Unlocking the Future of Education: Empirical Insights into the Adoption of Generative AI in Higher Education

This study investigates the factors influencing the adoption and use of generative AI technologies (GenAI) in higher education through a comprehensive survey of 592 university professors across the USA and Canada, using both quantitative and qualitative data. The results reveal that educators primarily benefit from using GenAI to create course materials more efficiently and enhance students’ learning outcomes. However, significant concerns persist regarding the accuracy of AI-generated content and the privacy and security of data. The qualitative analysis further identified six common themes: efficiency and time-saving, creativity and innovation, engagement with technology, support in research and learning, skepticism or uncertainty, and contextual dependency. Our findings also indicate that perceived enjoyment and performance expectancy are the most crucial drivers for adopting GenAI, whereas perceived risk substantially deters educators from integrating these technologies. Additionally, age negatively affects use and amplifies the effect of perceived risk on intention; female educators report higher intention than males, with social influence exerting a stronger positive and perceived risk a stronger negative association with intention among female educators. This research substantially contributes to the Information Systems (IS) literature by empirically examining GenAI use in higher education with a large sample size. The study not only highlights the practical benefits and risks associated with GenAI but also provides a nuanced understanding of the psychological factors influencing educators’ decisions. These findings offer actionable insights for developers to address educators’ concerns and for educational institutions to develop strategies that facilitate the effective and responsible integration of GenAI technologies in academic settings.