New Blog Post: AI In Grantmaking

Carrie Watkins

Taking Careful Steps Toward the Future

Customer Success Manager for Grantmaking, Ryan Turner, wrote a piece for our ENGAGE blog on his experience with and the opportunities (and concerns) he sees with generative AI, like ChatGPT.

Here is a preview. Check out the full post here: https://blog.blackbaud.com/ai-in-grantmaking-taking-careful-steps-toward-the-future/

---

By now you’ve likely seen or heard about artificial intelligence (AI), and the predictions that it’s going to upend everything we do. Maybe you’ve even played around with ChatGPT or some other AI language tool. Maybe your organization even uses some early AI for administrative tasks, like a chatbot for questions.

I tried ChatGPT and can tell you it writes wonderful haikus, crafted a pretty decent Valentine’s Day message for my sweetheart, and correctly predicted many of the matchups in my colleagues’ Holiday Movie bracket contest.

On its face, this seems at best a pleasant distraction, or maybe just a waste of time. But if anything is certain, this and other AI systems are only going to get better, and quickly. Even Microsoft has announced incorporating AI into Bing (I wish them the best) and Google quickly followed suit. With that in mind, I began thinking about how AI might start playing a role in our collective grantmaking. While it’s still very rough, I can see artificial intelligence providing a variety of possibilities to streamline our processes and improve outcomes.

AI in Grant Applications

Perhaps the most obvious place to start would be the application process. AI could certainly be used by applicants to fill out parts of the required forms, such as program summaries, leaving the questions that would need a human touch to finalize. This would free a nonprofit’s resources to apply for more grants or focus on their other outcomes.

Similarly—though perhaps dangerously—AI could be used to weed through hundreds or thousands of applications to highlight the options that best fit a grantmaker’s desired outcomes. I say dangerously because the downside of AI is that it is still a blunt instrument, and organizations could miss diamonds that the AI doesn’t know to look for. This would be something I’d carefully consider before implementing, or at least test and monitor by ensuring the automated system is weeding out the same applications that you would.

Continue Reading