When AI Becomes the Boss: Algorithmic Management, Digital Workplace Surveillance, and AI-Induced Job Insecurity as Determinants of Employee Psychological Well-Being

Abstract

Artificial intelligence is no longer confined to decision support or task automation; it increasingly participates in the management of people. Algorithms allocate work, monitor activity, evaluate performance, recommend rewards, and shape employment expectations. These developments create an important interdisciplinary problem at the intersection of management sciences and the sociology of work: organizations may gain coordination and efficiency while employees experience intensified control, surveillance, insecurity, and a weakening of relational trust. This study develops an integrated model in which algorithmic management, digital workplace surveillance, and AI-induced job insecurity predict employee psychological well-being, with organizational trust operating as the central mediating mechanism. The framework combines Job Demands-Resources theory, Social Exchange Theory, and labor process insights to explain why technologically mediated management can become psychologically consequential. It also offers a practical governance logic for organizations adopting AI-enabled management systems: transparency, procedural safeguards, human review, proportionate monitoring, and credible reskilling commitments are likely to be as important as technical performance.