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AI-Induced Job Anxiety and the Perceived Effectiveness of AI-Enabled ESG Initiatives: Evidence from Bank Employees

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  • Bowon Kim

    (College of Business, KAIST, Seoul 02455, Republic of Korea)

Abstract

Artificial intelligence (AI) is increasingly integrated into corporate Environmental, Social, and Governance (ESG) strategies, yet employees’ psychological responses to this transformation remain underexplored. This study examines how AI-induced job anxiety influences employees’ evaluations of AI’s role in supporting ESG initiatives. Drawing on Challenge–Hindrance Stressor Theory and cognitive appraisal perspectives, we propose that technological anxiety may function as a cognitive–evaluative signal rather than merely a barrier to adoption. Using survey data from 858 employees of a major commercial bank, we test a structural equation model distinguishing cognitive appraisal from motivational and learning pathways. The results reveal a paradox: AI-induced job anxiety is positively associated with employees’ perceptions of AI’s effectiveness in ESG implementation (Estimate = 0.195, p < 0.001) but does not significantly increase intrinsic motivation or knowledge acquisition in either AI or ESG domains. Instead, employee motivation remains the primary driver of knowledge development. Our findings suggest that prior literature may have conflated attentional activation with behavioral adaptation. While anxiety can heighten cognitive vigilance, it does not necessarily provide the motivational or psychological resources required for knowledge acquisition.

Suggested Citation

  • Bowon Kim, 2026. "AI-Induced Job Anxiety and the Perceived Effectiveness of AI-Enabled ESG Initiatives: Evidence from Bank Employees," Sustainability, MDPI, vol. 18(9), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:18:y:2026:i:9:p:4353-:d:1930576
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