Every few months, a new tool promises to write your grants for you. Plug in your organization, answer a few prompts, and out comes a proposal. For a nonprofit leader trying to expand a grants portfolio with a lean team, that promise lands somewhere between exciting and too good to be true.

It is usually the second one. The tools are getting better, and some of them are genuinely useful for a first draft. Here’s the problem with these tools: when you try to generalize something for everyone (selling a product to 1000s of nonprofits), the specifics get lost. And in grant writing, the specifics are the entire point.

Why Generic AI Grant Writing Tools Lose What Matters

A general-purpose AI grant tool is built to serve thousands of organizations at once. To do that, it has to flatten the way that it writes grants. When a tool is designed to work for everyone, it cannot hold the things that make your application yours. You get language that is technically competent and fairly interchangeable. A reviewer reading a hundred applications can feel that flatness immediately.

The deeper issue is what happens when the output is wrong. With a closed tool where you can’t rewrite the skills/code, you are stuck. You can regenerate; you can tweak your inputs, but you cannot reach into the system and fix what is actually broken because you did not build it and you do not understand how it works.

The Case for Training Your Team Instead

There is another path: when you train the experts in your organization to use AI effectively, they can fix the problems themselves.

I have been saying this for a long time (in AI years…so like at least 18 months…ha!): the real promise of AI is that you get to solve YOUR problems. The accessibility of the tech is the benefit.