Jumping from AI is great at fundraising tasks to AI is great at fundraising and treating the two claims as the same when they very much aren't, and your donors are the ones proving it. Research on this is consistent with donors showing that they can tell when an appeal has no human behind it, and their ability to recognize that erodes the trust you were working so hard to build with them. Fidelity Charitable's research on donor perception found that people are genuinely open to AI assisting a fundraiser, but they're a lot less comfortable when AI replaces one. And think about what that means. If fully autonomous AI outreach was actually the most effective model, you'd expect donor response data to award that. Instead, it does the exact opposite. Now this, of course, isn't some quirk specific to fundraising. It's actually a pattern that shows up everywhere researchers have tested AI against judgment heavy work. Since the earliest studies comparing AI plus human teams against AI working alone, the finding that keeps coming and being repeated across all of our fields is human in the loop systems outperform fully automated AI on accuracy and on error rates. Fundraising has its own version of this with things the model can't see, a donor's hesitation on a call, the organization's unspoken priorities, the read on whether now is the moment for a bigger ask or if that should be later. That information isn't living in any dataset, and honestly, the companies actually building fundraising AI aren't designing it to run without a human. BlockBot's own development agent, for example, is built around human oversight, visibility, and escalation baked in. It automates the day to day outreach that removes management flow, but still allows for true human oversight and management. And that's not some compliance footnote for us, it's a true AI strategy. If AI works best without humans will true, the incentive would be to build toward full autonomy. Instead, the tools winning trust across the fundraising space are the ones that keep a person in the loop on purpose. So what's actually happening to fundraising jobs? It's the same thing happening in most fields right now. Rather than replacing talent, the best AI offerings are working to redistribute it. AI is taking the parts of the job that were never really about those relationships, the research, the first drafts, data cleanup, and handing fundraisers back the time to spend on the parts that are all about those relationships, calls, visits, the judgment calls on timing, the follow through that turns a first gift, into ten years of repeated giving. This myth sticks around because AI replaces fundraisers is just a punch you headline, then AI changes what fundraisers spend their time on. But remember, punch you is not the same as true. AI ceiling and fundraising will be set by how well it makes fundraisers more effective, not by how well it replaces them. It's funny to not have Steven live here. I feel like I should say thank you, Steven. But he is, again, prepping for BBCon. But to his point, we have purposely built, the solutions that we're bringing to market, whether it's development agent or some of our upcoming agents, to make sure that fundraising expertise and the functional expertise is coming all the way through, whether it's using best practices that we know from decades of experience working with you all in the field, combining that with the real oversight of an agent manager, which is a really important role that, people are learning how to do. We're actually working towards a lot more guidance on how to be a really good agent manager. It's a little different, right, than managing just a person or a team, but how do you fold that, agent in and how do you oversee their work, while letting them actually add capacity to your team. So you don't wanna be reading every email that the agent writes all the time forever, but making sure they learn with, what they need to to do the job that you've assigned them really well. Our next myth is that AI creates impersonal donor experiences. So we're gonna hear about how Responsible AI can support the human center experience from Tim Hammond, who you may or may not have met. Tim is fantastic, and he is in our user experience, area and helps design, our agents right now and other wonderful products we have. One of the biggest concerns I hear about AI in fundraising is that it's going to make donor experiences feel impersonal, and honestly, I think that's a reasonable concern. But when people ask me that, I usually come back to a different question. What actually makes a donor experience feel personal in the first place? Because I don't think donors are asking for more communication. Most of us already get plenty of that. What donors want is communication that feels relevant. They wanna feel like the organization knows who they are, understands what they care about, and values their support. They want to feel seen. When we talk about personalized fundraising, we often imagine every donor getting outreach that's specifically tailored to them. But for most organizations, that's not really what's happening today. Most donors aren't having one on one conversations with fundraisers. They're getting messages that are designed to work for a large audience. That's not because organizations don't care. It's because true personalization is really hard to do at scale. Most organizations would love to create deeply personal experiences for every donor. They'd love every communication to reflect a donor's interests, history, and relationship with the mission. The challenge is that there are only so many hours in a day. A fundraiser might be responsible for hundreds or sometimes thousands of donors. Even when organizations have good information about those donors, acting on that information consistently can be incredibly difficult. In fact, most organizations already know quite a bit about their donors. They know what causes people care about. They know what people have engaged with in the past. They know who attends events, who volunteers, who opens emails, and who has been supporting the mission for years. The challenge usually isn't gathering the information. The challenge is using it. And that's actually why I find the AI conversation interesting because the question stops being, will AI make fundraising less personal? And for me, the more interesting question is, could it help make fundraising more personal than it is today? Could it help organizations make better use of what they already know about their donors? To dive into this, let's imagine two donors who