Human and AI Collaboration and Employee Productivity with Moderating Role of Job Insecurity
Abstract
The rapid integration of artificial intelligence (AI) into organizational processes has transformed how employees perform tasks and interact with technology. While AI enhances efficiency and decision-making, its impact on employee productivity remains complex and context-dependent. This study examines the relationship between human–AI collaboration and employee productivity, with job insecurity serving as a moderating variable. Using a quantitative research approach, data were collected from 250 employees working in technology-enabled organizations. Structural Equation Modeling (SEM) using SmartPLS was applied to test the hypothesized relationships. The findings indicate that human–AI collaboration has a significant positive effect on employee productivity. However, job insecurity weakens this relationship, suggesting that employees who fear job displacement are less likely to fully benefit from AI-enabled collaboration. The results highlight the importance of psychological and organizational factors in determining the success of AI adoption. The study contributes to the growing literature on human–AI interaction by integrating job insecurity as a critical contextual variable. Practically, the findings emphasize the need for organizations to address employee concerns, promote reskilling, and develop supportive work environments to maximize productivity gains from AI. The study concludes that technological advancement alone is insufficient without parallel investment in employee well-being and job security.
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