It’s consensual that in the contemporary world, data are produced at an unprecedented speed through digital media platforms. It raises numerous opportunities but also challenges in businesses, and the higher education institutions (HEI) and their systems are not the exception. In this latter context the age of (Generative) Artificial Intelligence (AI) emerges a complementary aspect of how it can be used to support the quality of data, at the level of processes in higher education systems. To reveal the most relevant works on the use of AI to improve the quality data in higher education systems is the main purpose of this paper. To address it, a systematic literature review around the keyword’s “quality”, “artificial intelligence “or “AI” and “higher education” carried out. The study focused on works published between 2014 and 2024, on Scopus and Web of Science databases. The studies reviewed (n = 17) report the use to improve teaching and learning quality, to enhance assessment processes and to optimize educational management. They were focused on six different contexts: teaching quality enhancement, assessment and validation, quality management systems, learning analytics and behavior analysis, translation and language processing, and technological integration in education.