Keyword: peer-review process

ABSTRACT: Peer review is important in maintaining the quality of scholarly publishing, but the process faces challenges such as shortage of reviewers, delays, inconsistent judgements, and overlooked errors. These challenges have increased the need to consider the appropriate use of artificial intelligence (AI) in peer review. Completely excluding AI or allowing it to function as an autonomous reviewer may not adequately address these problems. A Human–AI Augmented Review model is therefore proposed, in which AI supports clearly defined tasks under human supervision, while reviewers and editors retain responsibility for interpretation, ethical judgement, and editorial decisions. Peer review involves both routine technical checks and complex scholarly evaluation. AI can assist with repetitive and rule-based tasks such as manuscript screening, consistency checking, reviewer identification, and identification of reporting gaps. Human reviewers are still needed to assess methodology, scholarly contribution, and ethical issues. Effective use of AI requires a clear division of responsibilities, verification points within the review process, and governance measures to address bias, hallucinations, confidentiality, and excessive reliance on automation. Careful and limited use of AI can improve efficiency and reduce avoidable errors while maintaining accountability and trust in peer review.