How to humanize an AI-drafted grant proposal
Put the specific claim in the first paragraph. Generated proposals are fluent and general, which is fatal in a format read by tired reviewers looking for the one thing you will do. Name it, say why it is not already known, and let the rest of the document support that.
Typical length · 2,000–10,000 words depending on the scheme, usually written against a rigid section structure. · Last reviewed 16 August 2026
Before and after
Before
This project will explore the important relationship between urban green space and community wellbeing. The research will employ a range of methodologies to investigate this complex and multifaceted topic, contributing valuable insights to the existing literature.
After
We will test whether the wellbeing gains attributed to urban green space survive when access is controlled for income. Two existing cohort studies report the effect; neither separated park proximity from neighbourhood affluence, and the policy recommendations drawn from them assume it did.
A topic became a testable question with a stated gap. The vague promise of insights became a specific problem with the existing work, which is the thing a reviewer is scanning for.
Fluent and general is the worst possible combination
A reviewer is reading their eleventh proposal of the weekend. They are looking for what you will actually do, whether it is new, and whether you can do it. Prose that is smooth and says nothing costs them time and gives them nothing to hold onto, and it is the exact register a language model produces by default.
This is different from the essay problem. Generated proposals are not usually badly structured — they follow the section headings faithfully. They fail because each section is a competent paragraph about the general area rather than about this project, and a document made entirely of those has no specific content anywhere in it.
The test is simple. Take your first paragraph, swap the topic for another one in your field, and see whether it still reads as sensible. If it does, it is not a proposal yet.
The gap is where the work happens
Every strong proposal has one sentence saying what is not known and why that matters. It is the hardest sentence to write because it requires knowing the literature well enough to say precisely where it stops, and it is the sentence a generated draft cannot produce — a model can tell you an area is under-researched, which is a claim about nothing.
The specific version names the studies and their limit. Two cohort studies found the effect and neither controlled for the obvious confounder. A method exists but has never been applied to this population. A result holds in one country and the mechanism suggests it should not travel.
Write that sentence yourself, first, before anything else in the document. Everything else in a proposal is a consequence of it, and a rewrite of the surrounding prose is much more useful once it exists.
What must not be rewritten
Costings, timelines, named collaborators, ethics statements and anything the funder specifies wording for. These are commitments rather than descriptions, and a tool has no way to know that the phrase it improved was a defined term in the scheme's guidance.
The subtler risk is a scored requirement disappearing. Funder templates often require a specific element inside a section — a data management statement, an impact pathway, a justification of resources — and a rewrite that tightens the section can drop it without anything looking wrong. Check the section against the scheme's own checklist afterwards, not against your memory of it.
Disclosure is now a live question here
Several funders have published positions on AI use in applications, and they differ. Some require declaration, some prohibit it in specific sections, and some are silent. Peer reviewers are frequently under a stricter rule than applicants are, because confidential material is involved.
Whatever the scheme says is the answer, and the terms move between calls. Reading the current version costs ten minutes; a declaration problem discovered after an award is a different order of trouble than a clumsy paragraph.
Formats with the same problem
Research papers — the same literature handled for a different reader with a different tolerance.
Dissertation chapters — where naming the gap is the sentence everything else hangs off.
Questions
- Will a funder run my proposal through an AI detector?
- Some have said they may, and the reliability problems apply exactly as they do in universities — a false positive on a competitive application is a serious matter with no established appeal route. That is an argument for being able to show your drafting history, not for a rewriting strategy.
- Is it acceptable to use AI on a grant application at all?
- It depends entirely on the funder, and positions vary between schemes at the same funder. Read the current call documents rather than a summary, and where disclosure is required, describe what the tool did rather than naming it and stopping.
- Which sections benefit most from a rewrite?
- The ones that are correct and leaden — background, wider context, dissemination. The sections that carry commitments, and the sections where the specific claim lives, are worth writing and rewriting yourself.
- How do I know if my proposal is too general?
- Swap your topic for a neighbouring one and reread. If the paragraph still works, it was never about your project. Applying that test to the first paragraph of each section finds most of the problem in about ten minutes.
What to watch for
- Do not let a rewrite touch a costing, a timeline or a named collaborator. Those are commitments, not prose.
- Funder templates are strict. Rewriting can silently drop a required element a section is scored on.
- Many funders now require disclosure of AI assistance in preparing an application. Check the scheme's current terms.
If your writing gets flagged
Rewriting for rhythm and specificity tends to lower detection scores, because that is what detectors read as human. It is not a guarantee — detectors disagree with each other and change without notice, and we do not promise a result from any of them.