Artificial intelligence is changing how academic publishing works, and peer review is no exception. AI tools are now being used to screen manuscripts for plagiarism, suggest reviewers, check statistical methods, and even draft review reports. For peer reviewers, this raises practical and ethical questions that need careful thought.
This post looks at how AI is being used in peer review today, what key publishing guidelines say about responsible AI usage, and the line between helpful assistance and problematic shortcuts.
Where AI is already involved in peer review
Many AI-driven checks are performed before a manuscript ever reaches a reviewer. Editorial systems check for plagiarism, image issues, and statistical inconsistencies. Some systems also use automated tools to suggest reviewers based on topic match and expertise. Most reviewers don’t directly interact with these tools, but they are already part of the process behind the scenes.
AI becomes more visible during peer review, and the writing of the peer review report itself. AI-powered tools can help summarize a manuscript, organize thoughts into a structured report, or suggest clearer ways to phrase comments. Although these uses vary widely, the boundaries are not always clearly defined.
Industry guidelines about the use of AI in peer review
Guidance from the Committee on Publication Ethics (COPE) emphasizes the importance of confidentiality in peer review and the reviewer’s responsibility for their reports. Unpublished manuscripts should not be shared with third parties unless journal policies explicitly allow it. COPE does not provide AI-specific guidance for peer review, but this principle extends to any external tool that processes manuscript content.
Confidentiality remains central to the peer review process. Because manuscripts being under peer review are unpublished, sharing them with external tools may raise privacy concerns depending on how those systems handle data. Reviewers are therefore expected to be cautious and follow journal-specific policies where available. COPE also reinforces that reviewers remain fully responsible for their evaluations. Any tools used to support writing or structure should not replace the reviewer’s own judgment.
How AI can help in peer review
AI can be instrumental in supporting peer review in ways that do not involve replacing the human effort of reviewers.
- Using a tool to improve grammar, clarity, or flow after the review is written is generally acceptable. This is like using a writing assistant or editor.
- AI can also help find related literature that might strengthen a reviewer’s perspective.
- Another useful application is structuring a review report once the analysis is complete.
Disclosure
If you have used AI in any part of your review, including assisting with language or structure, disclose it. Transparency is a reasonable professional norm regardless of whether a specific policy exists. A note in your confidential comments to the editor is sufficient: something like “I used a language editing tool to check the clarity of this report after completing my own evaluation.” It would also be helpful to clarify what tool you used and specifically how you used it.
The bottom line
AI is a tool, and like all tools, it can be used well or badly. In peer review, the test is whether the expert judgment at the heart of the evaluation is genuinely yours. If it is, if you have read the manuscript carefully, assessed the methods and conclusions independently, and arrived at your own evaluation, then AI assistance with writing or literature search is not inherently a problem, as long as confidentiality is protected and your use is disclosed. If it is not, no AI tool can substitute for the expert engagement that peer review requires.
We’d like to hear from you
Have you used AI tools in your peer review workflow? How do you think about where the boundaries are? Share your experience and perspective in the comments below.
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