How AI is trying to solve retail’s returns problem
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It pinches here; drags there; the draping is wrong. These are some of the examples of the feedback a new crop of artificial intelligence apps might give a prospective customer trying on clothing ahead of a purchase, and in the process reduce the chances of a product being returned to a store.
Fashion retailers are increasingly turning to AI to solve the issue of rising product returns, a persistent drag on profitability and something many in the industry refer to as the industry’s “silent killer”.
A growing number of AI start-ups have emerged to provide virtual try-on technology, allowing potential customers to visualize fit and style before they buy.
While tech companies have attempted to solve online fit issues since the 2010’s, the rapid development of generative AI has finally made these applications good enough to meaningfully impact retailers’ bottom lines.
The U.S. National Retail Federation late last year estimated that 15.8% of annual retail sales were returned in 2025, totaling $849.9 billion. For online sales, that number jumped to 19.3%. Gen Z is driving this trend, with shoppers aged 18 to 30 averaging nearly eight online returns per person last year, the NRF found.
Most returned items never make it back to the shelves and often cost the retailer more to process than the value of the refund itself. It’s a multibillion-dollar problem for the industry that’s eating directly into companies’ margins.
“Figuring out how to proactively use returns and then how to minimize them can be a meaningful driver of business and profitability,” Guggenheim Senior Managing Director Simeon Siegel told CNBC.
While fit technology will never be as good as trying something on in person, it’s a great way to bridge the gap, Siegel said. “It’s going to continue to get better, I think that’s going to continue to reduce returns.”
Mirror-like realism?
The primary reason for returns and abandoned shopping carts is uncertainty over fit, Ed Voyce, founder and CEO of AI startup Catches, told CNBC in an interview.
Catches has developed a platform that allows users to create a “digital twin” to try on clothes virtually with what it calls “mirror-like realism.” The application went live last month on luxury brand Amiri’s website for a select range of clothes.
Unlike other models that Voyce says “just look pretty,” the Catches platform incorporates the physics of fabric texture and how material interacts with a moving body.
“The reason we built Catches was to take advantage of a kind of confluence of technologies that is taking place right now to solve this issue effectively,” says Voyce, who founded the startup backed by LVMH’s Antoine Arnault and built on Nvidia’s CUDA platform.
“The reason it’s solvable now in terms of timing is that you have to be able to run visuals for end users on bare metal in the cloud, cheaply enough to make a [return on investment] for brands,” Voyce says.
“This technology has the potential to impact the whole…
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