Podcast Summary

Nonprofit Lowdown #355: The Future of Fundraising and AI

Host: Rhea Wong
Guest: Brooke Richie-Babbage, Founder/CEO of Bending Arc
Date: September 15, 2025

Episode Overview

In this dynamic episode, Rhea Wong and her business bestie Brooke Richie-Babbage explore the evolving relationship between nonprofits, fundraising, and artificial intelligence (AI). The two seasoned leaders dive into how AI can be leveraged thoughtfully as a partner—not a replacement—for critical thinking, uncover the best use cases for nonprofits, and parse out complex ethical questions about privacy, bias, and donor trust. They advocate for intentional innovation, highlight the need for practical guardrails, and encourage nonprofits to experiment with AI while staying true to their values.

Key Discussion Points & Insights

1. The Reality vs. Hype of AI in Nonprofits

Timestamps: 01:50 – 04:34

• Hype vs. Reality: Rhea observes that the impact of AI hasn’t matched the initial hype around job loss and full automation.
• Human Concerns: Brooke explains slow adoption is due to significant human concerns—job security, the value of critical thinking, and discomfort with rapid change.
  • "AI isn't a replacement for thinking. It can help you get outside of your own box... but we're rediscovering use cases." (Brooke, 03:58)
• AI as a Thought Partner: The consensus is that AI can help, but it needs human input and discernment.
  • "The calculator doesn't replace thinking, it just calculates it. We need a human to discern if this is a good answer." (Rhea, 04:34)

2. Favorite and Effective AI Use Cases

Timestamps: 05:05 – 09:49

Brooke’s Use Cases:

• Finance Review as CFO Assistant
  • Downloading monthly/quarterly financials, uploading to ChatGPT, prompting for year-over-year analysis, trend spotting, and strategic questions.
  • "It doesn't replace my thinking; I have to sit with those numbers and go back and forth." (Brooke, 06:24)
• Google Analytics Interpretation
  • Downloading analytics, using ChatGPT to simplify understanding traffic sources and conversion issues.
  • Example: Diagnosing a campaign’s failure through 9-second page visits.

Rhea’s Use Cases:

• Donor Data Analysis
  • Anonymized multi-year donation data uploaded to ChatGPT for insight into donor trends, retention rates, major gift thresholds, and fundraising timing.
• Donor Avatar GP
  • Feeding ideal donor profiles and behaviors into ChatGPT for custom outreach email sequences, proposal strategies, and engagement tactics.
• AI Role-Play for Donor Conversations
  • Using tools like Practivated with AI to rehearse donor conversations and boost staff confidence.

“In the absence of knowing, we avoid it because it's uncomfortable.” (Rhea, 09:19)

Takeaway:

AI increases speed and strategic insight by making data analysis approachable and prepping staff for real-world scenarios.

3. Donor Trust vs. Data Ethics—The “Creepy Line”

Timestamps: 10:36 – 15:36

• Tension Point: The line between using AI for actionable insights and breaching privacy.
  • "How would you treat your own grandmother? Would you want someone scraping your grandmother's data?" (Rhea, 11:03)
• Policy Principles (Brooke):
  • Consent-based transparency: Always tell donors what data you’re using and why. Let them opt out.
  • Minimal data collection: Collect only the data essential to your specific function.
  • Transparent Communication: Make the "why" for data use clear to donors.
  • Guardrails: “Form should follow function... Do we need to collect graduation data about my major donor's oldest son?” (Brooke, 13:54)

Tool Recommendation

• Fast Forward’s AI Policy Generator: To help orgs quickly draft thoughtful AI usage policies.

4. Bias, Representation, and Responsible Prompting

Timestamps: 15:21 – 18:36

• Bias Checks in AI Prompts: Important to regularly audit for unintended bias and stereotypes in AI use.
  • “Auditing, what we’re asking AI to do, the assumptions we’re making...unintended stereotypes are baked in.” (Brooke, 15:40)
• Algorithmic Equity Concerns: As women of color, both hosts underscore the lack of diversity among AI creators and the importance of underrepresented groups contributing informed data and feedback.
  • "One thing that I am very careful not to do is opt out...being intentional and leaning in feels important to me." (Brooke, 17:12)

5. Engaging Mindfully with AI—Risks, Rewards & Integrity

Timestamps: 18:36 – 22:45

• Ethical Use of AI: Acknowledgement of environmental and social costs of AI, but also the risks of being excluded (“If we are not part of the conversation, the tech bros win.” — Rhea, 20:07)
• Integrity vs. Absolutism: Using AI is not black-and-white; it's about acting from values and building policies that reflect intentionality rather than rigidity.
  • "Integrity doesn't allow for black and whites. It is always gray areas." (Brooke, 21:08)
• Analogies: Accepting corporate funding—shades of gray; same with AI policy.

