Exploring the nexus of academic integrity and artificial intelligence in higher education: a bibliometric analysis

Artificial intelligence has created new opportunities in higher education, enhancing teaching and learning methods for both students and educators. However, it has also posed challenges to academic integrity. To describe the evolution of scientific production on academic integrity and artificial intelligence in higher education. A bibliometric analysis was carried out using VOSviewer software and the Bibliometrix package in R. A total of 467 documents published between 2017 and 2025, retrieved from the Web of Science database, were analyzed. The analysis reveals a rapid expansion of the field, with an annual growth rate of 71.97%, concentrated in journals specializing in education, academic ethics, and technology. The field has evolved from a focus on the use of artificial intelligence in dishonest practices to the study of its integration in higher education. Four main lines of research were identified: the impact and adoption of artificial intelligence, implications for students, academic dishonesty, and associated psychological factors. The field is at an early stage of development but is expanding rapidly, albeit with fragmented evolution, limited collaboration between research teams, and high editorial dispersion. The analysis shows a predominance of descriptive approaches, leaving room for the development of theoretical frameworks. This study provides an overview and updated of the evolution of research on artificial intelligence and academic integrity, identifying trends, collaborations, and conceptual gaps. It highlights the need to promote theoretical reflection to guide future practice and research on the ethical use of artificial intelligence in higher education.