are supporters of a national organization that protects animals and the environment. Maybe one of those donors is passionate about animal welfare, while the other cares more deeply about the environmental conservation side of things. If both of them receive exactly the same message, that's not a particularly personal experience, even if someone spent a lot of time writing that message. But if each person receives a story that's connected to the reason they care about the organization in the first place, that feels different. It feels like the organization understands them, and I think that's an important distinction. Donors don't really experience the amount of effort that went into a communication. They experience whether it feels relevant. If I get a message that reflects the things I care about and helps me see the impact of my support, that feels personal. On the other hand, if someone spent an hour writing a message, but it could have been sent to anyone, that doesn't necessarily feel personal at all. To me, that's the opportunity here. And just to be clear, AI doesn't create the relationships. It doesn't build trust, and it doesn't inspire someone to care about a mission. People do that. The fundraisers, volunteers, staff members, and supporters behind an organization are still the ones creating human connection. What AI can do, though, is help organizations be better stewards of those relationships. It can help them remember more, notice more, and act on more of what they already know. It can help extend the same level of thoughtfulness to more donors than would otherwise be possible. And that's very different from replacing the human side of fundraising. It's actually about supporting it. At the end of the day, the relationship is still between the donor and the organization. The mission still matters. The people behind that mission still matter, and AI doesn't change any of that. What it might change is how many donors get an experience that feels like it was actually meant for them. So to circle back to the original question of whether AI makes donor experiences impersonal, my answer is not really. In fact, I think the bigger risk is settling for a world where most donors continue to receive generic communication because personalization is simply too difficult to deliver consistently. If AI can help more donors feel understood, recognized, and connected to the causes they care about, that's not less personal. That's more personal. Here we go. Again, thanks, Tim. Tim will also be at BB Kind, for those of you who are there, if you have more questions for him. We have two more myths, and Lorena's gonna speak to both of them. If you have not seen a webinar with Lorena or, by chance met her, although she, for those of you in The US, she lives overseas, as you will tell by her lovely accent. She is brilliant AI researcher. Her her whole purpose is to research how to do responsible AI, how people and donors, and society is responding to AI. So she is the perfect person to speak to these last two minutes. This one is donors don't want nonprofits using AI. And I'm sure that she will reference some of our baby institute data from our research that we put out this summer, but I bet she has some newer things as well. An assumption or myth can be that donors don't want nonprofits using AI, and there's reasonable basis for this concern. Donors care deeply about the organizations that they support. The the social impact sector itself is relationship driven and AI raises real questions about data, about human connection, about whether technology could weaken the relationship that they have with a cause. But our research gives us a more nuanced picture and our Blackbaud Institute bridging the AI effectiveness gap research, 81% of donors said that they already use AI themselves. 71% said that they were either equally comfortable or more comfortable with social impact organizations using AI than they are with for profit companies using AI. And the evidence doesn't point to donors rejecting non profit use of AI altogether. And our qualitative research where we have deep discussions on the topic helps us understand more of the the why behind this. And what we've seen is donors actually recognize that non profits are operating under increasing pressure and limited resources and they can see a role for AI in helping organizations work more efficiently, extend their reach and direct more capacity towards their mission. But at the same time, that openness comes with expectations and responsibilities. And what donors appear to be asking for most clearly is transparency. 76% want to understand when and how AI is being used and only around 26% of social impact organizations reported that they currently disclose this. And 68% of donors also said protecting sensitive personal data is very important. And I think what's particularly encouraging is that that openness and transparency about AI use has the potential to strengthen that trust that organizations have worked so hard to build. And when organizations communicate whether and how they use AI, the research shows a net positive effect of around 18% on donor trust across all generations. A public statement explaining responsible AI use is also likely to produce a net positive effect of around 20% on existing donors' likelihood to continue to give. And what we're seeing from these insights is that transparency, it means more than than adding a disclaimer. Donors want to understand why they are receiving a communication, for example, what they are being asked to do, who remains responsible and how they can reach a person if they need one. And in our research on agent enabled communications, people responded better when the purpose was clear, the relationship remained with the organization, and AI supported rather than overshadowed the mission. So our research is signalling that donor caution isn't a message to avoid AI. The research suggests something different. What we're seeing is that donors can see where AI may help organizations become more effective, but they want organizations to be transparent, accountable, and thoughtful about how it's used. And, ultimately, donor trust is shaped less by the presence of AI itself and more by the choices that organizations actually make around it. So I I we get that question a lot, and we get it about different demographics and some of that's in the, Black Witness Institute research. But what we continue to hear over and over is about that transparency. So sometimes, if you've been to, if you've been exploring Agenstic AI, perhaps, maybe you've been to