<![CDATA[The transformation of higher education through artificial intelligence is increasingly relevant in addressing the challenges of access, quality, and diversity of student learning needs. Although this technology promises a more adaptive and personalized learning experience, its use is still influenced by socioeconomic inequalities that create gaps in access to and perceptions of technology. This study aims to analyze how artificial intelligence, through cognitive and affective feedback, can improve students' independent learning abilities, with motivation as an intermediary variable and socioeconomic status as an external factor that influences the effectiveness of technology utilization. This study uses a quantitative approach with a cross-sectional design. The instrument, in the form of a structured questionnaire with a Likert scale, was distributed to 450 students from various universities in Indonesia. The questionnaire was compiled based on theoretical indicators from five main constructs and validated through convergent validity and construct reliability tests using outer loading and average variance extracted. The data were analyzed using partial least squares structural equation modeling to test direct and indirect causal relationships, as well as the mediating role between variables. The main results show that artificial intelligence supports students in understanding material in a structured manner and increases emotional engagement, which ultimately strengthens self-regulation and meaning-making in the learning process. Motivation was found to be a significant link between technology and learning outcomes, while socioeconomic background significantly influenced the intensity of technology use. This study concludes that artificial intelligence can be an effective and inclusive learning innovation if it is developed with consideration of cognitive, affective, motivational, and social inequality aspects in education.]]>
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