Plenty of vendors now use AI to help draft their proposals, and there’s nothing wrong with that — used well, it’s a genuine time-saver for a small team facing a big deadline. The problem is that used poorly, it produces exactly the kind of proposal that evaluators have been trained by years of experience to score low. And they can usually tell.

Here’s what gives it away. AI writes fluent, confident, general prose. It fills a page beautifully and says very little. So, an evaluator reads paragraph after polished paragraph about “innovative, results-driven solutions” and “seamless collaboration” — and finds nothing specific to their agency, their project, or their risks. The writing is clean. It’s also empty. And empty is what loses on a scored evaluation, where points go to specifics an evaluator can verify, not adjectives they have to take on faith.

The other tell is subtler: AI doesn’t know things it wasn’t told. It won’t reference the agency’s recent audit, its strategic plan, or the real constraint buried in the RFP — unless you put those in yourself. A proposal that reads as generic is often a proposal that was written without the homework that actually wins.

None of this means avoid AI. It means use it for what it’s good at and do the winning work yourself. Let it draft, organize, and tighten. Then you supply what it can’t: the specific evidence, the tailored past performance, the direct answer to what this evaluator is actually worried about. The goal isn’t to hide that you used a tool. It’s to make sure the finished proposal reads like it was written by someone who understands the agency — because, with your fingerprints on it, it was. 

Take the free RFP Compliance Scorecard → 

FAQ 

Is it against the rules to use AI to write a proposal?

Generally no, but check the solicitation — some now ask about AI use. The bigger risk is that AI-heavy drafts read as generic, which scores poorly regardless.

How do you use AI without losing points?

Let it draft and organize, then add what it can’t: agency-specific evidence, tailored past performance, and a direct answer to the evaluator’s real concerns.