Balancing generative AI integration and faculty well-being: evidence from Chinese higher education

Abstract

Introduction The rapid integration of generative artificial intelligence (AI) tools such as ChatGPT and DeepSeek is transforming higher education, yet limited attention has been paid to their effects on faculty well-being. This study addresses this gap by examining how technology acceptance and emotional factors shape university teachers’ adoption of DeepSeek and its subsequent impact on stress, happiness, and energy. Methods A cross-sectional survey was conducted among 711 faculty members from Chinese universities between January and February 2025. Data were analyzed using covariance-based structural equation modeling (CB-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to capture both linear and configurational relationships among variables. Results Findings show that perceived usefulness, ease of use, and enjoyment significantly predict DeepSeek adoption. Adoption, in turn, is associated with increased happiness and reduced stress but shows no significant effect on faculty energy. The combination of TAM and fsQCA approaches revealed multiple sufficient pathways leading to positive well-being outcomes, emphasizing the importance of usability and hedonic motivation. Discussion The study extends the Technology Acceptance Model by incorporating emotional and contextual drivers of adoption. It suggests that universities should strengthen training, usability design, and workload management policies to balance innovation with faculty well-being.

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