Drafting funding bids and impact reports
AI can structure a bid, tighten wording and hit a word limit. It cannot supply your evidence, and it will invent figures if you let it.
Our rating
Good to try
Low risk and useful today, with sensible checks.
What it looks like
Before
Notes: "Ran 340 sessions last year. 62 people. Survey said 80% felt less isolated. One woman started going to the shops again after two years indoors. Funder wants 300 words on outcomes."
With AI
A 300-word outcomes section built only from those figures, keeping the woman's story as the closing example, with the 80% attributed to the participant survey rather than stated as fact.
An invented example.
Bid writing is the work that gets done at nine in the evening by someone who has already done a full day. It is also, for many care charities, the difference between running a service next year and not.
This is one of the lower-risk uses of AI, because bids usually contain no personal data. It still has one serious trap.
The trap: it invents evidence
Ask a tool to write an outcomes section and give it nothing to work with, and it will produce something. That something will contain figures. The figures will be plausible, well-formatted and entirely made up.
This is not a rare failure. It is what these tools do when asked for content they do not have: they produce likely text, and a bid’s outcomes section likely contains numbers.
Submitting invented figures to a funder is fraud, whether or not anyone intended it. There is no version of this that is a small problem.
So: gather your evidence first, give it to the tool, and check every number in the output against your records. If a figure in the draft is not in what you supplied, it is not real.
Where it genuinely helps
Fitting the word limit. Cutting 600 words to 300 without losing the argument is tedious and AI is good at it.
Answering the question actually asked. Funders ask oddly specific questions and bids often answer a slightly different one. Giving the tool the question and your draft and asking whether it answers it is a useful check.
Structure. A blank page at nine in the evening is the enemy. A rough structure to react to is worth a lot.
Reusing your own material. You have written about your service many times. Assembling a first draft from your own previous text is fast and safe, because the facts are already yours.
Plain English. Bids are full of sector language that funders outside the sector do not share.
Where it weakens a bid
Everything sounds the same. Funders read hundreds of applications. “We are uniquely placed to deliver transformative outcomes for the most vulnerable in our community” is now background noise. The specific, slightly awkward, true detail is what gets remembered.
It overstates. AI drafts drift towards the impressive. Left alone it will turn “participants reported feeling less isolated” into a claim about transformation. Funders who fund care know the difference, and overclaiming costs credibility.
It cannot fix weak evidence. If your outcomes data is thin, the honest response is better measurement, not better adjectives. See measuring a baseline.
A sensible way to use it
- Gather the real figures and stories first.
- Paste the funder’s questions and your evidence, and ask for a draft.
- Check every number. Anything not in your input comes out.
- Rewrite the opening and closing in your own words — those are the parts that get read properly.
- Keep at least one specific, concrete detail that no other bid could contain.
- Check the funder’s rules on AI, and declare it if asked.
Impact reports
Everything above applies, with one addition: an impact report is a report to people who already funded you. The temptation to smooth over what did not work is stronger, and AI smooths by default.
A report that says plainly which part of the project did not land, and what you learned, tends to do more for the next application than one where everything succeeded.