Adoption of generative artificial intelligence by university marketing students

The growing adoption of Generative Artificial Intelligence (GenAI) is transforming marketing education and increasing the need to understand the factors that drive its academic use among university students. This study aimed to analyze the determinants of GenAI adoption among university marketing students using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). A quantitative, explanatory, cross-sectional study was conducted with 310 marketing students from two Latin American universities in Peru and Costa Rica during the first academic semester of 2026. Participants were selected through non-probability purposive sampling. Data were collected using a structured questionnaire and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS version 4.1.1.8. The findings indicate that habit is the main determinant of both behavioral intention and actual use of GenAI tools, while hedonic motivation, facilitating conditions, and price value also show significant positive effects. Conversely, performance expectancy, effort expectancy, and social influence do not significantly influence behavioral intention. It is concluded that the adoption of GenAI among university marketing students is increasingly driven by habitual academic use rather than by traditional technology acceptance factors. These findings provide evidence to support institutional strategies for the responsible integration of GenAI into higher education.