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Fashion AI across the value chain: A comprehensive literature review and future agenda

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  • Neulonbit Oh
  • Eunju Ko
  • Minjung Cho

Abstract

The fashion industry is rapidly transforming with the integration of artificial intelligence (AI). Although research on Fashion AI began in the early 2000s, scholarly and industry interest has surged in recent years, yet a comprehensive overview remains lacking. This study reviews 164 peer-reviewed articles published between 2000 and 2023 to provide a systematic understanding of Fashion AI. First, the study analyzes the major theories and variables underlying Fashion AI research. Second, a two-dimensional framework maps AI adoption across the fashion production lifecycle (pre-production, production, and post-production) and classifies AI into three types: Mechanical AI, Thinking AI, and Feeling AI. The findings reveal that AI’s role varies by both fashion production lifecycle and AI type. The study concludes that Fashion AI contributes not only to efficiency but also to consumer–brand relationships, offering consolidated theoretical perspectives and process-specific insights to advance both academic inquiry and managerial practice.

Suggested Citation

  • Neulonbit Oh & Eunju Ko & Minjung Cho, 2025. "Fashion AI across the value chain: A comprehensive literature review and future agenda," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 35(4), pages 516-538, October.
    • Handle: RePEc:taf:jgsmks:v:35:y:2025:i:4:p:516-538
    DOI: 10.1080/21639159.2025.2548816
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