The Use of AI In Manuscript Writing: What Editors And Reviewers Expect

Today, many authors use AI tools while preparing their manuscripts. These tools mainly help authors to refine language, organize ideas, or speed up early drafts. If you have used or plan to use AI tools to assist in your writing, remember that irrespective of the tool you use, your manuscript needs to uphold high standards of quality and integrity. Editors and reviewers are guided by the principles that have shaped scholarly publishing for decades: accountability, transparency, and intellectual ownership. The real question, then, is not whether you used AI. It is whether you used it responsibly and ethically. 

How AI helps in the manuscript writing process 

Most editors understand that researchers are under pressure to write, meet deadlines, and address extensive peer review comments. Using AI tools to improve grammar or clarify phrasing is not inherently problematic. In fact, many journals already encourage authors to get support with language editing. Concerns arise when AI usage moves from polishing the expression to generating content on behalf of the author. If an AI tool drafts your literature review and you accept its output without verifying the content or sources, you are likely introducing an integrity risk through fabricated citations, misrepresented findings, or shallow synthesis. Reviewers notice this. They see references that do not align with the argument, paragraphs that sound polished but lack depth, and conclusions that move too quickly from data to claim. These are not minor issues. They raise doubts about whether the author fully engaged with the research. Responsible AI usage means understanding these boundaries and acknowledging that AI can support clarity, but it cannot replace human judgment, critical thinking, or domain expertise. 

What editors expect from authors who use AI tools 

Editors are not trying to police technology. They are protecting the credibility of their journals and the trust of their readers. When they assess a submission, they expect the authors to take full responsibility for their work. This includes verifying references, checking statistics, and understanding every claim made in the manuscript. If you used AI to refine the text, you are still accountable for the accuracy of the content. Many journals now have clear AI policies. Some ask authors to disclose if AI tools were used for manuscript drafting or editing. Others insist that the use of AI be clearly explained in the Methods section. Editors expect authors to read these policies carefully. A common frustration among editors is not that AI is used but that AI usage is disclosed, or that obvious AI-introduced errors were left uncorrected.  

What peer reviewers look for 

Reviewers may not know whether or to what extent AI was involved but they are often the first to detect when something feels off. For example, a common AI-introduced pattern is surface-level synthesis. The manuscript summarizes several studies but does not compare them critically or meaningfully. Inconsistent terminology, where concepts shift subtly across sections, is another signal. Another example of poor AI usage is when references appear relevant by title but do not actually support the claim when examined closely or have fudged key details. Peer reviewers also look at the logic of the argument. If the discussion overstates the implications of the data or if the analysis seems disconnected from the methodology, they are unsure about the work. In peer review reports, this often shows up as comments like “The argument needs deeper engagement with the literature” or “Please clarify how this conclusion follows from the results.” When AI is misused or used without discernment, it can weaken the core of the manuscript. Reviewers are not looking for perfectly written manuscripts. They are looking for evidence that authors have done the thinking. 

Transparency: The non-negotiable principle 

Transparency is emerging as the core requirement for AI usage by both authors and peer reviewers. A clear statement indicates exactly where and how AI tools were used and confirms that the authors have reviewed and verified all content. Transparency protects authors. If reviewers question a citation and authors can show that they verified sources and disclosed how they used AI, the conversation remains focused on improving the manuscript rather than on questioning integrity. In the long run, transparency builds trust among authors, editors, and reviewers.  

These are not bureaucratic hurdles but safeguards. In editor/reviewer-author interactions, conflicts arise not from disagreement about findings but from uncertainty about rigor. Taking ownership of your processes reduces this uncertainty. 

The bigger picture: AI is a tool, not an author 

AI can be a helpful assistant. It can suggest alternative phrasing, flag unclear sentences, and help you tighten the structure of a manuscript. But it cannot take responsibility for the integrity of the research and the content of the manuscript. It cannot respond to replace the human effort of writing or stand behind the ethical implications of your research. Editors and reviewers expect human authors to remain at the center. Your expertise, interpretation of data, and critical evaluation of the literature are what make the work credible. When used thoughtfully, AI can improve clarity and efficiency. The key is remembering that the tool serves the researcher, not the other way around.