Leading at the algorithmic border: governing leadership boundaries in algorithmically mediated organizations

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Purpose This paper develops the concept of border-governance leadership to explain how leaders sustain adaptive order in organizations increasingly shaped by algorithms. It responds to growing calls to rethink leadership and organizational development at the interface between human judgment and digital systems. Design/methodology/approach Drawing on border theory, algorithmic governance, leadership studies, and organizational development, the paper develops a middle-range conceptual framework. It conceptualizes leadership as a cyclical process of structuring, negotiating, and reflecting through which leaders govern algorithmic boundaries. Findings The paper advances seven propositions linking transparency, participation, and reflection to organizational fairness, collaboration, and resilience. It introduces adaptive equilibrium as the dynamic condition through which organizations maintain coherence while continuously revising their algorithmic boundaries. Research limitations/implications As a conceptual study, the framework requires empirical validation. Future research may examine how these mechanisms operate across sectors such as healthcare, education, and digital services. Practical implications The framework helps leaders approach algorithms not simply as tools of control, but as evolving governance environments. It highlights the importance of ethical design, participatory dialogue, and structured reflection in supporting responsible and adaptive organizing. Originality/value This study introduces border-governance leadership as a distinct form of leadership for algorithmically mediated organizations. It reframes leadership from interpersonal influence toward the governance of boundary conditions that shape participation, discretion, and organizational learning.