AI-Generated Models and Their Impact on Consumer Trust and Perceived Risk in Online Fashion Retail
type: CreativeWork
description: The purpose of this research is to understand how the use of fashion models generated by artificial intelligence (AI) in product imagery affects consumer trust and perceived risk in the online retail setting. As AI technology continues to advance, its implementation and the opportunities it offers have noticeably expanded across marketing practices. AI-generated models are one of the latest phenomena observed in advertising and retailing spheres. Previous literature has widely explored the effects of different types of sources in marketing content, with recent studies focusing on the use of virtual endorsers and AI imagery in advertising. However, as AI-generated models start to become a more common occurrence in online retail spaces, its impact on consumers in this setting remains under researched. Understanding the effects of this phenomenon is particularly important in the online retail context due to its intangible nature, which can lead to higher perceptions of risk and lower level of trust (Teo & Liu, 2007; Handoyo, 2024). As consumers often rely on visual information to reduce perceived risks, particularly when shopping for clothing online (Yu et al., 2012), the use of AI generated models can be expected to negatively impact consumer trust and perception of risk. Recent studies have demonstrated that disclosed AI imagery in ads is associated with a decrease in credibility and trust (Grigsby et al., 2025), while other studies have shown that virtual influencers have the same effect (Hofeditz et al., 2022; Nissen et al., 2023). Such outcomes can be related to a reduction in perceived anthropomorphism, whereby lower perceptions of anthropomorphism in AI imagery are associated with a decrease in consumer trust (Muniz et al., 2024; Luo et al., 2019). Thus, using a quantitative research approach, the current study aims to address these observed gaps in the literature. This work’s research question seeks to understand how the use of AI-generated models impacts consu…
abstract: The purpose of this research is to understand how the use of fashion models generated by artificial intelligence (AI) in product imagery affects consumer trust and perceived risk in the online retail setting. As AI technology continues to advance, its implementation and the opportunities it offers have noticeably expanded across marketing practices. AI-generated models are one of the latest phenomena observed in advertising and retailing spheres. Previous literature has widely explored the effects of different types of sources in marketing content, with recent studies focusing on the use of virtual endorsers and AI imagery in advertising. However, as AI-generated models start to become a more common occurrence in online retail spaces, its impact on consumers in this setting remains under researched. Understanding the effects of this phenomenon is particularly important in the online retail context due to its intangible nature, which can lead to higher perceptions of risk and lower level of trust (Teo & Liu, 2007; Handoyo, 2024). As consumers often rely on visual information to reduce perceived risks, particularly when shopping for clothing online (Yu et al., 2012), the use of AI generated models can be expected to negatively impact consumer trust and perception of risk. Recent studies have demonstrated that disclosed AI imagery in ads is associated with a decrease in credibility and trust (Grigsby et al., 2025), while other studies have shown that virtual influencers have the same effect (Hofeditz et al., 2022; Nissen et al., 2023). Such outcomes can be related to a reduction in perceived anthropomorphism, whereby lower perceptions of anthropomorphism in AI imagery are associated with a decrease in consumer trust (Muniz et al., 2024; Luo et al., 2019). Thus, using a quantitative research approach, the current study aims to address these observed gaps in the literature. This work’s research question seeks to understand how the use of AI-generated models impacts consu…
author: Melamed, Milana
date published: 2026
date modified: 2026-07-27T18:45:47Z
provider: AUT University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: AUT University