Factors influencing accounting students attitudes towards AI tools in higher education using PLS SEM

This study examines the factors that influence accounting students' attitudes and intentions regarding the use of artificial intelligence (AI) tools in a developing Latin American higher education context, where AI has not yet been formally integrated into curricula. The research applies an extended technology acceptance model (TAM) to analyze how cognitive, experiential, and contextual factors determine students' evaluations of AI use. The model incorporates perceived usefulness and perceived ease of use as core beliefs of TAM, while perceived enjoyment, enabling conditions, and social influence are included as complementary contextual variables that are frequently examined in technology adoption research. Data were collected from 166 accounting students at a Peruvian university in 2024 using a structured questionnaire. The proposed relationships were tested using the partial least squares structural equation model (PLS-SEM). The results show that perceived usefulness, perceived enjoyment, and facilitating conditions significantly influence students' attitudes toward AI, explaining 75.4% of its variance. In contrast, perceived ease of use and social influence were not statistically significant predictors. Attitude toward AI use significantly determines behavioral intention, explaining 52.3% of its variance, with an acceptable model fit (SRMR = 0.064). These findings suggest that, in early-stage adoption contexts characterized by exploratory and self-directed use, students' attitudes toward AI are primarily determined by perceived value, experiential involvement, and access to technological resources, rather than normative pressures or perceived simplicity. The research offers empirical evidence regarding the integration of AI in accounting education within an emerging economy and enhances the literature on technology acceptance in higher education.