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AI-Generated Fashion Advertising and Gen Z: The Role of Perceived Credibility and Consumer Trust in Shaping Consumer Attitudes
Jönköping University.
Jönköping University.
2026 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Background: Generative Artificial Intelligence (GenAI) is reshaping the digital marketing landscape, particularly within the fashion industry. It is transforming how brands create content and communicate with consumers, enabling new forms of AI-generated advertising. While GenAI provides brands with opportunities for efficiency and creativity, it also raises questions about consumer perceptions. Previous research has explored the corporate side of AI use in marketing. However, how consumers, particularly Generation Z, perceive AI-generated fashion advertising remains underexplored. 

Purpose: This paper examines how AI-generated advertisements affect Generation Z’s perceptions of perceived credibility and consumer trust, and how these perceptions shape consumer attitudes in the fashion industry. 

Method: The study follows a qualitative, abductive approach using semi-structured interviews with 14 Swedish Gen Z aged 21-27. The data were analysed by using a thematic analysis, identifying patterns and themes related to perceived credibility, consumer trust and consumer attitudes.

Conclusion: The findings indicate that AI-generative advertisements generally have a negative impact on Gen Z’s consumer attitudes in the fashion industry, primarily by reducing perceived credibility and consumer trust. While transparency and brand familiarity can influence these effects, the results highlight a suggested trade-off between efficiency and credibility in AI-generated advertising. 

Place, publisher, year, edition, pages
2026. , p. 86
Keywords [en]
AI-generated advertising, Perceived credibility, Consumer trust, Consumer attitudes, Fashion advertising, Source credibility
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-71759OAI: oai:DiVA.org:hj-71759DiVA, id: diva2:2066887
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Available from: 2026-06-26 Created: 2026-06-05 Last updated: 2026-06-26Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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