ANTICIPATING THE INTEGRATION OF ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: EXPLORING ADOPTION MODELS AND PREDICTING ITS FUTURE IN MOROCCAN UNIVERSITIES

Abstract  Purpose: The emergence of artificial intelligence (AI) in many fields has shown how modern technological advances are being introduced y into the educational process of higher education institutions. In the current context, some educational institutions have exploited AI to interact with students and optimize their learning by tracking their progress (Wang, & al., 2018; Yang, 2022; Kaklauskas, 2015). This article defines artificial intelligence as an educational technology and studies this process to anticipate the future nature of the higher education system in the world, where AI becomes a part of the structure of not only higher education, but society as a whole. The objective of this study is to predict how teachers might adopt it in Moroccan universities. To do this, we drew on many adoption models and theories, including the extended Unified Theory of Acceptance and Use of Technology (UTAUT2), To explain professor's attitudes and behavioral intent toward the use of artificial intelligence in higher education Design/methodology/approach – A survey was conducted among Moroccan higher education professors to assess attitudes and behavioral intention towards the use of artificial intelligence in the education process. The questionnaire was administered online only and 98 responses were received in a 40-day period, from March 3, 2022 to April 9, 2022, using Google Forms as a medium. We adopted the structural equation modeling technique based on partial least squares (PLS-SEM) to analyze the relationship between the latent variables: perceived risk, performance expectancy, effort expectancy, facilitating conditions, behavioral intention. To this end, SmartPLS 3.0 software was used to create path diagrams and calculate the significance of factor loadings using the bootstrap technique. Findings – The main results indicate that effort expectancy and performance expectancy have a positive impact on attitude. And attitude with facilitating conditions have a positive impact on behavioral intention towards the use of artificial intelligence by higher education teachers in Morocco. Overall, the model, proved to be a better model to explain the antecedents of attitude and intention of use. In addition to the risk has no effect on the attitude towards the use of artificial intelligence by university professors. Originality/value – To the best of our knowledge, this is the first attempt of its kind to assess the role of perceived risk in examining the antecedents of attitude toward the adoption of artificial intelligence within a UTAUT model. This study examined the antecedents of attitude and behavioral intention to use artificial intelligence applications by higher education professors in the Moroccan context.