Reframing artificial intelligence as an observable market signal: Extending Signaling Theory in luxury fashion retail

Artificial intelligence is transforming luxury fashion retail; however, existing research primarily views AI as an operational technology that enhances efficiency and personalization. Less attention has been given to how consumers interpret AI-enabled marketing applications as signals of luxury brand meaning. Drawing on Signaling Theory, this study conceptualizes AI-enabled marketing applications as market signals through which consumers infer luxury brand attributes. Using a multi-method design comprising survey-based structural equation modeling ( n = 362), exploratory consumer segmentation ( n = 101), and sentiment analysis of 193 online reviews, the study examines how AI shapes perceptions of exclusivity, authenticity, innovation, and responsiveness and how these perceptions influence luxury brand performance. The findings reveal that AI-enabled marketing applications do not show a statistically significant direct effect on brand performance; instead, their effects operate through these four signaling dimensions. The exploratory segmentation identifies three consumer profiles with different signaling perceptions, while sentiment analysis reveals generally positive evaluations alongside concerns about excessive automation and diminished human interaction. The study extends Signaling Theory by positioning AI-enabled marketing applications as market signals through which technological capabilities acquire symbolic brand value. Managerially, the findings suggest that luxury brands should deploy AI strategically to reinforce symbolic value while preserving exclusivity and authenticity.