Students’ intention to use artificial intelligence in business courses: an extended TAM approach in a developing economy

Abstract

Introduction: This study examines students' adoption of Artificial Intelligence (AI) in business education through an extended Technology Acceptance Model (TAM), positioning AI as an intelligent and adaptive socio-technical system rather than a conventional digital tool.

Methods: Drawing on data from 521 undergraduate business students in private universities in Cairo, Egypt, the study employs structural equation modelling to investigate the psychological, contextual, and cognitive factors of AI usage.

Results: Findings reveal that perceived usefulness and perceived ease of use remain central drivers of students' attitudes toward AI; however, AI-specific factors (including job relevance, self-efficacy, and perceived resource availability) significantly shape these perceptions. Notably, the results highlight the importance of contextual constraints in developing economies, where institutional support and access to technological resources play a critical role in facilitating AI adoption.

Discussion: By extending TAM to the context of AI-enabled learning, this study contributes to the literature by emphasizing the dual role of AI as both a technological tool and a cognitive partner in the learning process. The findings offer implications for the design of digitally enhanced curricula, particularly in emerging markets, and provide insights into how higher education institutions can better align with the demands of an AI-driven workforce.