<p>As generative artificial intelligence (GenAI) becomes increasingly integrated into organizational workflows, understanding its impact on employee collaboration and group decision contexts is crucial. Prior studies have largely adopted a linear view, portraying AI either as a helpful augmentation tool or a threat to human roles. In this study, we investigate a nonlinear relationship between employee-AI collaboration and employees’ perceptions of GenAI, specifically its usefulness and replaceability, within group-based work environments. Drawing on exposure effect theory, we propose and test an inverted U-shaped indirect relationship, where collaboration initially enhances perceived usefulness and, in turn, perceived replaceability, but excessive collaboration reverses this effect. Data from a two-wave multi-source field survey supports our hypotheses. Moreover, we find that task complexity and managerial support moderate these effects. By reframing employee-AI interaction as a dynamic and context-sensitive process, our study advances theory on human-AI teaming and offers insights into how GenAI shapes perceptions in group-oriented work.</p>

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Beyond the Linear Perspective: Unpacking the Inverted U-shaped Relationship between Employee-AI Collaboration and Perceptions of GenAI

  • Erica Wen Chen,
  • Duoran Liu,
  • Fan Yang,
  • Hongkun Tang,
  • Yating Wang,
  • Ben Nanfeng Luo

摘要

As generative artificial intelligence (GenAI) becomes increasingly integrated into organizational workflows, understanding its impact on employee collaboration and group decision contexts is crucial. Prior studies have largely adopted a linear view, portraying AI either as a helpful augmentation tool or a threat to human roles. In this study, we investigate a nonlinear relationship between employee-AI collaboration and employees’ perceptions of GenAI, specifically its usefulness and replaceability, within group-based work environments. Drawing on exposure effect theory, we propose and test an inverted U-shaped indirect relationship, where collaboration initially enhances perceived usefulness and, in turn, perceived replaceability, but excessive collaboration reverses this effect. Data from a two-wave multi-source field survey supports our hypotheses. Moreover, we find that task complexity and managerial support moderate these effects. By reframing employee-AI interaction as a dynamic and context-sensitive process, our study advances theory on human-AI teaming and offers insights into how GenAI shapes perceptions in group-oriented work.