How to use AI in grant writing without getting flagged
AI tools frequently strip out essential substance and replace it with generic boilerplate, yet even completely original drafts often trigger false positives on AI detectors. This leaves applicants trapped between producing low-quality text or facing unfair penalties for automation, while grantmakers simultaneously use the same opaque systems to evaluate submissions.
What people tried
Every workaround mentioned in the threads below. We haven’t tested any of them — and nobody here is claiming they worked.
Found another way around this?
Share your steps and trade-offs so fellow engineers don't have to reinvent the wheel. No account required.
- 1Using AI exclusively for non-creative administrative tasks like brainstorming, summarizing webpages, or outliningDid this help you?
- 2Refusing to use AI entirely out of ideological preference or fear of rejectionDid this help you?
- 3Passing proposals through LLMs to improve grammar for non-native English speakersDid this help you?
In their words
Unedited, grouped by where they were said, most upvoted first within each place, each linked to the thread it came from.
“I understand why so many overworked nonprofit employees are using AI in the preparation of proposals. What concerns me significantly more is funders using AI to evaluate them.”source ↗
“We have seen issues where several applicants give similar responses to a question because they've all used AI, but it hasn't been a huge issue yet.”source ↗
“Most of the time, what comes out is terrible. The LLM removes much of the substance and replaces it with nonprofit brain rot”source ↗
“I’ve put my own 100% self written narratives into AI detection tools and it still says it's partial AI when none was used.”source ↗
Where this came up
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