AI-Driven Hybrid Leadership in Health Care

Generative artificial intelligence (GenAI) is transforming healthcare leadership by shifting decision-making from hierarchical control to hybrid human–AI collaboration. This study investigates how senior healthcare and information technology (IT) executives adopt, trust, and govern GenAI within complex decision environments where algorithmic systems influence authority, accountability, and ethical oversight. The study used a mixed-methods design, combining quantitative survey data from 319 healthcare and IT leaders with 27 semi-structured executive interviews. Statistical analyses, including ANOVA (analysis of variance), regression, and factor analysis, examined relationships among digital literacy, ethical governance, and organizational trust, while thematic analysis explored leaders’ perceptions of GenAI’s agency in decision-making. Findings indicate that GenAI functions as an agentic collaborator, shaping how leaders frame problems and justify decisions. Adoption is highest among digitally fluent, mid-career executives in organizations with formal AI ethics frameworks. Trust remains conditional, depending on explainability, bias auditing, and human oversight. Ethical governance—anchored in ethics boards, explainability dashboards, and multidisciplinary review—emerges as the strongest determinant of organizational legitimacy. The study advances a hybrid-intelligence leadership model, extending transformational, complexity, and ethical leadership theories to reflect distributed authority between human and algorithmic actors. Practically, it calls for institutionalizing AI governance, expanding executive digital literacy, and embedding participatory oversight mechanisms across health systems. GenAI’s success in health care will depend less on its technical sophistication than on leaders’ capacity to govern its agency responsibly, ensuring that algorithmic innovation reinforces fairness, transparency, and trust in human-centered care.