AI Recommendations Fuel Purchases—and a 46% Return Rate

Forty-six percent—nearly one in two—of U.S. consumers who bought a product based on an AI recommendation returned it in the past year, according to Blue Yonder’s survey of 2,000 U.S. shoppers. Nearly a quarter of U.S. consumers have bought a product based on AI, Blue Yonder found. Recommendation engines can get a shopper to checkout. Accurate product data still decides whether the sale survives delivery.

The return reasons

Among U.S. shoppers who returned an AI-recommended purchase, Blue Yonder found:

• Description mismatch: 36% said the item was different from its description.
• Size or fit: 23% cited an incorrect size or fit.

Incorrect size or fit accounted for 42% of returns in general, according to the survey. The survey analysis suggested that AI assistants may be doing better at finding the right fit while still struggling to describe products accurately.

Blue Yonder’s research concluded that AI agents have not solved returns despite the promise of deeper personalization. The analysis identified retailer information supplied to answer engines as the likely culprit, rather than the AI agent alone.

“Shoppers are taking AI’s advice faster than retailers are getting ready for it, and nearly half of them are sending something back,” Duncan Angove, CEO of Blue Yonder, said in a statement. “That’s not really an AI problem. It’s a data problem.”

“An AI assistant is only as good as the product information it can find, and most product data was written for a search bar, not for a machine suggesting products for someone. When what arrives doesn’t match what the shopper expected, it goes back in the box,” Angove said.

Younger shoppers lead adoption

AI-assisted buying skews younger in Blue Yonder’s survey of 2,000 U.S. shoppers:

• Gen Z: 43% bought a product based on an AI recommendation.
• Millennials: 36%.
• Gen X: 19%.
• Baby boomers: 9%.

Adoption does not equal confidence. A recent SmartCustomer survey found that 89% of shoppers did not fully trust AI recommendations, while one-third said they had made a regrettable purchase based on one. Separately, a recent Mastercard survey found that nearly one-third of teenagers trusted AI-generated product recommendations over a friend.

Returns policies shape loyalty

Fifty-one percent of Blue Yonder respondents said they had decided to buy from one retailer over another purely because it had a better returns policy. The survey also found that 29% had stopped shopping altogether at a retailer that implemented a stricter return policy in the last year.

RTB House research offers shoppers another route to defection. According to its research, AI tools often surface more options than traditional search, giving consumers an alternative when the first option does not fit.

What does this change for retailers?

Blue Yonder’s findings put product data and returns policy in the same workflow. Descriptions and sizing need to be accurate in the systems that answer AI queries, not merely legible to a human browsing a search bar. Retailers also need returns terms that do not cancel the convenience shoppers accepted when an AI agent made the recommendation.

Angove called it a data problem, not an AI problem. For retailers, that means auditing what feeds recommendation systems and aligning it with fulfillment and returns. AI can win the click, but inaccurate descriptions and restrictive policies help send the sale back.

As shoppers give AI agents more influence over product choice, the forward test is straightforward: whether the delivered item matches the recommendation and whether the retailer can accept it when it does not. Blue Yonder’s figures suggest those two handoffs now determine whether AI-assisted selling scales or simply feeds the returns counter.