Algorithmic Management and Employee Outcomes: Dual Effects of Control and Capability on Autonomy and Career Security

The increasing integration of artificial intelligence (AI) into organizational processes has accelerated the adoption of algorithmic management, reshaping work structures across labor-intensive service organizations. However, empirical evidence remains limited regarding the simultaneous control-oriented and developmental dimensions of AI-enabled management systems. This study examines how algorithmic control and AI-supported skill development influence perceived autonomy and career security among employees in hospitality organizations. Data were collected from 441 employees working in hotel organizations in Bavaria, Germany. The data were analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), bootstrapped mediation analysis, and hierarchical regression. The results suggest that control-oriented and developmental dimensions of AI are associated with different aspects of employees’ work experiences. Algorithmic control was negatively associated with perceived autonomy, whereas AI-supported skill development was positively associated with both perceived autonomy and career security. Perceived autonomy did not mediate the relationships between AI-related workplace conditions and career security, and digital literacy did not moderate the relationship between algorithmic control and perceived autonomy. The study contributes to research on algorithmic management and AI-enabled workplaces by highlighting the importance of analytically distinguishing between the control-oriented and developmental dimensions of AI when examining the organizational implications of AI-enabled management.