Abstract
This systematic literature review (SLR) investigates the role of artificial intelligence (AI) in promoting sustainable practices within the apparel industry, addressing the critical need for efficient and environmentally responsible solutions in a sector facing increasing sustainability pressures. The research methodology adheres to PRISMA guidelines, encompassing a comprehensive literature search across databases such as Scopus and Web of Science for articles published between 2010 and 2024. The review process involved rigorous filtering and screening, ultimately analyzing 31 relevant journal articles. Key findings reveal that AI applications significantly enhance operational efficiency and sustainability in apparel manufacturing and supply chains. Techniques such as machine learning for demand forecasting, genetic algorithms for supply chain optimization, and computer vision for quality control are instrumental in reducing waste and improving resource utilization. Despite these advancements, challenges in implementation and scalability persist, indicating areas where further investigation is necessary. The implications of this review underscore the potential of AI to transform the apparel industry by integrating sustainable practices into core operations. However, notable research gaps remain, particularly regarding the ethical implications of AI adoption, its impact on labour practices, and the need for interdisciplinary approaches that bridge technology with environmental sustainability. Future research directions should focus on developing innovative AI methodologies tailored to sustainability challenges, examining the socio-economic impacts of AI on labour within the apparel sector, and enhancing collaboration between academia and industry to foster practical applications of AI technologies. This SLR not only contributes to academic discourse but also serves as a valuable resource for practitioners seeking to implement sustainable practices through AI in the apparel industry.
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