<![CDATA[The rapid digital transformation has driven entertainment platforms like Netflix to adopt artificial intelligence (AI) in their recommendation systems to enhance users’ personalized experiences. Although this system can suggest relevant content, its effectiveness in meeting user expectations and sustaining long-term satisfaction still requires further examination. This study aims to analyze the impact of AI-based recommendation systems on user satisfaction and continuance intention on Netflix using the Expectation Confirmation Model (ECM). The model evaluates the relationship between expectation confirmation, perceived usefulness, satisfaction, and continuance intention. A quantitative approach was employed through survey techniques, distributing questionnaires to Netflix users in Indonesia. The collected data were analyzed using descriptive and inferential statistical methods to examine the relationships among variables. The findings reveal that the AI recommendation system significantly influences user satisfaction, mediated by perceived usefulness and expectation confirmation. These results highlight the importance of accurate and diverse recommendations in maintaining user loyalty. This research contributes theoretically to understanding the sustainable use of AI-based digital services, particularly in the context of online entertainment in Indonesia.]]>
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