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Dictionary termTrack AStablev2026.2

AI in editorial decisions

The use of AI or generative AI tools by a journal editor in the process of managing or deciding on a submitted manuscript -- including drafting decision letters, summarising reviewer reports, or (in the position no major publisher currently permits) using AI output to make or substantially inform the accept/reject/revise judgment itself.

ByCASRAI Editorial Board
· Last updated 5 Sept 2026
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Examples

Worked examples

  • Is an instance

    An editor using an AI-adjacent screening tool for plagiarism detection or reviewer-matching, with the final editorial judgment made entirely by the human editor

  • Is an instance

    An editorial office using AI to check reference formatting or flag missing disclosure statements before a manuscript reaches an editor's substantive review

Counter-examples

Looks similar, but isn't

  • Not an instance

    An editor using generic writing-assistance software (grammar/spelling correction) on their own routine correspondence is not AI-in-editorial-decisions in the sense journals regulate

  • Not an instance

    A reviewer's use of AI to draft their review is ai-in-peer-review, a distinct role and a distinct set of publisher rules

Editorial commentary

Editors occupy a different position from reviewers in the manuscript-handling chain, and publisher AI policies treat the two roles separately. Editorial decisions — accept, reject, request revisions — are the point at which a journal exercises its actual editorial judgment, and every major publisher policy reviewed for this entry draws a firm line at that point.

The publisher and body positions

SAGE’s journal AI policy explicitly bars editors from using generative AI for decision letters or for summarising unpublished research, and treats undisclosed use as a matter for COPE-guided investigation. JAMA Network’s guidance (Flanagin et al., JAMA, July 2023) states editors do not use AI for individual manuscript decisions, while permitting AI-adjacent tools for plagiarism detection, metadata parsing, reviewer recommendations, and reference validation — always with human oversight of the outcome. ICMJE’s generative-AI guidance (May 2023 update) establishes the underlying principle that an AI tool cannot be held responsible for a judgment, which is precisely what an editorial decision is. COPE‘s position is consistent with this: editorial decisions require a human able to take responsibility, and AI tools cannot meet that bar.

How this differs from related AI-band terms

  • vs. AI in peer review: a different actor (editor vs. reviewer) with a different confidentiality exposure and a different point in the workflow — reviewer conduct concerns evaluating a manuscript’s content; editorial-decision conduct concerns making the final call on it.
  • vs. detection tool (AI-generated): screening a submission for AI-generated or manipulated content is a distinct, narrower administrative function that editorial offices may legitimately automate; deciding what to do with a flagged result is still an editorial judgment, not delegable to the tool.

Where the line sits in practice

The consistent pattern across policies is: AI-assisted triage (plagiarism screening, reviewer matching, formatting checks) is broadly accepted with human oversight; AI-assisted judgment (deciding the outcome, drafting the substantive reasoning in a decision letter, or summarising unpublished manuscript content to a third-party model) is not. See AI in manuscripts: publisher policy landscape for a fuller cross-publisher comparison.

Also known as

AI editorial triage · Automated editorial screening

Machine-readable encodings

Use in your systems

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Referenced across the research world

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