Generative AI has undergone a profound transformation, emerging as a disruptive force comparable in scale to the advent of the internet. It has reshaped learning environments and educational processes, influencing both students' experiences and instructional approaches.
In this context of rapid change, the present systematic review investigates the role of AI in higher education, using the principles of Education 4.0 as a guiding framework for analysis. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology and is based on an evaluation of 243 peer-reviewed articles published between 2017 and 2025. It addresses three main objectives: to review existing literature, to examine the opportunities and challenges related to AI adoption, and to identify gaps that warrant further research.
A co-occurrence analysis, supported by data-driven techniques such as Latent Dirichlet Allocation (LDA), BERTopic, and K-Means clustering, shows a growing academic interest in the topic, especially after 2024. The most prominent themes include ethical governance, the personalization of learning, and the development of faculty competencies. These concerns reflect broader priorities related to fairness, transparency, and inclusive educational practices.
By contrast, areas such as statistical analysis and institutional applications have received limited attention and remain underexplored. This exploratory review contributes to a clearer understanding of the evolving role of AI in education and proposes future directions for both research and practical implementation in higher education contexts.
