Green Manufacturing 5.0: Leveraging AI for Carbon-Neutral Industrial Growth

Abstract

The transition toward sustainable industrial practices has elevated the role of green manufacturing as a strategic imperative for reducing carbon footprints while enhancing competitiveness. With the rise of Industry 5.0, emphasis has shifted from digitalization alone to a human-centric and sustainability-oriented paradigm. This study explores how artificial intelligence (AI)-enabled technologies—including predictive maintenance, digital twins, and data-driven energy optimization—can support small and medium-sized enterprises (SMEs) in achieving carbon-neutral growth. Building on the evolution from the 3R principles (Reduce, Reuse, Recycle) to holistic sustainability frameworks, the research highlights the potential of AI in optimizing energy efficiency, reducing waste, and fostering resilient supply chains. A conceptual framework and model are proposed, linking AI adoption, green practices, carbon-neutral growth, and industrial competitiveness. Empirical analysis through SME-focused data demonstrates significant positive relationships, with results indicating that AI-enabled practices lead to measurable reductions in energy intensity and carbon emissions, while simultaneously strengthening competitiveness. Despite challenges such as limited financial resources, knowledge gaps, and infrastructure constraints, SMEs adopting AI-driven sustainability practices achieve higher performance than their counterparts. The findings bridge a crucial research gap by providing empirical evidence of AI’s role in carbon reduction within SMEs. This study contributes to the discourse on Green Manufacturing 5.0, offering both theoretical insights and practical implications for industries and policymakers seeking to balance sustainable development goals (SDGs) with industrial growth.