Leading Algorithmic Authority: Why Ethical AI Governance Depends on Legitimacy Infrastructure, Not Compliance Checklists

Abstract: Ethical AI governance has become a strategic imperative as algorithmic systems increasingly mediate consequential organizational decisions affecting credit access, service delivery, and social participation. Existing frameworks emphasize principles and technical assurance but assume stable infrastructure, coherent institutions, and baseline trust—conditions that rarely hold in volatile environments. This article reconceptualizes ethical AI governance as legitimacy infrastructure: a leadership-designed capability system enabling organizations to deploy algorithmic authority while sustaining contestability, accountability, and procedural justice when external conditions are unstable. Drawing on legitimacy theory and leadership scholarship, the article introduces a three-dimensional volatility typology—infrastructural, institutional, and socio-political—and proposes a Sensing–Stabilizing–Legitimizing (SSL) leadership framework. The analysis demonstrates that under volatility, ethical governance succeeds only when leaders institutionalize legitimacy production rather than rely on documentation alone. Organizations must build redundancy into harm detection, treat governance documentation as adaptive rather than static, and prioritize procedural justice mechanisms that make algorithmic decisions genuinely contestable. The framework offers actionable guidance for leaders navigating the dual pressures of innovation acceleration and disruption management in an era where algorithmic authority increasingly shapes organizational power.

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