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ORIGINAL RESEARCH article

Front. Psychol.

Sec. Educational Psychology

Artificial Intelligence and Chinese university teachers' Work Performance: A Synergistic or Adversarial Relationship

Provisionally accepted
Wenhua  WenWenhua Wen1Xinyi  CaiXinyi Cai2*
  • 1Jinan University, Shenzhen, China
  • 2School of Journalism and Communication, Jinan University, Guangzhou, China

The final, formatted version of the article will be published soon.

With the widespread adoption of AI by Chinese university teachers in their work processes, an increasing number of complexes work this study aims to examine are being handled by AI. Under these circumstances, as traditional knowledge workers, Chinese university teachers may develop concerns about their career prospects, leading to negative work attitudes and pessimism, which could ultimately affect their work performance. Hence, based on the knowledge worker's perspective of relationship between leader and subordinates and through a self-administered survey, valid questionnaires were collected from 423 Chinese university teachers working in 64 Chinese universities, and partial least squares structural equation modeling (PLS-SEM) was employed for data analysis. In the result, the study reveals a negative correlation between Chinese university teachers' AI awareness and LMX, as well as a positive association between servant leadership and LMX. Furthermore, it demonstrates that Chinese university teachers' LMX is negatively related to turnover intention, which in turn shows a negative relationship with work performance. Against the background of widespread AI adoption in China, this research provides both theoretical implications and practical suggestions for managing, motivating, and inspiring Chinese university teachers to enhance their work performance and thereby improve organizational performance.

Keywords: knowledge worker, AI awareness, servant leadership, leader-member exchange, turnover intention, Work performance

Received: 04 Sep 2025; Accepted: 29 Oct 2025.

Copyright: © 2025 Wen and Cai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Xinyi Cai, cai_xy@jnu.edu.cn

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