AI-Driven Sustainability in Industry 5.0: The Role of Responsible Leadership

Abstract

Abstract As Industry 5.0 advances, artificial intelligence (AI) is increasingly positioned as a driver of sustainability in knowledge-based economies; however, empirical outcomes remain uneven and frequently symbolic. Addressing this paradox, this paper examines AI-driven sustainability through the lens of knowledge creation, governance, and application, rather than technological capability alone. Using a Critical Interpretive Synthesis, the paper systematically analyses interdisciplinary literature on AI, Industry 5.0, sustainability, and leadership to move beyond descriptive aggregation toward theory development. The findings reconceptualise AI as a knowledge infrastructure whose sustainability value depends on how AI-generated knowledge is governed, interpreted, and applied across systems. The paper further advances theory by reframing responsible leadership as a knowledge-governance mechanism, explaining how leadership shapes the prioritisation and diffusion of AI-enabled knowledge across micro (individual), meso (organisational/industry), and macro (institutional) levels. Building on these insights, the paper develops an integrative framework that explains why AI-enabled sustainability initiatives often result in performative environmental, social, and governance (ESG) compliance rather than substantive environmental and social impact. By linking responsible leadership with AI knowledge governance, the paper contributes to the knowledge-economy literature by explaining variability in sustainability outcomes beyond technological adoption. The paper concludes by outlining implications for organisational governance and identifying directions for future empirical research to test and extend the proposed framework.