AI’s integration into academic research has prompted a reevaluation of traditional peer-review processes. This paper delves into the significance of peer review in mass communication research and explores AI’s role in enhancing its efficiency. It outlines objectives centered around AI-based tools for manuscript screening, improving peer-review efficiency, ethical implications, challenges, case studies, and recommendations. Automated plagiarism detection, identifying research misconduct, and analyzing methodological rigor are highlighted as AI’s contributions to assessment and screening. Efforts to streamline peer-review processes include AI-assisted reviewer matching, communication facilitation, and expedited editorial triaging. Ethical concerns encompass AI bias, academic freedom implications, and data privacy issues. Challenges such as ensuring transparency and addressing resistance are discussed alongside case studies illustrating AI applications and their impact on research quality. The paper concludes by summarizing key findings, emphasizing AI’s potential to enhance research quality, and urging consideration of ethical dimensions in peer review.

Priyam Verma, Research Scholar,, School of Media and Communication Studies, Galgotias University

Click here for the full paper