Retailers' AI Pricing Puts Shoppers in the Dark

U.S. consumers are angry and confused as restaurant chains and major retailers bring digital shelf labels and artificial intelligence into decisions about what shoppers pay. Companies can use AI to predict how customers might respond to prices, but limited transparency about data collection leaves shoppers guessing whether the same product costs different people different amounts.

Kearney’s Katie Thomas put the power struggle plainly: “There are major tensions happening right now between who's really going to have the power with some of these algorithms and usage of bots and AI: the companies or the shopper.” The question reaches everyday purchases, not just flights or hotel rooms. Consumers already know changing fares and rideshare prices; now algorithms and personal data have entered the retail conversation.

Who Controls the Price Tag

Digital shelf labels let stores change prices electronically instead of replacing paper tags. They’re spreading among major U.S. retailers, including Walmart and Whole Foods, after long use in Europe and Asia. Consumer advocates warn the labels could eventually enable surge or personalized pricing, and labor unions have opposed the technology.

Walmart CEO John Furner said in a blog post last month that digital labels save workers’ time and keep prices current. He said Walmart doesn’t use them to raise prices based on weather, time of day or an individual shopper. “We price the product, not the person,” Furner wrote. Those assurances sit alongside limited transparency, fueling suspicion about the data retailers collect and how they use it.

Some social media posts falsely claim Walmart’s planned labels scan shoppers’ faces or cellphones to set individualized prices, Thomas said. The labels themselves don’t prove that claim. Still, the broader use of personal data to shape prices remains unclear.

Retailers typically update electronic shelf prices on a regular schedule, often weekly, said Asa Farquhar of Relex Solutions. Researchers tracking prices at an unnamed grocery chain found “virtually no surge pricing” after labels were introduced. “Changing prices throughout the day, the way airlines or rideshare apps do, is exceedingly rare in grocery and general merchandise today,” Farquhar said.

The Rules—and Their Limits

Legislators in at least 30 states considered pricing bills this year, according to the National Conference of State Legislatures. The Federal Trade Commission has proposed an enforcement policy warning that failing to disclose personal data used to set individualized prices could violate consumer protection law. Maryland, New Jersey and Connecticut recently enacted restrictions; the Maryland and New Jersey laws focus on groceries, while Connecticut’s covers a broader range of retail purchases. The Maryland and New Jersey laws make exceptions for certain loyalty discounts and other promotional offers.

Some advocacy groups and regulators call personalized pricing “surveillance pricing.” It can draw on information such as shoppers’ locations, incomes and web-browsing habits. A Federal Trade Commission staff report released in January 2025 found that intermediaries offering tools to tailor prices and promotions worked with at least 250 clients, including grocery and clothing retailers. That report shows a market for these tools; it doesn’t establish how widely retailers use them.

Algorithms Serve Business Goals

Decodo tracked price changes in 2025 across products including electronics, clothing and home-improvement supplies. About half of the U.S. changes it recorded were decreases, said Gabriele Vitke, a senior product marketing manager. Algorithmic pricing can recommend or automatically set prices, drawing on sales patterns, competitors’ prices and other information to estimate demand and effects on sales and profits.

A Simon-Kucher survey of more than 2,200 business leaders in 28 countries and 39 industries found that 41% used AI software to gather market intelligence, including competitors’ prices, and 28% used it for “real-time price optimization.” The National Retail Federation said algorithmic pricing offers a new way to monitor and adjust prices according to supply, demand, seasonality, competitors’ prices and other factors.

Lawsuits have challenged how those tools serve corporate interests. In a 2023 antitrust lawsuit against Amazon, the FTC alleged that Project Nessie identified products whose prices Amazon could raise with competitors likely to follow, generating more than $1 billion in excess profits. Amazon called the allegations “grossly mischaracterize[d]” and said it tested the tool for a few years, it didn’t work as intended and the company scrapped it before the lawsuit. A trial is scheduled for next year.

A recent consumer lawsuit against McDonald’s alleged its pricing system used nonpublic sales data from competing locations to coordinate prices. The company called the suit “filled with inaccuracies” and said it makes the tool available to U.S. franchisees to help them set prices at their individual restaurants. In California, prosecutors sued Target in 2022 over allegations its app showed lower prices before shoppers entered stores and raised them inside. Target agreed to a $5 million settlement and a ban on using geofencing technology to increase prices. The company said the feature provided “accurate pricing” and said it remains “committed to clear, transparent pricing.”