Artificial Intelligence assimilation and University Service Quality: The Mediating Role of student satisfaction

Purpose: This study investigates how artificial intelligence (AI) assimilation influences students’ perception of university service quality (USQ), considering student satisfaction (SS) as a mediating factor. Methodology: A quantitative research design was applied. Data were collected through a Likert-scale questionnaire administered to students from Botswana Open University and the National Open University of Nigeria. Structural Equation Modelling (SEM) using Smart PLS was employed for hypothesis testing. Findings: The results confirm that AI assimilation significantly influences students’ perception of university service quality. Moreover, student satisfaction partially mediates the relationship between AI assimilation and USQ, indicating its essential role in successful AI integration in higher education. Originality/Contribution: The study offers empirical evidence on the mediating effect of student satisfaction in the AI assimilation–USQ nexus within the context of developing countries. It contributes to theoretical understanding and provides practical insights for institutions aiming to improve service quality via responsible AI use. Practical Implications: Universities are encouraged to invest in AI tools that enhance personalized services, administrative efficiency, and student engagement, while simultaneously addressing student concerns related to critical thinking and autonomy. Limitations: The study is limited to two universities and adopts a cross-sectional approach, suggesting the need for longitudinal and broader studies.