Taste and temporality: The rise of AI trend forecasting
This article critically examines the emerging role of artificial intelligence (AI) in the field of fashion trend forecasting, focusing on how machine-learning technologies reshape the aesthetic and commercial dimensions of predicting style. Drawing from fashion studies, philosophy and management studies, this article interrogates the shift from qualitative, expert-led trend forecasting to data-driven, predictive systems that claim to map and anticipate consumer taste at scale. It explores how these systems function not only as tools of prediction but also as producers of cultural meaning, taste hierarchies and aesthetic norms. The article offers a new perspective on AI forecasting in the academy, which has thus far focused on its technical aspects. By analysing AI fashion trend platforms, I explore a critical framework for understanding the implications of AI-driven trend forecasting in both commercial and cultural contexts.
Authors
- Gwyneth Holland (ORCID: https://orcid.org/0009-0001-0247-8441)
Institutions
- University of Westminster (GB)
Publication Details
- Journal
- Fashion Style & Popular Culture
- Published
- 2025-11-07
- DOI
- https://doi.org/10.1386/fspc_00360_1
- Primary Topic
- Fashion and Cultural Textiles
- Type
- article
- Field-Weighted Citation Impact
- 0.00