A Beginner’s Guide to Integrating AI Tools into Peer Review

Peer Review Week 2025 has the entire scholarly community in a buzz! With the theme focused on rethinking peer review in the AI era, several crucial questions need answers:  

How to use AI tools for peer review?  

What are the risks of integrating AI tools into peer review?  

What does it mean to use AI responsibly for peer review? 
Here’s a beginner’s guide to understanding AI-powered peer review and how the next generation of reviewers can utilize AI tools efficiently.

How AI Helps Peer Review

AI is meant to ease task execution in any field. And that’s how it can aid the scholarly community as well. Here’s how AI tools help peer review: 

• Streamlined workflow for the review process: Publishers receive thousands of paper submissions, making it impossible to manage the workload on their own. AI tools can come in handy in triaging research manuscripts at the initial stages of peer review. When the right tools are used, AI can help detect quality issues in papers before being sent for peer review, streamlining the process greatly.
   
• Improved reviewer feedback: Several AI systems are designed to guide novice peer reviewers to ensure that clear, actionable feedback is shared with the researchers. Studies have shown that tools like Review Feedback Agent and ReviewFlow help reviewers correct their vague comments and unprofessional remarks. The feedback provided by the tools led to 27% of reviewers reworking on their review report to provide actionable inputs to authors.
    
• Faster writing of review reports: Because large language models (LLMs) facilitate fluent writing, reviewers can enhance their reports shared with journal editors. As long as LLMs are used only to rephrase notes prepared by actual peer reviewers rather than to simply prepare the entire report, AI tools can speed up the review writing process. 

Nevertheless, AI-powered peer review is not without risks! 

What Could Go Wrong—And How to Prevent it

Journal publishers have been using AI to ease tasks like summarizing findings, checking statistics, and shortlisting peer reviewers even before LLMs became popular. But when these tools began mimicking human writing fluently, panic set in. 

Risks

• Over-automation impacts trust: Overuse of AI tools causes authors to lose confidence and trust in human expertise. Many authors worry, and rightly so, that AI tools could one day take over the peer review process and eliminate human involvement.
    
• Confidentiality concerns: There is always concern around maintaining confidentiality. Some peer reviewers may directly ask AI tools to simply review an entire paper by uploading it to the system, which could leak confidential information to chatbots.
   
• Ethical misuse: Some authors take advantage of the LLM-based review and hide prompts in the paper to avoid getting negative reviews. If publishers over-rely on AI tools and minimize human involvement, these hidden prompts could result in glowing positive reviews for papers that report flawed results and conclusions.
   
• Potential to create bias: Another ramification of AI-based peer review is that the tool may be biased towards longer papers and papers authored by prestigious scientists. The tool could overlook the novelty and nuance of the research while giving feedback.  

Despite these risks, implementing certain mitigation strategies can facilitate the responsible use of AI in peer review. 

Mitigation Strategies

• Use AI as a support tool, not as a replacement: Publishers need to be aware that AI is only meant to support and not replace humans. The tools should be designed such that boundaries are clearly maintained between AI and human peer review to enhance human judgement rather than override it.
   
• Prioritize confidentiality: External AI tools must be avoided to prevent exposing the content of unpublished research papers. Many journals and publishers have either developed or are in the process of developing in-house tools to assure authors of confidentiality.
    
• Develop clear policies and train reviewers: Clear guidelines should be established for acceptable AI use. Peer reviewers must be trained on the ethical use of AI tools and penalties must be enforced for prompt manipulation.
   
• Regularly monitor and audit AI tools: Tools are trained on datasets fed by humans. So, diverse data must be used for training AI tools and their behavior should be regularly monitored to detect—and minimize—biases and favoritism.  

Examples of AI Tools that Support Peer Review

With these best practices in mind, where exactly can AI tools support peer review?  

For publishers

Publishers use AI tools for identifying plagiarized content, both text and images, in the initial stages. Tools like Editorial Manager help journal editors check for duplicate submissions, while AI-powered platforms like Proofig AI and Imagetwin assist in detecting manipulated images.  

Journals can also develop in-house tools for fundamental checks, such as confirming whether the submission matches the journal’s accepted article types. Even assessments like data presentation and basic formatting checks can be performed using AI tools. 

For peer reviewers

AI tools must not be a peer reviewer’s go-to solution for acerating the process. However, they can use tools for identifying flaws in data analyses (e.g., Tableau and DataWrapper) or for improving their feedback reports (e.g., Review Feedback Agent and ReviewFlow). 

For authors

When submitting your paper, you want to have a final draft that meets all journal requirements to avoid desk rejection. While tools like Paperpal, Mind the Graph, R Discovery can be extremely useful in preparing your manuscripts, do not hesitate to use human expertise to get a pre-submission peer review AI and human inputs will give you submission-ready research papers for faster publication.

Why Embrace AI

With the era of AI on the rise, the research community can no longer resist its presence. We now have a chance to reshape the future of peer review. Let us build a community that benefits from AI-assisted peer reviews rather than being impaired by AI-led peer reviews! 

Want to know if your paper is ready for peer review? Get your manuscript evaluated by expert reviewers using our Pre-Submission Peer Review Service.