Interpreting intelligence: organizational meaning-making processes in AI-enabled leadership development

Purpose This study aims to examine how organizations construct shared meanings around artificial intelligence (AI) in leadership development through a symbolic interactionist lens, addressing the underexplored social and interpretive dimensions that influence implementation success. Design/methodology/approach The research uses an interpretive review of interdisciplinary literature spanning organizational behavior, leadership studies and information systems. Drawing on pragmatist thought from Blumer and Mead to contemporary scholars, the analysis identifies key mechanisms of technological meaning-making in organizational contexts. Findings Four mechanisms facilitate shared technological understanding: negotiated social construction of AI meaning, personalized symbolic interaction with AI systems, creation of new symbolic environments through virtual/augmented reality (e.g. immersive leadership simulations where avatars interact in crisis scenarios) and development of AI literacy through collective interpretation. Successful AI integration depends on organizations’ ability to facilitate collective meaning-making processes rather than technological sophistication alone. Practical implications Organizations implementing AI-enabled leadership advancement should focus on creating psychological safety zones through regular AI exploration sessions, facilitating cross-hierarchical dialogue via structured reflection protocols and establishing ethical frameworks through participatory processes. The study provides an implementation framework addressing both technical and social dimensions. Originality/value This study contributes a novel theoretical framework integrating symbolic interactionism with contemporary pragmatist thought, revealing the fundamentally social nature of technological implementation and providing context-sensitive approaches for diverse organizational settings.