ALGORITHMIC MANAGEMENT AND LEADERSHIP LEGITIMACY: EXAMINING THE IMPACT OF AI-DRIVEN DECISION-MAKING ON EMPLOYEE TRUST, WELL-BEING, AND PERFORMANCE IN PAKISTANI ORGANIZATIONS

Abstract

This study examined the impact of algorithmic management and AI-driven decision-making on leadership legitimacy, employee trust, well-being, and performance in Pakistani organizations. A quantitative, cross-sectional research design was employed, and data were collected through a structured questionnaire from employees working in organizations where AI-enabled management systems were operational. A multistage sampling technique was applied, combining purposive selection of organizations and simple random sampling of respondents. The collected data were analyzed using SPSS and SmartPLS/AMOS through descriptive statistics, correlation analysis, and regression/structural equation modeling techniques. The findings revealed that algorithmic management significantly enhanced employee performance and positively influenced perceptions of leadership legitimacy. Employee trust was found to play a critical role in strengthening these relationships. However, the results also indicated that the impact on employee well-being was comparatively weaker, suggesting potential psychological and workload-related challenges associated with AI-driven management systems. Overall, the study highlighted both the benefits and limitations of algorithmic governance in modern organizational settings. The study concludes that while AI-driven decision-making improves efficiency and performance outcomes, a balanced and human-centered approach is essential to ensure employee well-being and sustainable organizational development. The findings contribute to the growing literature on digital transformation, algorithmic management, and leadership in emerging economies