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Artificial Intelligence (AI) influences many activities and aspects of daily life including the higher education environment. AI in education has become vital for educators and researchers. There is a rising debate regarding the positive advantages and how higher education institutions adapt to changes in the learning perspectives of students. Educators use the implementation of AI in higher education to guide teachers, improve instructional systems, and make administrative decisions that shape higher education policy. The purpose of this research is to investigate how educators and policymakers can utilize AI and adapt it to the learning aspect. A total of 351 respondents participated in an online survey, and the proposed hypotheses were evaluated using a structural equation model (SEM-PLS). The study revealed that (1) users' attitudes toward the adoption of AI are positively influenced by performance expectancy and effort expectancy, and negatively influenced by perceived risk; (2) Facilitating Conditions exert a positive influence on Effort Expectancy, but a negative influence on Behavioral Intention; (3) Users' attitudes toward the adoption of AI have a positive impact on behavioral intention; and (4) Behavioral intention positively influences the adoption of AI in higher education. The model is expected to assist policymakers in accelerating the acceptance of AI in higher education. Moreover, AI is still new and needs to be researched further by academics regarding its use in the education sector.
Helmiatin et al. (Mon,) studied this question.