AI for Good: Advancing Sustainability in Smart Manufacturing

This paper examines the potential of artificial intelligence (AI) to facilitate sustainable development within smart manufacturing globally, addressing a significant literature gap. While AI clearly plays an important role in operational efficiency, its broader contribution across the manufacturing life cycle remains underexplored. Drawing on 43 expert interviews conducted between June and September 2024, four areas where AI delivers sustainability value are identified: energy optimization, predictive maintenance, sustainable supply chains, and carbon emission management. The robustness of the results is ensured by the Gioia protocol, double coding with adjudication, cross-role and cross-country triangulation, member checking, saturation, and an auditable codebook. First, the findings reveal that many small and medium-sized enterprises (SMEs) experience greater than expected efficiency gains when moving from manual to AI-based energy monitoring, exposing hidden inefficiencies. Second, a strong link between predictive maintenance and energy savings is revealed, suggesting that equipment longevity and sustainability are more tightly coupled than previously recognized. Third, AI-enabled emission tracking serves both as a compliance mechanism and as a catalyst for internal cultural change and stakeholder trust, positioning AI as a strategic governance tool. Finally, policy and managerial recommendations are provided to foster responsible AI adoption in manufacturing. A multilevel conceptual model that illustrates how AI, supported by digital and organizational enablers, contributes to sustainability outcomes and alignment with the Sustainable Development Goals (SDGs) is also presented. This research advances theory and practice by highlighting the transformative, yet still underleveraged, role of AI in sustainable manufacturing transitions.