Major retailers are adopting artificial intelligence, electronic shelf labels and automated pricing systems, prompting questions about whether businesses could use shoppers’ personal information to determine how much they pay.
By yourNEWS Media Newsroom
American shoppers are facing growing uncertainty about how prices are determined as retailers and restaurant chains introduce artificial intelligence systems capable of analyzing customer behavior, monitoring competitors and recommending price changes.
The technology is attracting scrutiny from consumer advocates and lawmakers concerned that businesses could eventually charge different customers different amounts for identical products based on their locations, purchasing histories or other personal information.
An Associated Press examination of emerging retail pricing practices found that confusion over digital price tags, dynamic pricing and personalized pricing has contributed to public concern, even though the technologies operate differently and do not necessarily involve surveillance of individual shoppers.
“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 a consumer behavior research group at consulting firm Kearney.
Much of the debate centers on whether technology designed to improve pricing efficiency could also make it easier for businesses to exploit differences in what consumers are willing or able to pay.
Walmart has attempted to address those concerns as it expands electronic shelf labels throughout its U.S. stores.
The displays allow employees to update prices electronically rather than manually replacing paper labels. Their introduction has generated speculation online that stores could use cameras or smartphones to identify customers and automatically adjust prices.
Walmart CEO John Furner rejected those claims, saying the company does not use personal information or the time of day to determine what individual customers are charged.
“We price the product, not the person,” Furner wrote in a September statement.
The company maintains that its digital labels are intended to improve price accuracy and reduce the time employees spend changing shelf tags.
Electronic shelf labels do make it technically easier to update prices, but they do not independently collect facial information or establish personalized prices.
Asa Farquhar of retail technology company Relex Solutions said frequent grocery price changes remain uncommon because retailers recognize that customers expect consistency.
“Changing prices throughout the day, the way airlines or rideshare apps do, is exceedingly rare in grocery and general merchandise today,” Farquhar said.
Research examining an unnamed grocery chain found virtually no evidence that introducing electronic shelf labels resulted in sudden demand-based price increases.
The distinction matters because electronic labels are sometimes confused with dynamic pricing, a longstanding business practice involving adjustments based on supply, demand, competition or other market conditions.
Airlines routinely change ticket prices as available seats diminish or departure dates approach. Hotels adjust room rates according to occupancy and seasonal demand, while rideshare companies increase fares when requests exceed available drivers.
Similar systems are becoming more sophisticated as businesses incorporate artificial intelligence into price-setting decisions.
However, fluctuating prices do not always mean consumers are being charged more.
Web data company Decodo analyzed pricing changes across categories including electronics, clothing and home improvement products in 2025. Approximately half of the changes it tracked in the United States were price reductions, according to senior product marketing manager Gabriele Vitke.
A separate practice, personalized pricing, has attracted greater scrutiny because it can involve information about individual consumers.
Personalized pricing allows companies to offer different prices or discounts based on factors such as location, income, browsing activity or purchasing behavior.
Consumer advocates and regulators sometimes refer to this practice as surveillance pricing when businesses rely on extensive personal data collection.
The Federal Trade Commission examined the industry in a January 2025 staff report and found that companies offering personalized pricing technology served at least 250 clients, including grocery retailers and clothing businesses.
The report raised questions about the types of information collected, whether consumers understand how it is used and whether individualized pricing could produce discriminatory outcomes.
Regulators have since proposed stronger disclosure requirements.
The FTC has warned that businesses failing to inform consumers about the use of personal information in individualized pricing could violate federal consumer protection law.
State lawmakers have also responded. According to the National Conference of State Legislatures, legislators in at least 30 states considered measures addressing algorithmic or personalized pricing during 2026.
Maryland and New Jersey enacted restrictions focused on grocery pricing, while Connecticut approved broader protections involving retail purchases. Some laws preserve exceptions for loyalty programs and promotional discounts.
Concerns over location-based pricing have already produced enforcement actions.
California prosecutors sued Target in 2022, alleging that the retailer’s mobile application displayed lower prices before customers entered stores and higher prices once they arrived.
Target agreed to a $5 million settlement and restrictions on using geofencing technology to increase prices.
The retailer maintained that the technology was intended to reflect pricing differences between stores and online channels rather than discriminate among customers based on their personal characteristics.
Similar questions emerged after an investigation by Consumer Reports, Groundwork Collaborative and More Perfect Union found that Instacart shoppers sometimes received different prices for identical products at the same stores.
Instacart said the differences resulted from randomized pricing experiments rather than the use of individual customer information. The company subsequently discontinued those tests.
Meanwhile, businesses are increasingly using AI to evaluate pricing strategies.
A survey by consulting firm Simon-Kucher involving more than 2,200 executives across 28 countries and 39 industries found that 41% used artificial intelligence to gather market intelligence, including information about competitors’ prices.
Another 28% reported using AI for real-time price optimization, which involves selecting prices intended to achieve business objectives such as increasing revenue, clearing inventory or attracting customers.
The National Retail Federation argues that algorithmic pricing is an extension of methods businesses have long used to respond to market conditions.
Critics counter that more powerful software and access to detailed consumer information could create opportunities for unfair pricing or reduced competition.
Federal regulators have pursued several cases involving allegations that pricing algorithms facilitated anticompetitive conduct.
In its 2023 antitrust lawsuit against Amazon, the FTC alleged that the company’s Project Nessie algorithm identified products whose prices could be increased while encouraging competitors to follow.
The agency claimed the system generated more than $1 billion in additional profits.
Amazon disputes the allegations, saying the technology was designed to prevent automated price-matching from producing unsustainably low prices. The company said it discontinued the system before the lawsuit.
A trial is scheduled for 2027.
McDonald’s is facing a separate consumer lawsuit alleging that its pricing software used nonpublic information from competing restaurant locations to coordinate prices.
The company disputes those claims, describing the lawsuit as “filled with inaccuracies.”
McDonald’s maintains that its software helps independently operated franchisees make pricing decisions for their own restaurants.
Neither lawsuit establishes that the companies violated competition laws, and the allegations remain subject to legal proceedings.
The growing use of AI-assisted pricing illustrates how ordinary retail transactions are becoming more dependent on automated systems and data analysis.
Although those tools can improve efficiency and help businesses respond to changing costs, their increasing complexity has made it more difficult for consumers to understand how prices are determined.
The central concern is whether shoppers can distinguish legitimate market-based changes from price adjustments influenced by information collected about them.
With state legislatures and federal regulators examining the issue, retailers face increasing pressure to explain their pricing practices and establish safeguards against misuse of consumer data.
For shoppers, the debate extends beyond whether digital technology makes prices rise or fall. It concerns whether customers know what information businesses possess about them and whether that information affects the prices they ultimately pay.
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