AWS Launches Virtual Try-On Tool to Combat $890B Retail Returns Problem

AWS Launches Virtual Try-On Tool to Combat $890B Retail Returns Problem

Amazon Web Services introduced a virtual try-on capability within Amazon Nova Canvas, its generative AI image tool, targeting the retail industry's mounting return costs. The feature uses two-dimensional image inputs—a source image of a person and a reference product image—to generate realistic try-on previews.

The move addresses a critical pain point: one in four clothing items purchased online is returned, according to the source material, with poor fit, wrong size, and style mismatch cited as top reasons. The U.S. retail returns problem reached $890 billion in 2024. Each return generates 30% more carbon emissions than the initial delivery while tying up inventory processing capacity.

AWS positioned the tool as solving earlier virtual try-on limitations around accuracy, scalability, and preserving garment details like draping, patterns, and logos. The company published sample code and implementation guidance for retailers in the first of a two-part technical series, with part two to explore real-world applications and benefits.

The announcement reflects growing AI vendor focus on reducing e-commerce friction—a direct lever on retailer profitability and customer lifetime value. CFOs managing logistics and returns operations should monitor adoption rates and impact on return rates in coming quarters.