Responsible AI Roadmap Seminar: The Nonprofit Use Case Moment

A clip from our AI Safe Sandbox webinar (September 2025), which we also ran as the Responsible AI Roadmap webinar. Recorded in 2025: AI tools’ settings and features have changed since.

Where nonprofits we’ve spoken with are finding benefit from AI, and the path we follow with them: conversation, policy, pilot, proposal.

Key takeaways

• Grants: tasks that are repetitive but never quite the same, like searching past work for what’s relevant to a new application. It’s the kind of research you’d hand an intern.
• Reporting outcomes, and communications such as streamlining email and preparing presentations.
• Knowledge management: a new staff member can query institutional knowledge through an assistant and get up to speed faster.
• Our process: a conversation about what you want, then a starting policy, then which projects are feasible, then a proposal.

Try this with your team

List the three most repetitive-but-not-identical tasks on your team. Which one would you hand to a capable intern first, and what would they need to know?

Going further

Browse 30+ AI Use Cases for more, or check a specific task with Can I Use AI for This Workflow?

Transcript

Lightly edited from YouTube’s automatic captions for readability. Wording and order are the speakers’ own.

Some of the areas where people are seeing a lot of benefit from these tools right now have to do with grant-related processes, especially things that are very repetitive but not exactly the same. For example, when writing a grant, needing to go through old documents to find which previous work is relevant. That’s something this kind of technology is really good at. It’s the kind of thing you would pass to an intern: research what in our prior work is relevant to this grant. That’s one example.

Another would be reporting, reporting outcomes.

“Yeah.”

Communications. Some of the people we’ve spoken to are interested in streamlining email communications and creating presentations.

Another thing that’s relevant is knowledge management. If there’s a lot of institutional knowledge and a new person wants to get up to speed quickly, being able to query that with an assistant is much faster.

We’ve basically had conversations about what these nonprofits want from us, and then we’ve been able to share back: here’s what we need to start with in terms of a policy. Then we can move into discussing which projects are going to work at your organization, the things AI can solve, and the feasibility of using it. And from there, we develop a proposal.