THE ALGORITHMIC MANAGER: EXAMINING THE MEDIATING ROLE OF PSYCHOLOGICAL SAFETY ON EMPLOYEE PERFORMANCE IN AI-MEDIATED WORK ENVIRONMENTS. - Subhan Dodo; Christanto Pratomo; Soemartono Soemartono; Chai Pao (Yayasan Adra Karima Hubbi, 2026)
Algorithmic management has become increasingly prevalent in modern workplaces, where AI-mediated systems monitor, assign, and evaluate employee tasks. The introduction of these technologies raises concerns regarding employee perceptions, engagement, and performance outcomes. Understanding how psychological safety influences employee adaptation to AI supervision is critical for designing effective and human-centered management systems. The study aims to examine the mediating role of psychological safety in the relationship between algorithmic management and employee performance. It investigates whether transparency, feedback clarity, and perceived fairness of algorithmic systems impact performance outcomes through employees’ perceptions of a psychologically safe work environment. A cross-sectional research design was employed, involving 312 employees from organizations utilizing AI-mediated management. Data were collected through validated survey instruments assessing algorithmic management exposure and psychological safety, complemented by objective performance metrics from organizational dashboards. Structural equation modeling was applied to test the hypothesized mediation effects. Findings indicate that psychological safety significantly mediates the effect of algorithmic management on both task completion and quality. Employees perceiving higher transparency and fair feedback demonstrate elevated safety, which translates into improved performance. The study underscores that AI systems must account for human perceptions to achieve sustainable productivity. Evidence from this research provides guidance for managers, system designers, and policymakers in developing AI-mediated supervision that balances efficiency with employee well-being.