Legitimacy Under Algorithmic Authority: A Relational Diagnostic of Leadership Education in AI-Mediated Contexts

As algorithmic systems become embedded in leadership development, evaluation, and recognition, they increasingly shape how authority is formed and justified. This manuscript argues algorithmic authority poses a legitimacy challenge for leadership education, especially when judgment is co-produced by humans and systems. It introduces the Surface-Cultural-Institutional-Systemic (SCIS) framework as a diagnostic lens for examining how legitimacy is configured, misaligned, or strained within hybrid authority systems. Rather than prescribing AI use or attributing legitimacy to algorithmic systems, I position leadership education as a formative but bounded site for cultivating conceptual readiness to interpret legitimacy as relational, contested, and mediated.