AI adoption in Chinese universities: Insights, challenges, and opportunities from academic leaders - Xibing Wang; Shuli Zhao; Xiaoshu Xu; Huanhuan Zhang; Vivian Ngan-Lin Lei (Acta Psychologica)
This study explores the perceptions, challenges, and strategies related to the integration of Artificial Intelligence (AI) in Chinese higher education from the perspective of academic leaders. Through semi-structured interviews with 20 academic leaders from eight Chinese universities and guided by the Diffusion of Innovation (DOI) and Transformational Leadership (TEL) theories, the study identifies the initial adoption of AI in administrative tasks and student services, but slower integration into core educational functions such as teaching and research. Key challenges include a lack of digital literacy and resistance to AI among faculty, which hinder deeper integration. Additionally, resource allocation, funding constraints, and concerns over data privacy and security present significant barriers. Academic leaders recommend enhancing digital literacy, offering ongoing professional development, and implementing supportive policies for AI adoption. While optimistic about AI's potential in personalized learning and resource optimization, they stress the importance of ensuring ethical and equitable AI use. The study suggests future research on AI's long-term educational impact, policy effectiveness, and its integration across disciplines. This research offers valuable insights into the challenges of AI integration in Chinese higher education and provides practical guidance for its global application.