Abstract
Artificial intelligence (AI) is increasingly embedded in small- and medium-sized enterprise (SME) managerial work, reshaping decision-making, authority, and accountability. While AI–leadership research predominantly focuses on large organizations and automation outcomes, SMEs present distinct conditions characterized by resource constraints and reliance on tacit knowledge. This study develops a conceptual framework to examine how SME leaders configure AI along an automation-augmentation spectrum and how recursive AI feedback loops redistribute managerial agency and authority over time.
Drawing on distributed leadership theory, sociomateriality, and Foucauldian perspectives on algorithmic discipline, we theorize AI-augmented leadership as a co-constituted practice in which human judgment and algorithmic systems jointly shape organizational action. We propose a continuum of human-centric, hybrid, and algorithmic-centric configurations and introduce a reflexive human – AI authority model tailored to SMEs. The framework contributes to critical SME leadership and digital strategy studies, explaining how AI both constrains and amplifies managerial agency in AI-mediated organizational contexts.