AI in EU Proposal Writing: What It Can Change in Evaluation — and What Applicants Must Check
AI can help organise and edit a proposal, but fluent text is not evidence of project quality. Learn how unsupported claims, invented citations and inconsistent delivery plans can affect evaluation — and how to use AI responsibly.
The Tool Is Not the Evaluation Criterion
Generative AI can support brainstorming, outlining, language editing and checks for repetition. It cannot establish whether a project's scientific claims are correct, whether partners have agreed to their responsibilities, or whether the proposed impact is supported by evidence.
Applicants should not assume either that using AI automatically improves their score or that any AI-assisted text automatically receives a penalty. Evaluation follows the requirements and criteria of the relevant call. For Horizon Europe RIA and IA applications, the proposal template organises the narrative around Excellence, Impact, and Quality and efficiency of implementation.
The practical issue is the quality and reliability of the submitted proposal, including any parts produced with AI assistance.
What the Horizon Europe Template Requires
The official Horizon Europe RIA/IA application template includes specific guidance on generative AI. It states that applicants remain fully responsible for their proposal content, including AI-generated material, and must be transparent about which tools were used and how.
The guidance requires applicants to check the accuracy and appropriateness of generated content and citations, provide and verify sources, consider plagiarism risks, and acknowledge limitations such as bias, errors and knowledge gaps.
Read the template provided for your particular submission. This Horizon Europe guidance should not be presented as a universal rule for every Erasmus+, EuropeAid or other EU funding instrument.
Where AI-Assisted Drafting Can Weaken a Proposal
1. Generic text instead of a specific project
A polished description of an important societal challenge does not establish a novel contribution. If the narrative lacks measurable objectives, a clear methodology or a convincing explanation of what is different, the proposal can remain weak under the relevant criteria.
2. Invented references and unsupported figures
AI tools can generate plausible-looking publications, statistics and policy references that are inaccurate or do not exist. Each citation and quantitative claim needs to be checked against the original source. An unsupported baseline also undermines the credibility of claimed impact.
3. Inconsistent work plans and budgets
Drafting sections separately can create contradictions: different participant numbers, deliverables that do not appear in the work plan, or activities with no corresponding resources. These inconsistencies make it harder to judge whether the project is feasible.
4. Promises the consortium has not agreed to deliver
An AI-generated description of a partner's facilities, expertise or role is not confirmation from that partner. Obtain institutional agreement and verify capacities before including them in the application.
A Responsible Review Workflow
Use human expertise to define the project and verify the evidence before relying on AI for drafting assistance.
1. Start with the official topic, template and evaluation criteria.
2. Build an evidence pack with verified references and agreed partner information.
3. Use AI for clearly bounded tasks, such as reorganising a paragraph or identifying inconsistent terminology.
4. Check every generated factual claim, citation and quantitative statement.
5. Review the narrative, work packages and budget together.
6. Follow the applicable transparency requirements and record the tools and purposes of use.
7. Have subject-matter and proposal specialists conduct the final review.
As a separate data-protection safeguard, do not upload confidential consortium documents, personal data or unpublished intellectual property to an AI service without appropriate authority and a review of its data-handling terms.
Improve Substance, Not Just Fluency
The most useful AI-assisted proposal is one whose language helps evaluators understand a sound project. Better wording cannot repair an unsupported innovation claim, an unrealistic implementation plan or a missing route to impact.
INTERALTER combines proposal support with human quality review. Request a free assessment of your opportunity before committing to a full application.
Official Reference
- Horizon Europe standard application form for RIA/IA, including guidance on generative AI — guidance checked against the template dated 22 January 2026.
This article provides practical preparation guidance, not a prediction of an evaluation result or a statement that every programme uses identical AI rules.