Artificial Intelligence Adoption in Sustainable Manufacturing: A Systematic Review of Antecedents, Mediators, Moderators, and Outcomes

ABSTRACT Artificial intelligence (AI) is increasingly expected to help manufacturing firms improve efficiency and achieve sustainability goals, yet the existing literature remains fragmented and offers limited understanding of what drives AI adoption, how it is implemented, and what outcomes it creates. To address this gap, this study conducts a systematic literature review of 78 peer‐reviewed articles published between 2015 and 2025 on AI adoption in sustainable manufacturing. The results show that AI adoption is influenced by technological, organizational, environmental, and individual factors. The findings also indicate that the relationship between AI adoption and sustainability outcomes is shaped by mediating and moderating factors. Based on the review, this study develops a framework linking AI adoption with organizational and strategic sustainability outcomes. It also highlights key research gaps and proposes future research directions. The study concludes that AI can contribute to sustainable manufacturing, but its success depends on the conditions under which it is adopted and used.