How AI Is Solving Philanthropy’s $300 Billion Problem

Hey there. Welcome back. I'm Jim Carter, and today we're talking about something that's been on my mind since a recent conversation with Mike Spier, founder of Altruists. If you've ever wondered how artificial intelligence could change the way we give back and measure impact, this one's for you. Mike's someone I've known for a while through the social impact space. He was part of the founding team@classy.org, which helped raise more than $5 billion for causes worldwide. So, needless to say, Mike already had an impressive track record. But what really got my attention is that he left all that behind to tackle a problem that's been troubling philanthropy for decades. $300 billion sits in donor advised funds right now, with only 20% getting used each year. That's hundreds of billions meant for good just sitting there. You're probably wondering how billions of dollars can be sitting around untouched. The biggest reason is evaluation paralysis. When you're a philanthropist or foundation trying to figure out where to put your money, evaluating programs takes forever. We're talking 20 to 40 hours per program, weeks of back and forth, mountains of paperwork. By the time you finish evaluating one opportunity, three more have passed you by. So Mike built Altruist. And here's where it gets interesting from an AI perspective. They're using advanced artificial intelligence to generate 25 page program evaluations in seconds. Not days, not weeks, seconds. The platform combines verifiable third party data with information from organizations, runs it through AI analysis, and produces comprehensive evaluations that used to take consultants weeks to complete. I've been working with AI for a while, and I've seen plenty of people try to automate things that shouldn't be automated. But what Mike and his team have done is different. They're not trying to replace human judgment, they're enhancing it. The AI handles the heavy lifting of data analysis and initial evaluation, while human experts provide context, ask important questions, and ensure cultural sensitivity. It's exactly the kind of human AI partnership I've been supporting. I actually had a chance to influence some of the thinking behind Altruist. A while back, I helped Pencils of Promise receive a million dollar bitcoin donation from the anonymous Pineapple Fund. We were able to close 10% of their entire year's fundraising in a day, just because we had the right technology in place at the right moment. That experience taught me something important. When you combine preparation with the right tech, you can create opportunities that wouldn't exist otherwise. I've developed this framework. I use with all my clients. Three simple questions that help identify where AI can make the biggest differ. What takes too long, what costs too much, and what good work could you do more of? When you apply these questions to philanthropy, the answers are pretty clear. Evaluation takes too long, comprehensive analysis costs too much. And there's so much more good work that could happen if we could just connect the right donors with the right programs faster. That's exactly what Altruist is doing. They've built features like a dynamic confidence score that measures how certain the platform is about its findings. It looks at program impact, transparency, team strength, all these factors that matter when you're deciding where to put your philanthropic dollars. And here's the kicker. It updates in real time as new information comes in. The platform even has this board book tool that automates reporting and presentation creation. So instead of spending hours putting together materials for board meetings, nonprofits and foundations can generate professional presentations with real time impact data at the click of a button. But let me be clear about something. This isn't about delegating everything to a robot. It's about letting AI be part of your day to day operations so you can make decisions more quickly, more effectively, and with better output. The human element is still crucial. AI can crunch the numbers and spot patterns, but it takes human wisdom to understand context, to ask the right questions, and to ensure we're not just optimizing for metrics, but actually creating meaningful change. The stats around AI adoption and philanthropy are pretty compelling. 81% of foundations now use some form of AI. And studies show that AI powered evaluation can increase philanthropic efficiency by up to 30%. That means more money going to actual programs instead of administrative overhead. Of course, there are valid concerns. 92% of funders worry about how AI uses nonprofit data. 40% cite high costs and overreliance on automation as barriers. These are real issues we need to address. But. But here's the thing. The organizations that lean into these technologies, experiment a little, learn from them, and integrate them thoughtfully, are the ones that'll thrive. Mike said something during our conversation that really stuck with me. He talked about how his parents used to ask at the dinner table whether they'd rather spend their lives being wealthy, happy, or good. The answer was always good. That childhood lesson shaped his entire approach to social entrepreneurship. And it's embedded in how Altruist operates. This collaboration between human expertise and AI capability is exactly what the future of philanthropy needs. We're not replacing human judgment, we're enhancing it. We're making high quality impact evaluation accessible and actionable. For philanthropists who want to maximize their social impact. If you're as interested in this intersection of AI and social impact as I am, I'd love to continue this conversation with you. I run a slack community called Control Alt Build, where we dig into how AI can enhance the good work you're already doing, whether that's in philanthropy, business, or any other field where you're trying to make a difference. We've got leaders from all kinds of backgrounds sharing what's working, what's not, and how we can all use these tools more effectively. I'll drop the link in the show notes for you to join us. Thanks for tuning in today. I think Altruist is a good example of AI for good, and a reminder that AI advancement is not about replacing humans, it's about AI helping us do more of what matters most. I'll catch you in the next episode.