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<p>With the rapid advancement of digital technology, a wide range of AI technologies has begun to emerge in the workplace, bringing new challenges to the management model of traditional enterprises. As end-users of digital technology, employees’ taking charge behaviors play a critical role in helping enterprises adapt effectively to AI technology. Drawing on the conservation of resources theory, this study proposes a dual path model (i.e., resource depletion path and resource gain path) to examine how AI technology application influences employees’ taking charge behavior. 506 paired data of leaders and employees were collected through a pre-survey and three-stage questionnaire survey to test the research hypotheses. The findings suggest that AI technology application can negatively affect employees’ taking charge behavior by increasing job anxiety, and positively impact employees’ taking charge behavior by increasing job autonomy. Furthermore, organizational innovation climate moderates the resource gain path of AI technology application. This study offers a novel theoretical perspective for exploring the impact of AI technology application on employees, helping enterprises effectively mitigate potential negative effects while fully leveraging the advantages of AI technology.</p>

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Resource depletion or resource gain? The impact of AI technology application on employees’ taking charge behavior

  • 期刊论文

  • 发表日期：

    2026年2月18日

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  • Haiqing Wang,
  • Long Zhang,
  • Mengting Cheng

摘要

With the rapid advancement of digital technology, a wide range of AI technologies has begun to emerge in the workplace, bringing new challenges to the management model of traditional enterprises. As end-users of digital technology, employees’ taking charge behaviors play a critical role in helping enterprises adapt effectively to AI technology. Drawing on the conservation of resources theory, this study proposes a dual path model (i.e., resource depletion path and resource gain path) to examine how AI technology application influences employees’ taking charge behavior. 506 paired data of leaders and employees were collected through a pre-survey and three-stage questionnaire survey to test the research hypotheses. The findings suggest that AI technology application can negatively affect employees’ taking charge behavior by increasing job anxiety, and positively impact employees’ taking charge behavior by increasing job autonomy. Furthermore, organizational innovation climate moderates the resource gain path of AI technology application. This study offers a novel theoretical perspective for exploring the impact of AI technology application on employees, helping enterprises effectively mitigate potential negative effects while fully leveraging the advantages of AI technology.