Relational Leadership in the Age of AI: Rethinking Pedagogy for Medical Affairs

Abstract

In healthcare settings where structural change is slow and leadership is distributed across roles, the integration of artificial intelligence (AI) into leadership education introduces both promise and complexity. The current paper distinguishes between generative AI, systems that create new content and insights, and algorithmic AI, which automates predefined tasks within leadership training contexts. Yet, these tools risk embedding algorithmic bias and reinforcing Western-centric leadership ideals, raising ethical, cultural, and pedagogical concerns. The current paper examines the implications of AI-enabled leadership education through theoretical lenses, including complexity leadership, cultural dimensions theory, and relational pedagogy. It explores how AI systems reshape power within learning environments, shifting emphasis from relational mentorship to behavioral optimization. Drawing on Foucauldian concepts of discipline and visibility, the analysis shows how data-driven models may prioritize conformity over ethical discernment and reduce leadership to a technical artifact. To address these risks, the paper proposes a Relational-AI Pedagogy Model that positions AI as a supportive tool within a relational and culturally adaptive leadership education framework. This approach balances the efficiencies of AI with human judgment, mentorship, and cultural responsiveness. By integrating technological and relational strengths, the model offers a path for pharmaceutical organizations to develop KOLs who are not only scientifically credible but also ethically grounded and culturally responsive within diverse leadership contexts.