International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Trust-Aesthetics Paradox: Generative vs. Agentic AI in Fashion Retail

Author(s) Mr. Sparsh Arora
Country India
Abstract As the fashion industry transitions from predictive algorithms to Agentic Artificial Intelligence, retailers face a critical dilemma: Does technological sophistication equate to consumer trust? This study employs a comparative mixed-method approach, synthesising secondary industry data from the AI's Fashion Trust Paradox (2026) report with primary quantitative research to evaluate consumer readiness for Generative and Agentic AI. Secondary research indicates a global consensus on AI aesthetics, with 82% of consumers globally drawn to the hyper-perfect visual appeal of AI-generated imagery [4]. However, our primary data from Gen Z consumers in Delhi reveals a stark contrast [1]. While the visual gap has narrowed, only 35.2% of local respondents preferred AI-generated imagery for fabric quality, suggesting that Indian consumers remain sceptical of synthetic perfection. In the domain of Agentic AI, the study uncovers a significant deviation from global trends. While secondary reports highlight a massive 74% fear of Black Box autonomy globally, our primary data indicates that Delhi consumers are adopting automation faster than expected [1]. A striking 59.3% of respondents expressed willingness to trust an AI agent with financial negotiations (refunds), challenging the global narrative. However, the limit of this trust is defined by final execution: 48.1% of users prefer an Add to Cart + Approval model over fully autonomous purchasing (33.3%). The study concludes that the Indian market is ready for Assisted Autonomy, in which AI handles aesthetic visualisation and service negotiation, while the human retains final transactional authority.
Keywords Agentic AI, Generative AI, Trust-Aesthetics Paradox, Assisted Autonomy, Consumer Psychology, Digital Fashion.
Field Business Administration
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-02-19
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.69192
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E-ISSN 2582-2160
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