AI-ASSISTED PEER-REVIEW, AI-ASSISTED EDITORIAL DECISION-MAKING AND PUBLISHING QUALITY OF SCHOLARLY JOURNALS IN FEDERAL UNIVERSITIES IN SOUTHWESTERN NIGERIA

This study examined how AI-assisted peer-review and AI-assisted editorial decision-making affect the publishing quality of scholarly journals published at Federal Universities in Southwestern Nigeria. This study was based on Socio-Technical Systems Theory and used a cross sectional survey research design. The target population was 420 editors, managing editors, editorial board members, journal managers and university publishers in selected Federal Universities of Southwestern Nigeria. The sample size for this research was 205 respondents. The data instrument was a structured questionnaire with a 5-point Likert scale. Face and content validation were used to validate the instrument and Cronbach's Alpha coefficients were used to achieve the acceptable level of reliability (above 0.70). Descriptive statistics were used to analyse the research questions, while simple linear regression was used to test the hypotheses at 0.05 level of significance. The results showed that both AI-assisted peer-review and AI-assisted editorial decision-making had a high positive impact on publishing quality; and that both together had the highest influence. Regression analysis also revealed that AI-assisted peer-review and AI-assisted editorial decision-making significantly predicted publishing quality. The study reveals that AI has the potential to improve the efficiency of the editorial process, bolster research integrity and contribute to the quality of published work in the field. It recommends responsible use of AI tools, integration of AI into scholarly publishing and implementing institutional AI governance mechanisms to enhance the quality of scholarly communications in universities in Nigeria