Andew Smith
Online shopping has a dirty secret. Despite its explosive growth, e-commerce is plagued by an astronomical return rate — and it is costing retailers a fortune. In 2025, the U.S. National Retail Federation estimated that 15.8% of annual retail sales were returned, totaling $849.9 billion. For online sales, that number jumped to 19.3%. Now, a wave of AI startups is stepping in with a powerful solution: virtual try-on technology powered by generative AI. In this blog, we explore how AI is tackling retail’s biggest problem and what it means for the future of shopping.
The Scale of the Online Returns Problem
The returns crisis is not just an inconvenience — it is an existential threat to retail margins. Most returned items never make it back to shelves and cost retailers more to process than the value of the refund itself. Gen Z shoppers aged 18 to 30 averaged nearly eight online returns per person in 2025 alone. The problem is structural: without the ability to physically try on products, online shoppers regularly buy multiple sizes or styles with the intention of returning what does not fit.
How AI Virtual Try-On Technology Works
AI virtual try-on systems use a combination of computer vision, generative AI, and 3D modeling to simulate how a garment will look and fit on a specific user’s body. Users upload a photo or use a live camera feed, and the AI maps the garment onto their body with realistic draping, fit assessment, and even fabric behavior simulation. Advanced systems can provide detailed feedback such as identifying where a garment pinches, drags, or does not align with the user’s proportions.
Key Players in the AI Returns Space
Several startups and tech giants are leading the charge. Shopify has integrated Genlook’s AI virtual try-on app into its commerce platform, helping brands boost buyer confidence and conversion rates while reducing costly returns. Google has launched virtual try-on capabilities directly within product search results across its platforms via Google Labs. Amazon and Adobe have also created virtual try-on tools in partnership with major brands. Startup Catches is targeting the luxury segment, projecting a 10% increase in conversions and a 20-30x return on investment for brand partners.
The Business Case for AI Returns Reduction
The economics are compelling. A 10% reduction in return rates for a mid-size retailer can translate into millions of dollars in recovered margin annually. AI try-on technology pays for itself quickly when deployed at scale. Beyond direct cost savings, retailers benefit from higher customer satisfaction scores, increased brand loyalty, and improved inventory management. As the technology matures, expect AI returns reduction to become a standard feature of every major e-commerce platform.
Challenges and Limitations
Despite impressive progress, AI virtual try-on technology still faces challenges. Accuracy varies significantly across body types and garment categories. Non-standard body proportions and complex garment structures can confuse current models. Privacy concerns around uploading body images persist among some consumer segments. And the technology works best for clothing, struggling more with shoes and accessories. These limitations are narrowing rapidly, but retailers should set realistic expectations when deploying current-generation solutions.
Conclusion
AI is finally delivering on its promise to solve one of retail’s most persistent and expensive problems. Virtual try-on technology, powered by generative AI, is reducing returns, increasing conversions, and improving the online shopping experience in measurable ways. For retailers facing margin pressure and rising operational costs, investing in AI returns reduction technology in 2026 is not just an option — it is increasingly a competitive necessity.
