AI and Big Data in the Fashion Industry: Transforming Supply Chains, Personalization, and Sustainability through Data-Driven Innovation

Abstract

Artificial intelligence and big data are no longer behind-the-scenes actors within the world of fashion—now they are the technologies that are transforming the way that fashion is designed, produced, promoted, and consumed. From algorithm-based design production and stock management forecasting to hyper-personalized marketing and analytics-driven sustainable programs, they are overturning long established industry conventions. This article discusses working applications of AI and big data across three primary areas: maximizing supply chain efficiency, individualizing individual needs with individualization of customer experience, and enabling environmental sustainability programs. It uses actual case studies, interviews with experts, and pertinent theory to explain how recommendations based on data allow companies to maximize predictability of demand, minimize overproduction, maximize utilization of resources, and create intimate relationships with consumers. It addresses emergent ethical issues surrounding higher levels of technology deployment, ranging from issues of protecting data to bias within algorithms and explaining automated functions. By so doing, it contributes to inter-disciplinary research into the digitized future of the industry and provides helpful insights for scholars and practitioners alike.