Leadership in Autonomous Organizations: Exploring New Managerial Roles in AI-Based Work Systems
Keywords:
autonomous organizations, artificial intelligence, AI-based work systems, algorithmic management, digital leadership, human–AI collaboration, qualitative research; managerial rolesAbstract
This study aimed to explore how leadership roles are reconstructed in autonomous organizations where AI-based work systems participate in task allocation, workflow coordination, decision support, performance monitoring, and managerial control. A qualitative interpretive design was used to examine managerial experiences in AI-enabled organizations in Tehran. Data were collected through semi-structured interviews with 24 participants, including senior managers, middle managers, HR managers, AI project leaders, operations supervisors, and data-oriented decision makers who had direct experience with AI-based work systems. Participants were selected through purposive and snowball sampling. Interviews continued until theoretical saturation was achieved, with saturation reached after the twenty-first interview and confirmed through three additional interviews. All interviews were audio-recorded with consent, transcribed verbatim, and analyzed using thematic analysis. NVivo software was used to organize transcripts, generate initial codes, compare patterns, and develop final themes. Credibility was strengthened through member checking, peer review, and repeated comparison between codes and interview excerpts. The analysis identified five main categories that explain the changing nature of leadership in autonomous organizations: algorithmic orchestration of work, managerial sensemaking in AI-mediated decisions, human-centered trust and transparency building, capability development for human–AI collaboration, and ethical governance of autonomous systems. Participants described leadership as shifting from direct supervision to system calibration, exception handling, interpretive judgment, employee protection, and continuous learning. While AI improved speed, prediction, coordination, and operational consistency, managers emphasized that human leadership remained essential for contextual interpretation, ethical accountability, conflict resolution, and maintaining organizational meaning. The findings suggest that AI-based work systems do not eliminate leadership but transform its core functions. In autonomous organizations, effective leaders act as orchestrators, interpreters, trust builders, capability architects, and ethical governors who align algorithmic efficiency with human judgment, employee agency, and organizational responsibility.
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