<![CDATA[The rapid development of generative AI (GenAI), such as ChatGPT, brought both opportunities and challenges to higher education. Although the government had issued guidelines for GenAI usage, many universities still lacked concrete policies at the institutional level. This study aimed to examine the factors contributing to the acceptance of ChatGPT in academic contexts using the UTAUT model as a basis for policy formulation. A quantitative approach was employed, involving 326 undergraduate students from a private university in Jakarta. Data were analyzed using PLS-SEM to assess the contributions of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions in predicting Behavioral Intention (R² = 0.871, p < 0.05) and Actual Use (R² = 0.869, p < 0.05). Performance Expectancy (β = 0.550, p < 0.05) emerged as the strongest predictor, indicating that students had experienced tangible benefits from using ChatGPT. These findings suggested that a complete ban on AI use was not advisable. However, Social Influence (β = 0.191, p < 0.05) and Facilitating Conditions (β = 0.210, p < 0.05) were the weakest contributors, reflecting that AI had not yet been fully integrated into learning practices. The influence of peers and lecturers also remained insufficient in encouraging ChatGPT use. Therefore, universities were encouraged to develop clear guidelines, supportive infrastructure, and concrete policies to meaningfully integrate AI into educational practices. The findings of this study provided an empirical foundation for developing student-centered AI policies in higher education.]]>
