<![CDATA[Artificial Intelligence (AI) has fundamentally reshaped the architecture of Information Systems (IS) within higher education institutions. This systematic literature review examines the technological transition from traditional management databases to intelligent, autonomous frameworks. By analyzing peer-reviewed studies published over the last decade, this paper identifies three major evolutionary phases: the automation of administrative tasks, the rise of adaptive learning platforms, and the integration of predictive analytics for student success. The findings highlight how AI-driven systems enhance operational efficiency and personalize student experiences while simultaneously introducing complex challenges regarding data ethics and algorithmic bias. This review provides a comprehensive synthesis of current trends, offering a strategic roadmap for educators and technologists to navigate the future of intelligent academic ecosystems.]]>
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