Artificial Intelligence in Scholarly Publishing: Enhancing Editorial Efficiency While Preserving Human Expertise

Abstract

Use of artificial Intelligence (AI) is increasing significantly in scholarly publishing. It can potentially enhance editorial workflows and reduce the burden on reviewers. AI applications, like plagiarism detection, formatting checks, and reviewer assignment, can improve efficiency and transparency during initial manuscript processing stages. However, the peer review process extends beyond mere technical tasks. It encompasses critical evaluation that requires human expertise, contextual understanding, and ethical consideration. This review highlights the constraints of using AI in peer review while examining both present and future uses of AI in editorial activities. A fair framework has been created, and AI can assist with editorial tasks rather than replace human reviewers. Peer review's integrity, legitimacy, and constructive character depend on human judgment. This review also emphasises the mounting issues facing the traditional peer review system, such as rising submission numbers, reviewer exhaustion, and delays in decision-making. To ensure that scientific publishing upholds its exacting standards, this narrative emphasises the importance of keeping human evaluation at the centre of the review process by addressing both advantages and disadvantages of integrating AI.

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