Abstract
The transition from conventional artificial intelligence to increasingly autonomous, goal-directed, and agentic AI systems is altering not only organizational processes but also the assumptions underlying contemporary leadership theory. Transformational leadership has traditionally emphasized vision, inspiration, intellectual stimulation, and the mobilization of human followers toward organizational change. In AI-enabled organizations, however, leaders increasingly operate within hybrid systems in which artificial agents can analyze information, generate alternatives, coordinate tasks, initiate actions, and exercise bounded forms of decision autonomy. This development raises a critical question: whether established leadership styles remain sufficient when leadership involves orchestrating interactions among humans, AI systems, and organizational structures rather than influencing human followers alone. This study therefore examines the conceptual transition from transformational to agentic leadership and identifies the leadership capabilities required for organizations operating with increasingly autonomous AI.
Drawing on a structured conceptual synthesis of recent research on transformational and digital leadership, human–AI collaboration, AI-enabled decision-making, organizational transformation, and responsible AI, the study distinguishes agentic leadership from the simple use of AI by leaders. Agentic leadership is conceptualized as an emerging leadership orientation through which leaders strategically distribute agency across human and artificial actors while retaining responsibility for organizational purpose, ethical boundaries, and consequential decisions.
The analysis indicates that transformational leadership remains relevant for articulating vision, motivating employees, and enabling change, but requires extension in environments where AI participates actively in cognition, coordination, and action. Five interconnected capabilities emerge as central to agentic leadership: adaptive orchestration of human and artificial agency; dynamic allocation of decision rights; development of human–AI collaborative capability; continuous learning and strategic experimentation; and responsible governance of AI autonomy.
The study consequently proposes a conceptual progression from human-centred transformational leadership toward hybrid, agentic leadership rather than a complete replacement of established leadership theory. It argues that effective leaders in AI-enabled organizations will increasingly be evaluated not only by how effectively they influence people, but by how responsibly they configure systems of distributed intelligence and agency. The study contributes to emerging leadership research by reframing AI from a managerial support technology into an organizational actor whose increasing autonomy changes the architecture of leadership itself. Future empirical research should examine the proposed construct across industries, leadership levels, organizational cultures, and different degrees of AI-agent autonomy.
Drawing on a structured conceptual synthesis of recent research on transformational and digital leadership, human–AI collaboration, AI-enabled decision-making, organizational transformation, and responsible AI, the study distinguishes agentic leadership from the simple use of AI by leaders. Agentic leadership is conceptualized as an emerging leadership orientation through which leaders strategically distribute agency across human and artificial actors while retaining responsibility for organizational purpose, ethical boundaries, and consequential decisions.
The analysis indicates that transformational leadership remains relevant for articulating vision, motivating employees, and enabling change, but requires extension in environments where AI participates actively in cognition, coordination, and action. Five interconnected capabilities emerge as central to agentic leadership: adaptive orchestration of human and artificial agency; dynamic allocation of decision rights; development of human–AI collaborative capability; continuous learning and strategic experimentation; and responsible governance of AI autonomy.
The study consequently proposes a conceptual progression from human-centred transformational leadership toward hybrid, agentic leadership rather than a complete replacement of established leadership theory. It argues that effective leaders in AI-enabled organizations will increasingly be evaluated not only by how effectively they influence people, but by how responsibly they configure systems of distributed intelligence and agency. The study contributes to emerging leadership research by reframing AI from a managerial support technology into an organizational actor whose increasing autonomy changes the architecture of leadership itself. Future empirical research should examine the proposed construct across industries, leadership levels, organizational cultures, and different degrees of AI-agent autonomy.
Cuvinte cheie
Human–machine agency
Decision rights
Hybrid intelligence
Responsible autonomy
Organizational orchestration
Istoric articol
Publicat
31.08.2026
Informații autori
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