Abstract
Artificial Intelligence (AI) increasingly performs leadership-related functions, making organizations face difficulties in sustaining collective trust and collaboration. We argue that challenges in thriving together within AI-enabled organizations cannot be explained solely by technological performance, ethical design, or governance arrangements, but stem from collective moral expectations that are unevenly applied across human and artificial authority holders. Drawing on a desk-based integrative literature review of leadership theory, moral judgment research, and studies of algorithmic management, we develop a conceptual framework explaining how divergent moral evaluation logics shape legitimacy, tolerance for error, and learning within hybrid leadership systems. We argue that when incompatible standards of accountability operate simultaneously, innovation and inclusion are constrained despite commitments to responsible AI. We clarify why AI-enabled organizations struggle to thrive together by shifting attention from individual leaders or technologies to the moral architecture of leadership evaluation.