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AI product discovery could raise UK retail return rates

AI product discovery could raise UK retail return rates

Mon, 26th Oct 2026 (Today)
Sean Mitchell
SEAN MITCHELL Publisher

MACH Alliance has published research suggesting that AI-led product discovery may contribute to higher retail return rates among UK shoppers. The findings are based on a survey of more than 1,000 UK consumers.

The study indicates that AI is already influencing a substantial share of online spending. It found that 42% of shoppers' digital spend is influenced by AI search, while 41% of eCommerce purchases are directly influenced by agents.

Among Millennials, that influence appears stronger. The research found that almost half, or 48%, of their purchases are shaped by AI, while in social commerce AI has a direct role in 45% of spending.

At the same time, the data points to a growing gap between what shoppers expect and what they receive. More than half of respondents, or 56%, said AI overhypes product expectations before checkout.

Six in 10 said AI creates unrealistic beliefs about how products will look, fit or perform. Another 44% said it sets expectations too high before purchase, leaving them disappointed when the item arrives.

That figure rises among younger consumers. Almost half of Gen Z respondents, or 47%, said AI leaves them with expectations that are too high before purchase, and 53% said it makes them more likely to return products.

Visual presentation emerged as a particular concern. More than two-thirds of respondents, or 68%, agreed that AI imagery that looks too perfect often does not reflect the reality of the product when it arrives.

A further 60% said AI-generated styling or visualisations make it harder to imagine how products will look in real life. The survey described this as an expectations gap between AI-led discovery and the goods ultimately delivered.

That disconnect appears to have consequences after the sale. The research found that 45% of shoppers believe unrealistic expectations created by AI discovery would make them more likely to return a product, while 51% said using AI increases the likelihood of buyer's remorse after purchase.

Returns have long been a pressure point for retailers, particularly in fashion and other categories where fit, finish and appearance are central to purchase decisions. The survey suggests the spread of AI across search, recommendations and product presentation may add another layer of risk if the information shown to shoppers does not match the item they receive.

Jason Cottrell, President of MACH Alliance, said retailers should weigh conversion gains against the effect on returns. "AI is already driving real gains in discovery, inspiration and conversion. Retailers also need to recognise it can come with an unintended consequence: returns," he said.

He added: "When the product that arrives doesn't live up to what AI promised, that sale quickly becomes a return."

Connected systems

Cottrell argued that the issue is linked to the quality and reach of the data used by AI tools. "Good outcomes for customers and businesses don't come from AI and agents working in isolation," he said.

"Agents need to be grounded in accurate, real-time product information and connected to the wider commerce ecosystem, from inventory and availability to fulfilment and post-purchase. No single vendor or agent can solve for every part of that journey," he added.

The research comes as retailers increase their use of generative AI and automated agents across customer-facing channels. These tools are being used to shape search results, generate imagery, present styling ideas and guide customers through buying decisions, particularly in mobile shopping and social commerce environments.

For retailers, the findings point to a trade-off. AI may help increase product discovery and improve conversion rates, but the survey suggests those gains may be offset if shoppers feel the final purchase does not match the impression created online.

Cottrell said the answer lies in closer links between AI systems and operational data across the retail chain. "Connected ecosystems are how retailers close the AI expectations gap. When agents, data and best-of-breed technologies work together, what shoppers see during discovery is much closer to what arrives at their door," he said.