At higher education institutions (HEIs), Generative Artificial Intelligence (GenAI) tools present significant challenges. The surprise and uncertainty surrounding this technology require well-developed guidelines and ethical codes, which are currently lacking. Furthermore, teaching is likely to increasingly boost this transformative and disruptive innovation for students’ learning, necessitating a major understanding at the individual level.

This paper elaborates on the factors that encompass business students’ technology acceptance perceptions regarding GenAI and its impact on recommendations at HEIs, taking into account the moderating effect of learning commitment. We hypothesize that business students who are actively engaged in learning show a greater willingness to engage in academic activities, seek additional learning opportunities, and devote time and effort to studying and understanding key concepts in their areas of study. In this sense, students actively engaged in learning will also seek technological tools to improve their academic performance, following theories of commitment and motivation.

Our findings indicate that business students perceive both utility and ease of use as factors that develop a positive attitude toward and intention to use GenAI technology. Consequently, GenAI tools are accepted technologies that they are likely to recommend to others. Drawing on theories of commitment and motivation, business students who apply GenAI tools are motivated both intrinsically (improving technological skills or competencies) and extrinsically (better grades) in a learning environment that encourages active participation, teamwork, and knowledge sharing. Overall, this study provides insight into how learning commitment moderates the recommendation of GenAI tools at HEIs.

Keywords: Learning commitment, artificial intelligence tools, theories of commitment and motivation.