The adoption of artificial intelligence and automation in the workplace has the potential to improve efficiency while also influencing employees’ psychological and behavioral responses. Although reskilling training is expected to support employee adaptation to technological change, its effectiveness in shaping employee responses toward AI-driven transformation remains unclear. This study examines the direct effect of artificial intelligence integration on turnover intention, the mediating role of technostress, and the moderating role of reskilling training. A quantitative approach was employed using Structural Equation Modeling with SmartPLS 4. Data were collected through an online survey involving 265 employees working in organizations that had adopted artificial intelligence and automation technologies. The results showed that artificial intelligence integration had a significant positive effect on turnover intention, while its effect on technostress was positive but statistically insignificant. Furthermore, technostress did not significantly mediate the relationship between artificial intelligence integration and turnover intention. Reskilling training also did not significantly moderate the relationship between artificial intelligence integration and turnover intention or between technostress and turnover intention. These findings indicate that AI integration may influence turnover intention through mechanisms beyond technological strain, while reskilling training alone was not empirically confirmed as a significant buffering resource in this research context. This study contributes to the AI and employee management literature by highlighting the complexity of employee responses to AI-integrated workplaces and emphasizing the importance of broader organizational support strategies in managing technological transformation.
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