Harnessing Big Data and AI for Supply Chain Resilience in the Garments Industry: A Comparative Analysis of Bangladesh and China

The Readymade Garments Industry of Bangladesh contributes about 80% of the export earnings and is currently positioned 2nd worldwide in exporting clothes and fabric industry. The competition within this industry is intensifying rapidly. In addition to fierce global competition labor union movements and higher-quality market demands are making it more challenging for brands to maintain their foothold. This study introduces strategies that may improve the resiliency of the supply chain in Bangladesh's Garments using AI and Big Data tools. About 3-4 case study designs are used in this study to compare the technological developments in Bangladesh's RMG industry with benchmark practices in China. Secondary sources such as case studies (HLA group, Alibaba, H&M, Zara), scholarly works, industry reports, and regulatory documents were used to gather data. The study shows China's adoption of advanced AI tools such as AI-based quality control cameras, Big Query to data analyze, blockchain platforms like Hyperledger Fabric, AI-generated digital patterns and Ethereum-based solutions, and physics-based simulators for garment modeling, which is contributing at an streamline operations, enhance transparency. On the other hand, Bangladesh has applied innovations like computer vision for quality inspections (Aamra vision by Amara technologies limited) and predictive analytics for supply chain planning and many . Development is still hampered by inadequate investment in digital technologies, a lack of qualified personnel, and inadequate infrastructure. Bangladesh's apparel and garments industry can improve supply chain resilience, lower costs, and improve compliance with international standards by giving targeted investments in AI and big data and making them a top priority. To ensure sustainability and long-term competitiveness, this study offers policymakers, governments and business executives practical suggestions for unlocking the full potential of AI and big data.