Artificial intelligence (AI) is reshaping organizational decision-making, workforce management, and performance evaluation, creating both opportunities and challenges for contemporary leadership. Although organizations increasingly adopt AI to improve productivity, operational efficiency, and strategic decision-making, its implications for employee well-being and human-centered leadership remain complex and context dependent. This article develops an integrative conceptual analysis of how organizational leaders can introduce AI while supporting employee psychological well-being, strengthening organizational effectiveness, and maintaining ethical accountability. Drawing on foundational scholarship on AI adoption, algorithmic management, job demands and resources, self-determination, psychological safety, and AI governance, the article proposes a Human-Centered AI Leadership Integration Framework. The framework links four domains: AI and work design; leadership governance and employee participation; employee experience and well-being; and multidimensional, sustainable performance. The synthesis identifies plausible pathways through which AI may support workload management, information access, decision quality, and employee development, while also highlighting risks associated with algorithmic bias, intrusive surveillance, work intensification, job insecurity, and reduced autonomy. Because this is a conceptual review based on purposively selected sources, the framework is not presented as empirically validated and no causal effects are claimed. The article offers practical guidance for responsible implementation and sets out propositions and research priorities for future empirical investigation.
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Tony Jones Jones (2026) studied this question.
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