The Evolution of Leadership Paradigms in the Age of Artificial Intelligence: A Grounded Theory of Human–Machine Collaborative Leadership Systems

Abstract

Objective: This study aimed to develop a grounded theory explaining how leadership paradigms evolve in organizations where artificial intelligence increasingly participates in decision-making, coordination, monitoring, learning, and strategic adaptation. Methods and Materials: This qualitative study employed a grounded theory design to explore the lived experiences of managers, senior experts, digital transformation specialists, and AI project leaders working in AI-adopting organizations in Tehran. Data were collected exclusively through semi-structured interviews. Twenty-four participants were selected through purposive and theoretical sampling, and data collection continued until theoretical saturation was achieved. Interviews focused on changes in leadership roles, human–AI interaction, decision authority, trust, accountability, ethical concerns, and emerging managerial capabilities. Interviews were transcribed verbatim and analyzed using open, axial, and selective coding with the support of NVivo software. Constant comparison, memo writing, peer checking, and participant validation were used to enhance analytical rigor. Findings: The analysis produced one core category, “human–machine collaborative leadership systems,” and four main categories: algorithmic augmentation of leadership cognition, redistribution of decision authority, relational reconstruction of trust and legitimacy, and ethical-adaptive orchestration. Participants described AI not as a simple technical tool but as a quasi-organizational actor that changes how leaders interpret information, justify decisions, communicate with employees, and govern uncertainty. The findings showed that effective AI-era leadership depends on balancing machine intelligence with human judgment, maintaining transparent accountability, protecting relational trust, and building continuous learning capabilities. Conclusion: The study suggests that leadership in the AI era is evolving from a primarily human-centered influence process toward a collaborative sociotechnical system in which leadership is distributed across human actors, algorithmic systems, organizational routines, and ethical governance mechanisms. The proposed grounded theory contributes to leadership studies by explaining how leaders preserve meaning, responsibility, and legitimacy while integrating AI into organizational decision systems.