With the advent of Education 4.0, the integration of Artificial Intelligence (AI) into higher education has become increasingly prevalent, reflecting the pervasive influence of digital technologies in contemporary educational paradigms. In light of this transformative shift, this conceptual article proposes a comprehensive investigation into the adoption of AI among undergraduate students in higher education institutions. Drawing upon the robust theoretical framework of The Unified Theory of Acceptance and Use of Technology (UTAUT), this study aims to elucidate the intricate interplay between key variables within the UTAUT Model—namely, performance expectation, effort expectation, social influence, and facilitating conditions—on students' attitudes and behavioural intentions toward AI adoption in their educational endeavours. By employing a quantitative research design, this study will leverage Structural Equation Modelling - Partial Least Squares (SEM-PLS) to rigorously analyse the gathered data. Such an inquiry is pivotal as it endeavours to uncover and comprehend the nuanced dynamics of AI adoption tendencies among students, thereby enabling educational institutions to proactively address potential challenges and capitalise on emerging opportunities associated with the integration of AI. Moreover, this study seeks to foster a nuanced discourse on the potential linkages between the aforementioned variables prior to empirical testing, thereby enriching the scholarly discourse surrounding AI adoption in higher education.