6. Infusing Structure Without Killing Innovation

Timestamps: 22:45 – 25:30

• Setting Boundaries: Leaders should co-define organizational guardrails (ethical boundaries, privacy lines, human-in-the-loop requirements), then let teams “play” and experiment within them.
  • "If you start too narrow, that's anathema to innovation." (Brooke, 25:01)
• Feedback Loops: Build regular sharing (e.g., AI experiments at staff meetings) to keep learning current and collective.
• No One is an Expert: The field is too new; everyone’s learning.

7. Overcoming Resistance—Smart Risk and Educating Stakeholders

Timestamps: 25:42 – 28:45

• Stakeholder Pushback: Address leadership reluctance with education—distinguish anonymized data, clarify privacy controls, and delineate what data is uploaded.
• Intentional Adoption: Flat refusal to use AI isn’t sustainable; intentional, controlled use is more realistic and valuable.
  • "The answer is we use AI in a very discerning and intentional way because we have evaluated the risks." (Rhea, 27:46)

8. The Hidden Cost of Avoidance

Timestamps: 28:45 – 32:24

• Invisible Costs: Not using AI incurs real but unseen losses in staff time, operational efficiency, and opportunity.
  • "The value equation, increasingly, is: if we use AI, there's a cost, and if we don't, there's an invisible cost to my team, my time, my energy, my operational efficiency." (Brooke, 29:23)
• Speed as the New Competitive Advantage: Execution speed, not just hard work, underpins organizational success.
  • "Success is not due to hard work. Success is due to your speed." (Rhea quoting Manny, 29:57)

9. Mindset: Done is Better than Perfect—Iterate and Learn

Timestamps: 32:24 – 36:38

• Action Beats Strategy Alone: Fear of making mistakes paralyzes organizations; better to try and iterate.
  • "The danger is not failing. The danger is not making the wrong decision...The real danger is that if you don’t try things, you will look up two years from now, your budget will be the same, your impact will be the same." (Brooke, 32:46; 33:54)
• Quality vs. Speed: It’s not an either/or—a balance of thoughtful action and iteration is best.
• Host Dynamic: Rhea is the bold risk-taker (“shoot first, ask questions later”), Brooke is the methodical planner—effective innovation is in the dance between the two.

Notable Quotes

• Brooke (03:58): "AI isn't a replacement for thinking. It is a great partner. It can help you get outside of your own box."
• Rhea (04:34): "The calculator doesn't replace thinking—it just calculates. We need a human to discern; is this a good answer?"
• Brooke (13:54): "Always start with...What is the least viable set of information that will allow us to accomplish that?"
• Rhea (20:07): "If we are not part of the conversation, then the tech bros win."
• Brooke (29:23): "If we use AI, there's a cost, and if we don't, there's an invisible cost to my team, my time, my energy, my operational efficiency."
• Rhea (29:57): "Success is not due to hard work. Success is due to your speed."
• Brooke (32:46): "The danger is not failing. The danger is not making the wrong decision... The real danger is that if you don't try things, you will look up two years from now, your budget will be the same, your impact will be the same."
• Rhea (36:15): "If you are thinking about AI—dipping a toe in, or you are all in—we support you. Build some guardrails and play and innovate, because the organization that you love depends on you."

Memorable Moments

• Data Practice Exercise: Using AI bots to rehearse donor conversations—addressing a real-world confidence gap.
• Tonal Playfulness: Hosts refer to themselves as “the peanut butter and jelly” of nonprofit innovation (01:49) and “Bert and Ernie” (01:51).
• Ethical Reflection: Rhea’s recurring "grandmother" test for data use and privacy.
• Cultural Commentary: Both acknowledge the Facebook “move fast and break things” ethos, but emphasize the need for values and thoughtful calibration.
• Honest Vulnerability: Brooke shares her hesitancy to adopt “move fast and break things” and the value of balancing cautiousness with Rhea’s boldness.

Timestamps for Key Segments

• 01:50 – The disconnect between AI hype and current reality
• 05:05 – Favorite AI use cases for nonprofits and fundraisers
• 10:36 – The challenge of donor trust and ethical use of data/AI
• 15:21 – The necessity for bias audits in AI prompts
• 17:12 – Navigating bias and ensuring nonprofit voices shape AI
• 18:36 – Addressing the cost/benefit & integrity of AI in nonprofit practice
• 22:45 – Creating containers & boundaries for safe AI experimentation
• 25:42 – How to manage upward/downward resistance to AI adoption
• 28:45 – The invisible cost of avoiding AI tools
• 32:24 – Overcoming the fear of mistakes—prioritize execution
• 36:38 – Closing encouragement for nonprofits to experiment with AI

Final Takeaways

• AI Is a Tool, Not a Threat: Use it thoughtfully, as a partner.
• Guardrails and Transparency Matter: Build policies, be up front, minimize data.
• Bias and Representation Are Real Battles: Stay in the conversation, guide ethical use.
• Iterate, Reflect, Move: Done is better than perfect; avoid analysis paralysis.
• Nonprofit Future: Your mission’s impact is amplified by your willingness to adapt, learn, and experiment with new tech.

Resources Mentioned:

• Fast Forward's AI policy bot
• Practivated for AI donor conversation practice
• Rhea Wong’s fundraising programs at riawong.com