a development agent product tour, we almost always get the question of, does the donor know it's an AI agent? And we say yes. Not only in the first message from development agent, for example, does it introduce itself as an AI solution that the organization that they're subscribed to is using. It does a little intro about the why and the, organizations give it names. And then sometimes we get the question, wouldn't it be more effective if they didn't know? Right? So we're all kind of used to if you're in marketing automation where I can write an email that looks like it's from someone in leadership perhaps. Right? And it's kind of it's mocked up as if it's for an email from someone that it's not. And, really, at the end of the day, we haven't built things like that because donors are saying we don't want that. We want to know when you're using AI. We wanna know when we're having a conversation with an AI agent. That doesn't mean that conversation is less effective at their goals. It's often more responsive. People really like that it can be responsive in off hours, things like that, but they want to know. It builds trust to be as transparent as possible. And the tools we use aren't they aren't secrets. Right? So I I love that. It's not that people don't want it. We're actually, nonprofits and, higher ed organizations and health care foundations things. We're actually kind of behind, where founders expect us to be with AI usage or where they're comfortable, but but it's all about that trust and transparency. That was one of the most interesting parts of the research that was done this summer to me. Our last myth, is AI and ethical fundraising cannot coexist. And Lorraine will obviously is uniquely qualified to talk about this, and so we have one more, clip from her. An assumption or myth can be that AI and ethical fundraising can't coexist. And when I hear this, my starting point is to take the technology out of it and bring our thinking back to people and principles that that matter to us and our organizations. And ethical fundraising has always been about stewardship. It's about treating people respectfully, protecting trust, and using information responsibly and building relationships that supporters feel good about being part of. And those principles existed long before mainstream access to AI technology and AI doesn't or shouldn't change what ethical fundraising is is fundamentally about. And I think that the bigger question is whether those principles continue to guide how new technologies are used, and our research suggests that they absolutely should. And in our research, many of the things that donors tell us are important when it comes to responsible AI are things that have been central to ethical fundraising practice for years. So things like protecting personal information, maintaining accountability, applying appropriate human judgment, and being open with supporters, respecting donor choice. And in our Blackbaud Institute research bridging the AI effectiveness gap, 68% of donors said protecting personal data is very important, 61% place high importance on human review of AI generated outputs, and 60% say clear policies and accountability matter to them. So to me those are examples of good stewardship and that's why I think ethical fundraising provides a useful framework for thinking about AI. So questions such as are we handling donor information responsibly? Can we explain how a decision or communication was generated? Is someone accountable for the outcome? Are we acting in ways that respect donor choice? And does this strengthen trust over time? So those are all stewardship questions before they're technology questions and donor agency is especially important here. Our research highlights that people need enough information to make informed decisions for themselves and transparency supports that agency because it helps people understand what's happening, where AI is involved and where people remain accountable. And this is why I see ethical fundraising and responsible AI as complementary rather than competing ideas. And responsible AI helps us think about how technology should be governed, which is very much includes ethical design. So ethical fundraising actually helps us think about the values that need to be supported and upheld when using those technologies. So for me, the conversation becomes less about AI in itself and more about whether organizations continue to demonstrate stewardship, accountability, transparency, and respect for supporters as fundraising evolves. So the technology may change, but the responsibility to earn and maintain trust doesn't. So, again, I'll say kind of a funny thank you, to Loreen. We'll also be at BBCon for those of you who'll be there. If you're not planning to travel to Columbus with us next week, you can still register for virtual b b con, by the way, if you're watching this live at bbconference.com/2020six. Not every session will be virtually, filmed things because there's a lot going on. But if you would if from your seat you would like to see kind of what's being announced and what's going on, we would love to have you. A poll is going to come up here or has. If you would like more info about whether it's our AI agents or you just, hey. I have a myth or something that's been bubbling around my office I wanna discuss. We would love to have a discussion with you, and one of our AI experts would will give you a call and make sure we set up a time. As I mentioned at the beginning, there are docs, in your, like, chat docs, q and a section. There are a number of pieces that we've done that include a lot of this research that you can check out or share, as you will. And then if you have an open q and a question, we I'm gonna move to, like, a thank you slide here, but we are gonna keep this open for a few minutes. We won't kick you out. If we have the answer, we will get back to you. And then if there are questions where we're thinking, those of us who are on today, I am not the AI researcher, but Loreen is traveling. We will, do a post content piece on some of these other questions you may have. We're continuing to have this conversation. We've discussed doing a repeat of this in a few months with new myths or new versions of this because they continue, to emerge as we are all learning about how to use AI effectively and ethically in fundraising, every day. That's what we do every day. Thank you so much for joining us. A recording of this will come to you in the next day or so, and we hope to see you again on our thought leadership webinar, in the future. Thank you so much.