Academic transformation in the era of artificial intelligence: drivers of university faculty adoption of GenAI based on the UTAUT model

Generative Artificial Intelligence (GenAI) technology is reshaping the traditional paradigms of research and teaching, with “AI for Science” and “AI-Enabled Education” profoundly transforming contemporary higher education. As the central force driving research innovation and education, university faculty members’ willingness to adopt GenAI technology is critical to educational innovation. This study employs the Unified Theory of Acceptance and Use of Technology (UTAUT), incorporating GenAI literacy and usage attitudes, and utilizes structural equation modeling to explore the key factors influencing faculty members’ intention to use GenAI technology in research and teaching contexts. A total of 238 valid responses were collected from university teachers. The findings reveal that: first, performance expectancy and usage attitudes within the UTAUT model significantly and positively impact faculty members’ usage intention, highlighting the importance of perceived benefits and personal attitudes in the technology acceptance process; second, faculty members’ overall level of GenAI literacy significantly and positively affects their attitudes toward GenAI technology, indicating that enhancing their GenAI literacy- as reflected in technical proficiency, critical evaluation, communication proficiency, creative application- is crucial for forming positive attitudes; and third, usage attitudes serve as a mediating factor, fully mediating the effect of GenAI literacy on usage intention, emphasizing the central role of positive attitudes in technology adoption. Based on these findings, this study provides theoretical and practical guidance for promoting GenAI technology in universities, suggesting that institutions should prioritize cultivating faculty members’ GenAI literacy and shaping positive attitudes toward technology to enhance their willingness to adopt it. Furthermore, the study offers new perspectives and frameworks for future research on the application of GenAI technology in education.