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<p>In light of the rapid advancement of generative AI technologies, exemplified by ChatGPT, there is growing interest in AI systems’ potential to complement, supplement, or replace traditional human managerial roles of providing work feedback to employees. This study investigated the impact of AI-driven chatbots as feedback providers on Work Engagement under varying conditions of Relational Mobility—flexibility to develop new relationships with others. Using a randomized controlled trial design, participants engaged in work-reflection sessions with ChatGPT-based chatbots programmed to provide either positive feedback (focusing on strengths) or negative feedback (focusing on improvements). The experiment recruited Japanese employees, including freelancers, with 54 participants assigned to the positive-feedback group and 48 to the negative-feedback group. The subsequent impact on Work Engagement levels was assessed with different degrees of Relational Mobility using mixed effect model analysis with R software. In environments characterized by low Relational Mobility (workplaces with fixed business relationships and limited opportunities for new relations), positive feedback from AI chatbots significantly enhanced Work Engagement. However, negative feedback showed no significant effect in either low or high Relational Mobility environments (workplaces with frequent job changes and abundant opportunities for new connections). AI-driven feedback systems demonstrate potential for improving Work Engagement under specific circumstances, even when substituting human managerial feedback. However, the findings contradict existing cultural psychology theories, which suggest negative feedback is more effective in low Relational Mobility environments. This discrepancy highlights the necessity for further research to elucidate the mechanisms by which AI-driven feedback systems enhance Work Engagement.</p>

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Enhancing work engagement through generative AI conversations: a controlled trial on the positive and negative feedback in high vs. Low relational mobility environments

  • 期刊论文

  • 发表日期：

    2025年7月2日

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  • Yasushi Watanabe,
  • Masataka Nakayama,
  • Kosuke Takemura,
  • Yukiko Uchida

摘要

In light of the rapid advancement of generative AI technologies, exemplified by ChatGPT, there is growing interest in AI systems’ potential to complement, supplement, or replace traditional human managerial roles of providing work feedback to employees. This study investigated the impact of AI-driven chatbots as feedback providers on Work Engagement under varying conditions of Relational Mobility—flexibility to develop new relationships with others. Using a randomized controlled trial design, participants engaged in work-reflection sessions with ChatGPT-based chatbots programmed to provide either positive feedback (focusing on strengths) or negative feedback (focusing on improvements). The experiment recruited Japanese employees, including freelancers, with 54 participants assigned to the positive-feedback group and 48 to the negative-feedback group. The subsequent impact on Work Engagement levels was assessed with different degrees of Relational Mobility using mixed effect model analysis with R software. In environments characterized by low Relational Mobility (workplaces with fixed business relationships and limited opportunities for new relations), positive feedback from AI chatbots significantly enhanced Work Engagement. However, negative feedback showed no significant effect in either low or high Relational Mobility environments (workplaces with frequent job changes and abundant opportunities for new connections). AI-driven feedback systems demonstrate potential for improving Work Engagement under specific circumstances, even when substituting human managerial feedback. However, the findings contradict existing cultural psychology theories, which suggest negative feedback is more effective in low Relational Mobility environments. This discrepancy highlights the necessity for further research to elucidate the mechanisms by which AI-driven feedback systems enhance Work Engagement.