Generative AI for nonprofits: Practical tips for starting small and building smart 

Generative AI (genAI) seems to be everywhere, but for many nonprofits, all the talk about “AI transformation” can feel more overwhelming than empowering. How are you supposed to use it, exactly? And how do you do it without compromising your values, your mission, or your team’s capacity? 

At The Bridgespan Group, over the past year, we’ve advised nonprofits, hosted learning sessions, and launched pilots to explore how AI and generative AI might support—not substitute for—the work of social change. Building on recent insights on AI in the social sector, we’re sharing a practical, nonprofit-ready framework for using generative AI tools, actionable ways to begin, and common traps to avoid, even if a full digital strategy is not in place…yet. 

Getting started with generative AI for nonprofits: Embed tools into everyday work 

While much has been written about the potential of generative AI for nonprofits, the real challenge lies in turning enthusiasm into practice. A simple benefit-risk assessment can illuminate trade-offs and identify areas worth exploring first. Resources like Fast Forward’s AI playbook also offer helpful starting points, including how to navigate off-the-shelf tools and what to consider when tailoring genAI use to your organization. 

We’ve seen three tactics work well in helping nonprofits get started: 

1. Integrate genAI tools into recurring team activities 

You don’t need to make dramatic changes to start incorporating generative AI; instead, integrate it into tasks you already do. For example, a project team could create a shared “prompt library,” a curated collection of pre-written and optimized prompts to use with genAI models to help colleagues write up weekly internal updates or board memos more clearly and quickly. In this way, organizations can frame genAI use as a way to reduce busywork, not to reinvent the wheel.  

It can also highlight what AI makes possible in freeing up staff time for higher value-add tasks that advance the mission. When people can see immediate and strategic benefits, they’re more likely to engage. 

2. Build in space for learning and reflection 

Launching “mini pilots” or weekly challenges with focused goals (e.g., draft a donor thank-you) can help staff start using genAI tools. And safe spaces for discussion, like lunch-and-learns or a collaborative forum, allow staff to swap tips, share what worked (and what didn’t), and surface surprises.  

3. Identify and elevate internal champions 

When organizations encourage teams to nominate champions of genAI implementation, it often leads to broader experimentation. These champions don’t need to be the tech-savviest staff but are often already trusted peer influencers. They can surface practical prompts, tools, and uses, while helping others feel more comfortable trying it out for themselves. These champions build trust between staff and leadership, create a sense of shared ownership across the organization, and provide feedback from staff to leadership and tech teams.  

Traps to avoid in adopting generative AI for nonprofits 

Still, even well-intentioned efforts to adapt generative AI for nonprofits can falter if teams fall into these common traps: 

1. “Shiny object syndrome” 

Generative AI for nonprofits is most helpful when introduced to create efficiencies in daily work or advances your mission, not simply to “keep up” because everyone else’s talking about it. Otherwise, adoption can feel forced or performative. And at its worst, genAI implementation can be rushed and ineffective, wasting time, resources, and making future technology rollouts harder. 

2. The ‘AI does it all’ myth 

AI can’t replace human judgment. For example, one nonprofit using generative AI in case management found the automated meeting transcripts increased accuracy and reduced bias and the tool even suggested follow-up actions based on case note patterns. But the final judgement on which action made sense for each client remained with the case manager. Why? Because discretion, context, and trust remain critical. 

3. Ignoring data ethics 

Free and easily accessible genAI tools are convenient. But using them without clear guidelines can put sensitive data at risk. Staff need to understand what information can be used with AI tools and what cannot. Legal, technology, and program leads should work together to establish clear protocols for responsible use, so staff don’t inadvertently expose private data or share sensitive information with AI models that learn from public inputs. 

4. Overloading staff without support 

Pushing generative AI for nonprofits without guidance, training, or alignment can undermine trust within the organization. That’s why it’s important to roll out these tools in a systematic way. At Bridgespan, we began our internal rollout with a dedicated AI policy and a pilot that engaged a small group in the same locale to test uses, develop organizational guidance, and share learnings. Building confidence, especially for nontechnical staff and staff who are understandably apprehensive about the effects of AI on society, takes time. 

If there’s one takeaway for nonprofits exploring genAI use, it’s that you don’t need to have all the answers to get started. What matters most is how you approach it—with curiosity, responsibility, and care for your team. GenAI tools won’t replace human insights, relationships, or the values that drive social change, but when used thoughtfully, it can help nonprofits do more of the work that matters, more effectively. 

Photo credit: Laurence Dutton via Getty Images