Authors : Imane Ouchen; Ghizlane Chouay; Abderahmane El Arabi

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/y43jw6na

Scribd : https://tinyurl.com/mwrfntkx

DOI : https://doi.org/10.38124/ijisrt/26mar272

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Artificial intelligence (AI) is progressively becoming a fundamental part of organizational information systems, deeply influencing decision-making processes, redistribution of authority, and socio-economic outcomes. Previous literature has mainly focused on AI technology, digital transformation, and formal mechanisms of information systems governance. Yet, little consideration has been given to leadership as a governance capability, particularly in AI-enabled socio-technical systems. The issue here is that many AI-related governance failures are not primarily due to technical shortcomings but rather because of the way algorithmic outputs are interpreted, enacted, and legitimized in organizational practice. This article proposes a leadership-as-governance framework in the context of AI-enabled information systems. Based on a review of information systems literature, leadership theories, and economic perspectives, the authors depict three leadership configurations, discrete, transformational, and augmented leadership, that regulate ethical risk, innovation, and human, AI complementarity, respectively. The paper further links leadership-based governance to the quality of AI system use, decision quality, organizational innovation, and to broad socio-economic outcomes such as productivity dynamics, skill transformation, and inequality by formulating a series of research propositions derived from the framework. In this research leadership is analyzed as a multifaceted supervisory system rather than a managerial style only, therefore it contributes to the extension of information systems governance theory and aligns with the debates on responsible AI, digital transformation, and public policy. The proposed model is of great assistance to the organizations and policymakers who want to manage AI-powered information systems at least in a way that differs from the compliance-centric approaches.

Keywords : Artificial Intelligence; Information Systems Governance; Leadership; Human, AI Complementarity; Digital Transformation.

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