AI for Grant Applications and Impact Reports
Draft stronger grant applications and honest impact reports with AI as your assistant
A taste of a lesson
AI wrote that our youth project will reduce local crime. We never measured crime. Should I keep it?
No, cut it. You have no evidence your project affects crime, and a reviewer may see it as overclaiming, which weakens the rest of the application. Replace it with an outcome you can actually measure, such as young people reporting stronger relationships with a trusted adult, or regular attendance over twelve weeks, and say how you will collect that. If reducing crime is the long term aim, frame it as the wider goal your outcomes contribute to. What is one change in participants you could realistically measure?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Summarise funder guidance into a criteria map linked to your evidence
- Draft application sections from your own notes without invented facts
- Distinguish outputs from outcomes and write a simple measurement plan
- Write impact reports that compare promises with results honestly
- Protect beneficiary data and follow funder rules on AI use
Lesson plan
- 1 Reading the funder before writing Turn funder guidance into a clear list of criteria, limits and rules. Start
- 2 Your project facts file Gather the facts, figures and stories every application will draw from. Start
- 3 Mapping criteria to evidence Build a table that links each scoring criterion to your proof. Start
- 4 Drafting sections from notes Use AI to draft and tighten sections while keeping every claim true. Start
- 5 Outcomes and measurement plans Write outcomes that are specific and say how you will measure them. Start
- 6 Honest impact reports Turn programme data into a clear report that compares plans with results. Start
Try asking
About this tutor
For staff and volunteers at nonprofits, community groups and social enterprises who write funding applications and report back to funders. You will use AI to read and summarise funder guidelines, map your project to their criteria, draft sections from your own notes, tighten language to word limits, and turn programme data into clear impact reports. The tutor is strict about honesty: AI must never invent outcomes, numbers, beneficiary stories or partnerships, and many funders now have their own rules about AI use in applications. You also learn how to protect beneficiaries' personal data. You finish with a reusable application kit: a project facts file, a criteria map and a reporting template.
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About the teacher
Practical AI for small businesses, founders and nonprofits with no time and a small budget
9 tutors 431 lessons taught Sample
I work with people who run small organisations: shop owners, solo operators, early founders and nonprofit teams. I have run small ventures myself and done the admin, the marketing and the customer emails at eleven at night, so I teach AI the way it actually fits into a crowded week. We start with the job you hate most, try one...
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