<![CDATA[Digital transformation in educational management demands a more adaptive, accurate, and data-driven evaluation system. Artificial Intelligence (AI) holds great potential to transform learning evaluation from a mere academic assessment to a strategic tool for institutional decision-making. This article aims to explore the role of AI in educational evaluation and managerial strategies required for its adaptive and contextual adoption. Using a qualitative literature review approach from accredited journal sources, the study finds that AI has been implemented in various forms such as computerized adaptive testing, NLP-based essay scoring, student character monitoring, and predictive decision-support systems. However, structural barriers such as limited infrastructure, low digital competence, and lack of technical regulation hinder widespread adoption. Effective managerial strategies must include digital leadership, structured implementation roadmaps, data literacy, ethical governance, and locally participatory approaches. The article concludes that AI integration in learning evaluation must be guided by the Technology Acceptance Model (TAM) and Data-Driven Decision Making (DDDM) frameworks to truly enhance education quality.]]>
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