U.S. consumers are frustrated not only by high prices but also by the increasingly high-tech methods restaurants and major retailers use to set them.
Digital price tags are quickly replacing paper labels in grocery aisles, while artificial intelligence tools help businesses determine what to charge by predicting how shoppers may respond. Terms such as “dynamic pricing” and “surveillance pricing” have fueled anxiety on social media, where users question whether different people are being charged different amounts for the same product.
Americans are familiar with prices that change when they book flights, hotel rooms or rides. But the possibility that algorithms consumers do not understand—and personal data they may not realize they are sharing—could shape everyday purchases has struck a nerve.
“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 that use the technology say some public concern is based on misunderstandings about how their pricing systems operate. Walmart CEO John Furner wrote in a blog post last month that digital price tags save employees time and keep prices current. He said the labels are not used to increase prices based on the weather, time of day or an individual shopper.
“We price the product, not the person,” Furner wrote.
Still, companies are not always clear about what customer data they collect or how they use it. That lack of transparency has increased suspicion and encouraged speculation. Social media posts, for instance, have falsely suggested that electronic shelf labels Walmart plans to install in all of its U.S. stores scan shoppers’ faces or cellphones to determine individualized prices, Thomas said.
Lawmakers and regulators are responding. Legislators in at least 30 states have considered pricing-related bills this year, including proposals involving algorithmic and personalized pricing, according to the National Conference of State Legislatures.
The Federal Trade Commission has proposed an enforcement policy stating that businesses could violate consumer protection law if they fail to disclose that they use personal data to set individualized prices.
Here are the pricing technologies and practices attracting the most scrutiny.
Dynamic pricing can push prices up or down
What it is: Dynamic pricing involves changing prices in response to market conditions, including supply and demand. An airline that adjusts ticket prices as a departure date approaches is using dynamic pricing. Uber’s practice of raising fares when demand exceeds the number of available drivers—such as during rush hour—is a form of dynamic pricing known as surge pricing.
Why it matters: Frequent price adjustments are common well beyond the food industry. Decodo, a web data company, tracked price changes in 2025 for products including electronics, clothing and home improvement supplies. Roughly half of the U.S. price changes it recorded were decreases, challenging the assumption that dynamic pricing only makes products more expensive, said Gabriele Vitke, a senior product marketing manager.
Digital price labels are spreading across U.S. stores
What they are: Digital displays that allow stores to update shelf prices electronically rather than replacing paper tags.
Why it matters: Digital price labels have been widely used in Europe and Asia for years, but they are attracting more attention as they expand to major U.S. retailers such as Walmart and Whole Foods. Consumer advocates warn that the technology could eventually enable surge or personalized pricing, while labor unions have also opposed its use.
Electronic shelf labels make frequent price changes easier, but they do not automatically result in higher prices when demand rises. Retailers generally update the labels on a set schedule—often weekly—because shoppers value consistency, said Asa Farquhar of retail technology company Relex Solutions. Researchers tracking prices at an unnamed grocery chain found “virtually no surge pricing” after the 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.
Personalized pricing, also known as surveillance pricing, relies on customer data
What it is: Personalized pricing involves offering different customers different prices or discounts based on factors such as location, income, web-browsing behavior and other information about individual shoppers or groups. Some advocacy organizations and regulators use the term “surveillance pricing” to describe the same practice.
Why it matters: It’s unclear how widely businesses use personal information to customize prices. An FTC staff report released in January 2025 found that intermediaries offering tools that can tailor prices and promotions worked with at least 250 clients, including grocery and clothing retailers.
Lawmakers in Maryland, New Jersey and Connecticut recently 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 promotional offers. Connecticut’s legislation covers a broader range of retail purchases.
California prosecutors sued Target in 2022, alleging that the retailer’s app displayed 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 so-called geofencing technology to increase prices.
Target said the app functionality at issue was used to “provide guests with accurate pricing, which can vary across stores and channels.” The retailer said it didn’t personalize prices based on a guest’s data or behavior and remains “committed to clear, transparent pricing.”
Different prices do not necessarily mean personal data was used. Last year, an investigation by Consumer Reports, Groundwork Collaborative and More Perfect Union found that shoppers on Instacart were shown different prices for identical products at the same stores. Instacart subsequently ended what it described as tests that randomly assigned shoppers to groups rather than setting prices based on their personal information.
Algorithmic pricing gets an assist from AI
What it is: Algorithmic pricing uses software to recommend or automatically set prices. Companies have used such systems for decades. AI can help the software identify patterns in sales, competitors’ prices and other information to predict demand and estimate how different prices would affect sales and profits. These tools can support both dynamic and personalized pricing.
Why it matters: It’s unclear how widely retailers use AI to help set prices, but research suggests businesses across industries are adopting it.
Simon-Kucher, a global consulting company, surveyed more than 2,200 business leaders in 28 countries and 39 industries last year, and 41% said they used AI software to gather market intelligence, including competitors’ prices. Another 28% said they used it for “real-time price optimization.” Price optimization means choosing prices that advance business goals, such as increasing profits, attracting shoppers or clearing unsold goods.
The National Retail Federation, which represents big and small stores, said algorithmic pricing is a new method of doing what retailers have always done: monitor and adjust prices depending on supply, demand, seasonality, competitors’ prices and other factors.
Some lawsuits have alleged companies used pricing algorithms to undermine competition.
A 2023 anti-monopoly lawsuit the FTC brought against Amazon challenged, among other practices, an algorithmic tool codenamed Project Nessie. The agency alleged Amazon used the tool to identify products whose prices it could raise with competitors likely to follow, generating more than $1 billion in excess profits.
A trial is scheduled for next year. Amazon said the FTC allegations “grossly mischaracterize” the pricing tool.
Project Nessie was intended to stop retail price-matching practices from creating unsustainably low prices, the e-commerce giant said. Amazon said it tested the tool for a few years but it didn’t work as intended and was scrapped before the federal agency’s lawsuit.
A recent consumer lawsuit against McDonald’s alleged that its pricing system use nonpublic sales data from competing locations to coordinate prices. The Chicago-based burger giant said the lawsuit was “filled with inaccuracies” and that the company makes the tool available to U.S. franchisees to help them set prices at their individual restaurants.
