As higher education institutions (HEIs) work to create environments that are committed to continuous improvement and accountability, Artificial Intelligence (AI) is proving to be one of the most powerful technologies in quality assurance (QA) and accreditation. Within the scope of AI application in this sector, this study undertakes a bibliometric analysis of 43 academic publications concerning higher education QA over the period 2004–2024, utilizing the Scopus database. The analysis is conducted considering the trends, themes about the subject area used in studies, statistics about relevant citations, co-authorship, and keyword co-occurrence, using programs like VOSviewer and BiblioMagika. The findings suggest a significant escalation of research activity since 2015, with significant interdisciplinary cooperation from computer science, social sciences to engineering. China, India, the UK and the US ranked highest overall publishing output, and the first contributions of first publications come from countries such as Malaysia and other Southeast Asian countries. Areas of focus might be predictive analytics, teaching evaluation, feedback analysis for students, AI-facilitated decision support systems, and other areas. It has therefore presented a bibliometric perspective with tactical significance for scholars, policy makers, as well as institution leaders who wish to exploit AI in higher education to improved education quality and to institutional accountability. It also promotes more international collaboration, location-specific design for AI, and research that links technological advancement to educational policy and practice.