Retail AI Pricing Puts Shopper Data in Play

Retail unions have opposed electronic shelf labels as Walmart and Whole Foods introduce the technology in more U.S. stores. Consumers, meanwhile, question how retailers use algorithms and personal data to set prices. Walmart says the labels save workers’ time and keep prices current. Whether shoppers pay different prices for the same product remains a public concern.

Who Sets the Price

“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,” said Katie Thomas, who leads an internal consumer behavior think tank at management consulting firm Kearney.

Companies say some public concerns misunderstand the tools. In a blog post last month, Walmart CEO John Furner said the company doesn’t use digital tags to raise prices based on weather, time of day or an individual shopper. “We price the product, not the person,” Furner wrote.

Thomas said social media posts falsely claim the electronic shelf labels Walmart plans to install in all its U.S. stores scan shoppers’ faces or cellphones to set individual prices. She said limited transparency about what customer data companies collect and how they use it has fueled suspicion.

Digital labels let stores update prices electronically rather than replace paper tags. Retailers have used them for years in Europe and Asia, and they’re now drawing attention as they reach major U.S. chains. Asa Farquhar of retail technology company Relex Solutions said retailers typically update shelf prices on a regular schedule, often weekly, because shoppers value consistency. Researchers tracking prices at an unnamed grocery chain found “virtually no surge pricing” after the labels arrived. Farquhar said changing prices throughout the day, as airlines and rideshare apps do, is “exceedingly rare in grocery and general merchandise today.”

Algorithms, Profits and Data

Algorithmic pricing software recommends prices or sets them automatically. Companies have used these systems for decades. AI can analyze sales patterns, competitors’ prices and other information to predict demand and estimate how prices might affect sales and profits.

A survey by global consulting company Simon-Kucher 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. Another 28% said they used it for “real-time price optimization,” meaning they chose prices to advance business goals such as increasing profits, attracting shoppers or clearing unsold goods. How widely retailers use AI for pricing remains unclear.

In an antitrust lawsuit against Amazon, the Federal Trade Commission alleged the company used an algorithm called Project Nessie to identify products it could raise in price when competitors would likely follow, generating more than $1 billion in excess profits. Amazon said the allegations “grossly mischaracterize” the tool, which it said aimed to stop price-matching from creating unsustainably low prices. The company said it tested the tool for a few years, found it didn’t work as intended and scrapped it before the agency’s lawsuit. A trial is scheduled for next year.

A consumer lawsuit against McDonald’s alleged its pricing system used nonpublic sales data from competing locations to coordinate prices. The company called the lawsuit “filled with inaccuracies” and said it offers the tool to U.S. franchisees to help them set prices at their individual restaurants.

Regulation and Its Limits

According to the National Conference of State Legislatures, lawmakers in at least 30 states have considered pricing bills this year, including proposals on algorithmic and personalized pricing. The Federal Trade Commission has proposed an enforcement policy warning that failing to disclose the use of personal data to set individual prices could violate consumer protection law.

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. Maryland, New Jersey and Connecticut have enacted restrictions on using shoppers’ personal data to determine what they pay. The Maryland and New Jersey laws focus on groceries, with exceptions for certain loyalty discounts and other promotions; Connecticut’s law covers a broader range of retail purchases.

California prosecutors sued Target in 2022, alleging its app showed lower prices before shoppers entered stores and raised them once they were inside. Target agreed to a $5 million settlement and a ban on using geofencing technology to increase prices. Target said the feature provided “accurate pricing, which can vary across stores and channels,” and denied personalizing prices based on guests’ data or behavior.

Different prices don’t necessarily mean personal data set them. Consumer Reports, Groundwork Collaborative and More Perfect Union found that Instacart shoppers saw different prices for identical products at the same stores. Instacart later ended tests that it said randomly assigned shoppers to groups rather than setting prices based on personal information.