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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 3 (March 2026).... Submit articles

AI-enhanced intelligent fashion eCommerce: Virtual try-on and personalized style recommendations in action

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Keshav Agrawal *

Wharton School at University of Pennsylvania, USA.

Review Article

World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 2142-2150

Article DOI: 10.30574/wjaets.2025.15.1.0475

DOI url: https://doi.org/10.30574/wjaets.2025.15.1.0475

 Received on 16 March 2025; revised on 23 April 2025; accepted on 25 April 2025

The fashion retail industry is experiencing a significant digital transformation driven by advanced technologies. This article examines the implementation of Artificial Intelligence in fashion eCommerce, focusing on virtual try-on technologies and personalized style recommendations. The article shows how these AI-powered solutions address key challenges in online fashion retail, including size uncertainty, fit issues, and the inability to physically experience products before purchase. Through article analysis of current technological frameworks, machine learning models, augmented reality applications, and 3D modeling techniques, this study demonstrates how AI is revolutionizing the customer experience while delivering measurable business benefits. The article also explores implementation challenges related to data quality, privacy concerns, technical integration, and cost-benefit considerations, providing practical solutions and frameworks for successful deployment across various fashion retail segments. 

Artificial Intelligence; Virtual Try-On; Fashion Ecommerce; Personalization; Augmented Reality

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-0475.pdf

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Keshav Agrawal. AI-enhanced intelligent fashion eCommerce: Virtual try-on and personalized style
recommendations in action. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 2142-2150. Article DOI: https://doi.org/10.30574/wjaets.2025.15.1.0475.

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