The integration of artificial intelligence (AI) into the higher education system has been a transformative phenomenon in recent years, reshaping traditional educational and organizational paradigms. This integration stems from the recognition of AI’s potential to optimize various aspects of higher education. Various forms of AI and the availability of vast amounts of educational data have led to the development of AI-driven insights and recommendations, thus facilitating learning, teaching, and decision-making in academia, but also challenges and concerns regarding ethics, data privacy, depersonalization of education, and faculty readiness to employ new technologies. The paper at hand aims to contribute to the broader understanding of the implications of AI adoption in higher education institutions and inform current and future research directions and practical implementations in the field. It does so by providing a state-of-the-art review of AI use in higher education, specifically focusing on current trends, use cases, and challenges in teaching, learning, and administration. The review examines relevant scientific literature published over the course of 2023 and the first quarter of 2024, indexed in the Scopus database. Reviewed literature is analyzed and categorized based on thematic similarities and key concepts from AI. The review results underline the potential of AI for changing teaching practices, facilitating informed strategic planning and decision-making among educators and policy-makers, and caution against potential ethical and social issues related to use.