Considering the proliferation of artificial intelligence (AI) technologies, it has become crucial to integrate AI-related knowledge and skills education into business management curricula. This is a significant concern for both academics and practitioners. However, in the context of university business management education, few studies have investigated the relevant factors that affect individuals' behavioral intention to learn AI knowledge and skills. This study develops a preliminary conceptual model of AI knowledge/skills learning behavior by integrating insights from AI education research within the context of university business management education. This study validates business management students' behavioral intention to learn AI knowledge and skills from the perspectives of AI self-efficacy, AI anxiety, perceived usefulness, curiosity, joy, and control, based on an integrated perspective of the hedonic-motivation system adoption model (HMSAM) and individual differences. This research investigates a theoretical model via a cross-sectional survey, collecting data from 230 business management students in higher education institutions. The analysis is conducted using the partial least squares (PLS) method. The findings indicate that perceived usefulness, curiosity, and control influence behavioral intention to learn AI knowledge and skills. AI self-efficacy positively correlates with perceived usefulness, curiosity, joy, and control. Additionally, AI anxiety is positively associated with perceived usefulness and curiosity. The results of this study expand our understanding of the relationship between the learning behavior of business management students in the context of AI knowledge/skills and AI education. Additionally, this study provides significant theoretical and practical implications for enhancing the advancement, teaching, learning and evaluation of AI education in higher education settings.