The past year has seen revolutionary breakthroughs in the development of artificial intelligence-based (AI) products that can impact almost every aspect of life. The change raises the question of the sustainability of education and how technology will transform the way we currently teach. This study aims to develop a model and its hypothetical adaptation that can be used to analyse the adoption and use of artificial intelligence in university settings. The importance of AI in education can be captured in its ability to personalise learning pathways, improve teaching methods and automate related administrative tasks. AI technologies are able to adapt to the needs of individual learners, providing personalised instruction and improving learning outcomes. AI can also help educators by automating routine tasks, allowing them to focus on individualised instruction and create a more engaging and effective learning environment. Based on the accepted results of exploratory factor analysis as the applied method of this paper, the research concludes that the model adaptation is feasible, but it is worth considering changing the variable reflecting implementation to one that is accepted by educators as the concrete institutional implementation of AI is still a very distant scenario in higher education. Future research should incorporate these findings into the design of possible structural models, as this area of AI research has the potential to bring significant social science and educational benefits.