Leading Innovation Using Artificial Intelligence in Higher Education Institutions: A Systematic Review to Analyze Strategies and Challenges

Abstract

This study aimed to explore how artificial intelligence (AI) can be utilized to drive innovation in higher education institutions. The study adopted a systematic review methodology of relevant scientific literature published during the period from 2018 to 2024, using databases such as Scopus, ScienceDirect, and SpringerLink. A total of 15 studies were reviewed. The findings revealed that AI supports innovation through tools such as adaptive learning systems, predictive data analytics, and administrative automation, which contribute to enhancing efficiency and improving educational outcomes. However, higher education institutions face challenges, including insufficient infrastructure, lack of regulatory frameworks, and issues related to privacy and algorithmic bias. The study concluded with the importance of developing technological infrastructure that aligns with AI requirements, establishing comprehensive regulatory frameworks to ensure the effective and responsible use of intelligent technologies, and providing training programs for leaders and faculty members to enable them to maximize the potential benefits of these technological advancements.