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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Taste and temporality: The rise of AI trend forecasting

Gwyneth Holland
Fashion Style & Popular Culture
Fashion and Cultural Textiles
article

Taste and temporality: The rise of AI trend forecasting

Gwyneth Holland
article en

Abstract

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.

Fashion Style & Popular Culture
University of Westminster (GB)
Openalex Percentile: Top 69%
Fashion and Cultural Textiles
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Taste and temporality: The rise of AI trend forecasting — Gwyneth Holland · Fashion Style & Popular Culture (2025) | TGRS Research Map | TGRS