Textile and Apparel Industries

Understanding Fashion AI Evolution: A Systematic Literature Review of AI Research in the Fashion Industry

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Abstract

 This study systematically reviews the evolution and applications of Artificial Intelligence (AI) in the fashion industry, highlighting its transformative impact across supply chain functions such as design, manufacturing, consumer behavior, and e-commerce. Leveraging Ha-Brookshire's (2014) C&T Supply Chain Research Model, it categorizes AI research into three areas: datasets, simple tasks (e.g., object detection, fine-tuning models), and comprehensive tasks (e.g., virtual try-ons, trend forecasting, and multimodal recommendation systems).

The analysis of 88 articles, spanning 2022-2023, identifies advancements in AI applications such as computer vision, natural language processing, and machine learning, focusing on efficiency and cost-effectiveness. Key findings reveal a significant shift toward industry-driven research, with commercial applications increasingly shaping AI developments. However, gaps persist in addressing AI's societal, ethical, and sustainability impacts within fashion.

This study underscores the need for academia to explore AI's broader implications, offering insights for future research that bridges technology, industry needs, and sustainable practices.

Keywords: AI research, fashion

How to Cite:

Liu, Y. J. & Zhao, L., (2025) “Understanding Fashion AI Evolution: A Systematic Literature Review of AI Research in the Fashion Industry”, International Textile and Apparel Association Annual Conference Proceedings 81(1). doi: https://doi.org/10.31274/itaa.18555