<![CDATA[This study aims to map trends in the use of artificial intelligence (AI) in higher education learning, examine its effectiveness, and identify key implementation challenges. A qualitative approach was employed using the Systematic Literature Review (SLR) method. Literature was collected from academic databases and platforms, including Google Scholar, Sinta, and DOAJ, covering publications from 2020 to 2025. Relevant national and international journal articles were selected using keywords related to AI, higher education, learning, effectiveness, and challenges. The selected studies were systematically analyzed through an SLR table and synthesized as primary data for the results and discussion. The findings reveal a significant increase in AI adoption, particularly generative AI, in higher education learning. AI is commonly used as a learning assistant, discussion facilitator, and support tool for assessment and academic administration. Its effectiveness is reflected in enhanced student engagement, learning autonomy, and institutional efficiency. Nevertheless, challenges persist, including ethical issues, limited AI literacy, infrastructure constraints, and the lack of adaptive regulatory frameworks. These results indicate that AI integration can improve educational quality when supported by clear policies and ethical governance.]]>
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