Adoption of generative artificial intelligence by university marketing students

A cross-sectional empirical study examined the determinants of Generative Artificial Intelligence (GenAI) adoption among 310 university marketing students across two Latin American institutions in Peru and Costa Rica. Applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework and Partial Least Squares Structural Equation Modeling (PLS-SEM), the research evaluates drivers influencing student integration of GenAI tools into academic settings.

This research matters because GenAI is rapidly reshaping skill requirements and educational delivery in marketing and business disciplines. Understanding empirical drivers of adoption enables academic leaders to guide emerging workforce capabilities rather than react to ad-hoc technology use. Proactive institutional alignment ensures pedagogical integrity while meeting the changing demands of technology-driven industries.

The study utilized the UTAUT2 framework to investigate factors governing academic GenAI adoption among higher education marketing students.

Forward consideration, not a verified fact.