Toward effective AI leadership: a multidimensional framework for human–AI collaboration in organizations

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Purpose This study develops a comprehensive understanding of AI leadership by examining how traditional leadership theories and psychological constructs explain effective leadership behaviors in AI-intensive organizational contexts. Design/methodology/approach This study employs a systematic conceptual review, synthesizing theories from leadership studies, cognitive psychology, organizational behavior, and AI ethics to develop an integrated AI-adaptive leadership framework (Jaakkola, 2020; Torraco, 2016). Peer-reviewed literature was identified, screened and thematically synthesized across transformational, servant and ethical leadership, mapped against growth mindset, antifragility and consideration of future consequences. Findings AI leadership is inherently multidimensional, emerging from the integration of transformational, servant, and ethical leadership with growth mindset, antifragility and consideration of future consequences. Thematic synthesis identified four clusters linking these frameworks to core leadership capacities: digital innovation, responsible AI governance, adaptive resilience and long-term strategic foresight. These clusters converge into a multi-theoretical model bridging management and psychology, offering a framework for navigating human-AI collaboration and organizational transformation. Practical implications The study guides organizations in cultivating AI-ready leaders by emphasizing ethical, adaptive and human-centered competencies alongside technological foresight and learning-oriented cultures. Originality/value This research integrates leadership and psychological theories to offer a multidimensional perspective on AI leadership, bridging theoretical and practical insights not addressed in previous studies.