Nonprofits are adopting AI fast, but governance, data controls and human judgment determine whether experimentation becomes real organizational value. AI governance is becoming a business necessity as organizations move rapidly from experimenting with AI to using it throughout finance, fundraising, communications, and operations. But adoption is racing ahead of strategy and that creates a very different challenge for nonprofit leaders!
Patricia Bueso, Client Services Technology Adoption Manager at Your Part-Time Controller (YPTC), joined us during Nonprofit Power Week to explain how nonprofits can turn AI experimentation into trusted organizational capability.
One statistic frames the issue: Patricia cites research indicating that 92% of nonprofits are already using or experimenting with AI, yet only 7% are using it in meaningful, impactful ways. That suggests the next competitive advantage isn’t simply adopting another AI tool. It’s knowing where AI adds value, where it creates risk, and where human judgment must remain firmly in control.
Patricia recommends beginning with actual workflows. Identify potential AI use cases across departments, then evaluate each according to effort, value and risk. Ask one deceptively simple question: “What happens if the AI is wrong?”
Low-risk applications may include brainstorming, outlines, email rewrites and meeting summaries. Risk rises when AI begins influencing financial analysis, donor segmentation or organizational decisions.
The conversation also moves squarely into data governance. Where is organizational data stored? How long does a vendor retain it? What happens after a subscription ends? Who has reviewed the security configuration? Patricia recommends examining standards such as SOC 2 and involving IT or technologically knowledgeable board members when appropriate.
Perhaps the clearest operating principle comes from YPTC: “Guidelines help protect the adventurous and reassure the cautious.” Governance doesn’t have to mean stopping innovation. It means establishing guardrails so people can use AI confidently!
Key Takeaways:
Evaluate AI at the workflow level—not as one enormous organization-wide problem.
Rate AI use cases by effort, business value and potential risk.
Distinguish low-, medium- and high-risk AI based on consequences for decisions, people, money and reputation.
Know where vendor-held data goes, how it is secured and what happens to it after termination.
Create AI guidelines defining what is encouraged, what requires approval and what is off limits.
Treat staff training and human judgment as essential parts of AI governance.
#NonprofitAI #TheNonprofitShow