Can AI-Generated Marketing Content Be Translated into Purchase Intention? Examining Gen Z Responses to AI-Generated Fashion Content

This study aims to explore how AI-generated fashion marketing content can influence purchase intention, whereas previous research has focused more on the outcomes of AI-generated content (AIGC) related to AI disclosure, consumer engagement, and advertising efficiency. In fact, the use of AIGC in the fashion industry is a highly effective business strategy that can reduce costs and enhance purchase intention. The method used was a quantitative approach applying Structural Equation Modeling (SEM), utilizing non-probability sampling with a focus on Generation Z. Data collection was conducted in Indonesia from June to July 2026. The data analysis results using SmartPLS 4 indicate that all hypotheses have a significant effect, showing that purchase intention can increase in line with the attitude toward AIGC, which is influenced by information quality, authenticity, and perceived anthropomorphism. Additionally, Brand Trust acts as a mediating variable between attitude towards AIGC and purchase intention, which ultimately affects purchase intention. The findings suggest that the most effective strategy when utilizing AIGC is to prioritize information quality, authenticity, and perceived anthropomorphism. Keywords— AI-Generated Content, Purchase Intention, Brand Trust, Attitude Towards AIGC, Generation Z, Fashion Marketing