There’s a quiet but urgent conversation happening in philanthropy right now.
It’s not just about AI.
It’s about whether we’re bold enough to use new tools to finally address old problems: systemic bis in grantmaking, access gaps in community engagement, and the burden of bureaucracy that too often crushes small but mighty changemakers.
So let’s talk about it.
Let’s talk about how one major funder used AI to surface historically overlooked voices. How another reimagined volunteerism using automation. And how a regional leader laid down some of the clearest ethical guardrails we’ve seen in the field.
This is not a theoretical exercise. It’s a roadmap.
🌍 The System Was Never Neutral — And We Know It
For years, the philanthropy sector has operated with the best of intentions. But let’s be honest: intentions alone don’t dismantle inequities.
The reality is, many traditional funding practices—lengthy applications, jargon-heavy language, metrics-first mindsets—have favored organizations with the time, staff, and resources to "speak philanthropy fluently." These are often larger institutions with full-time grant writers and dedicated development teams.
Meanwhile, smaller, grassroots, BIPOC-led organizations doing powerful, community-rooted work have been sidelined—not because their ideas weren’t strong, but because the system wasn’t designed with them in mind.
This is where AI offers an unexpected opportunity—not to replace our decision-making, but to help us see our patterns more clearly and design better pathways forward.
🧠 The MacArthur Foundation: AI as a Mirror for Equity
Enter MacArthur.
In a recent pilot, the Foundation explored how AI could amplify, not overwrite, community voice. They used AI to analyze thousands of data points from past applications, surveys, and community feedback. What emerged was telling.
The algorithm flagged recurring themes that had been historically deprioritized—issues disproportionately affecting BIPOC communities, youth-led movements, and emerging leaders with no 501(c)(3) status but undeniable traction.
Even better? They redesigned the application process itself. Applicants could now submit oral or video-based narratives, breaking down the literacy, time, and tech barriers that have made traditional grantwriting feel like the SATs.
The result?
A 30% increase in funding to BIPOC-led grassroots organizations—and a lighter, more inclusive application lift for everyone involved.
🛠 Habitat for Humanity: AI That Gets Hands Dirty
While MacArthur reimagined who gets funding, Habitat for Humanity tackled a different side of the social sector coin: how people engage.
Partnering with Civic Champs, Habitat introduced an AI-powered system for:
Volunteer FAQ chatbots (answering “Where do I park?” before the email ever hits staff inboxes)
Geofenced volunteer check-ins (no more clipboards or signature sheets)
Automated scheduling and follow-ups
The impact?
Fewer no-shows, better volunteer retention, and more time for Habitat staff to focus on building relationships instead of chasing down forms.
What’s beautiful about this isn’t just the efficiency—it’s that the tech frees up humans to be more human.
🧭 United Way Suncoast: Guidance with Heart
Now, before the skeptics jump in (and some of you should—this stuff deserves scrutiny), let’s look at one of the best examples of thoughtful implementation: United Way Suncoast.
In their 2025–2028 Community Investment Guidelines, UWS outlines how and when AI should be used:
“AI must be accountable to human judgment. It is a tool, not a decision-maker.”
They make it clear: AI is fine for tone-polishing and helping under-resourced groups compete more equitably—but not as a crutch that replaces authentic community-rooted proposals. They also warn about using outdated demographic data and the risks of homogenized, impersonal applications.
This is the kind of leadership philanthropy needs: not banning the tech, not blindly embracing it—but applying values and wisdom with eyes wide open.
💡 So What Can You Do—Today?
For philanthropic leaders looking to explore AI responsibly, you don’t need a moonshot budget or a tech overhaul to start. Here are three balanced, accessible steps that build toward equity, efficiency, and trust.
🔍 1. Run an Audit of Your Historical Grantmaking (Thoughtfully)
AI is great at surfacing patterns we didn’t know to look for. Try running a retrospective analysis of your last 3–5 years of grants—applications received, language used, types of orgs funded, those who didn’t get in.
But do it ethically:
Redact organization names and personal identifiers before analysis.
Keep the focus on themes and trends, not individual org profiles.
Be transparent with your team about why you're doing this and how the findings will be used.
You’re not conducting surveillance—you’re holding up a mirror. This is about spotting blind spots, naming bias, and designing smarter, fairer pathways forward.
🚪 2. Rethink the Front Door
If your application process unintentionally screens out small, nontraditional, or grassroots orgs—you’re not alone. The good news? It’s fixable.
Ask yourself:
Could you accept voice notes or video submissions instead of long-form text?
Could you offer an AI agent to help grantees with budget templates or logic models?
Are your forms accessible to those with limited tech access or time?
Small process changes can have an outsized impact on who applies—and who sees your funding as truly accessible.
🧠 3. Establish a “Human-in-the-Loop” Standard
Whatever AI tools you experiment with—proposal screening, data analysis, chatbot FAQs—don’t remove people from the equation. AI is fast, but discernment is still a human superpower.
Build your practice around:
Human review at critical points
Explicit and clear ethical guidelines for staff and vendors
Community feedback loops that check for unintended impact
Remember: AI is a tool. Values set the blueprint. People make the calls.
🌱 A Final Word: AI Won’t Save Us, But It Can Help Us See
At its best, AI isn’t the hero of this story.
You are.
The funder willing to try something new. The nonprofit leader who says, “We’re using this tool, but we’re doing it ethically.” The grantmaker who redesigns an intake form because they actually listened to feedback.
MacArthur, Habitat, and UWS show us three different doors into the same room—a room where AI isn’t a threat to our values, but a tool that can help us live them more fully.
Now the question is: Will you walk through?
This piece was made possible by the ongoing work of funders, nonprofit leaders, and thinkers asking the hard questions about equity, technology, and community. Want to share your story or AI pilot? Let me know. Let’s build this future together.