Artificial Intelligence (AI) systems are now widely applied across different domains. As AI systems increasingly shape professional and academic domains, there is a growing need to pre-pare future professionals to work with these technologies responsibly and effectively. Accordingly, an increasing number of studies advocate AI education for undergraduates across disciplines. However, there is limited qualitative research on these students’ motivations for learning about AI and on what they are interested in learning, despite the importance of such understanding for designing motivating, engaging, and effective learning experiences. Therefore, the objective of this research is to answer the following two research questions: (1) What motivates undergraduates across disciplines to learn about AI? (2) What are undergraduates across disciplines interested in learning about AI? To answer the research questions, we conducted a survey with 128 students who voluntarily enrolled in an elective introductory AI course over three semesters. The findings indicate that these students are motivated to learn about AI not only for career-related utility but also due to its perceived societal relevance and ethical implications. Regarding learning interests, students most frequently expressed interest in learning how AI systems work, how these systems impact society positively and negatively, and how to use them effectively and responsibly. In the discussion section, we provide guidance on how these results can inform the design or adaptation of AI curricula, course invitations, and learning experiences to foster sustained engagement and meaningful learning among these students.