The much-discussed subject of algorithmic pricing (also known as surveillance pricing) has come under scrutiny by the U.S. Federal Trade Commission. The FCC is demanding that nine companies – Delta, United, JetBlue, Lyft, Uber, DoorDash, Instacart, Target and Walmart – explain why consumers are charged different prices for identical goods or services.
Meanwhile, a slew of recent lawsuits has alleged that companies are arriving at prices based on consumers’ buying histories or personal data.
“We intend to scrutinize the opaque methodology that some companies in these industries may be using to determine how much consumers pay or how much gig workers are paid for the same product or service,” said FTC Chairman Andrew N. Ferguson, in an October 28 press release. “Consumers deserve to know whether companies use their web surfing habits or other personal data to estimate the highest price they can charge each consumer. Workers also deserve to know if their compensation is affected by how companies use their personal data.”
Each company must turn over information that will allow the agency to assess whether the pricing for a ticket, ride share, food delivery or other product or service varies from one person to the next based on factors such as participation in loyalty programs or analysis of personal data by superintelligence algorithms, the FCC said. If a company fails to turn over the required information, the Commission has the power to compel compliance in federal court.
While the FTC is tasked with policing “unfair or deceptive acts or practices,” its mandate excludes the industries of banking and airlines, which means it cannot impose any fines or regulations on the airlines named, The Guardian said.
Several states have already begun to address the growing issue proactively, bringing lawsuits against specific retailers and service providers, and introducing legislation to ban surveillance pricing, as well as electronic shelf labels that could be used to individualize prices based on shoppers habits and online information. For example, New York state has introduced a law that mandates companies alert customers that their personal data is being used to set prices. California has introduced a bill that would outright ban it.
The FTC previously commissioned a study on personalized pricing in 2024, but that study examined only middlemen consultancies, such as McKinsey and JP Morgan Chase, who offered retailers surveillance pricing products, not the businesses that actually set prices. “The agency learned nothing about actual pricing decisions from the 2024 study,” admitted the FTC in its October 28 statement. “This study corrects the Commission’s mistaken 2024 approach and demands information directly from companies who may be engaging in personalized pricing, rather than middlemen.”
Pricing based on supply and demand, such as Uber “surge” pricing, or the way in which airlines charge different fees for the same class of seat on the same plane depending on when you buy a ticket, remains legal. But the practice of adjusting prices to specific consumers brings several legal risks. One is price-fixing between multiple providers of the same goods or services, in violation of federal anti-trust law. Another is falling foul of false-advertising laws.
In addition, there is the risk of price-gouging based on discrimination – something every street vendor since the beginning of human commerce is familiar with (which prompts the joking imprecation, “They saw you coming!”). The new twist is that this version deploys artificial intelligence using non-public data to recommend higher prices based on what it judges specific customers are willing to pay. McDonald’s is currently in the cross-hairs for exactly this practice in a nationwide class-action lawsuit that accuses the fast-food giant of using an AI-powered pricing system to coordinate menu prices across its U.S. restaurants (McDonald’s denies that it does so).
Generally, the point is that this is different from simple market economics, where the price of something varies according to supply and demand. The danger is that large companies, or colluding cartels of companies, can fix prices in a fiendishly complicated, individualized way that is nevertheless still price-fixing. It’s one thing to be charged more for an item based on its availability; quite another to be charged more because the retailer knows how much you earn, or that you’re about to host a kid’s birthday party.
Some retailers outed by the media for using surveillance pricing have stepped back from the practice. One example is Instacart. Prompted by an investigation conducted by Consumer Reports and Groundwork Collaborative, the online grocery retailer in December 2025 announced it would stop offering technology that allowed grocery retailers to charge shoppers different prices for the same groceries at the same time.
Consumers are meanwhile being empowered by legislation that allows them to refuse to let social media companies exploit their personal information. In September, the Australian government announced “world-leading” reforms that would force social media platforms to allow users to opt-out of algorithms, dubbed “my feed, my way.”
Technology presents opportunities to push back, too. YouTuber Chris Parr used a drone carrying his iPhone to trick DoorDash into charging him different prices for the same meal order from the same White Castle store for pickup (not delivery), depending on where the phone he used to place the order was located. Bizarrely, the online food, grocery and retail delivery platform charged 19% less when his phone was hovering within the confines of a high-income enclave.
Although AI’s power to harness the vast amount of consumers’ personal data in myriad ways to make supply chains more efficient (or at least more responsive) is undeniable, it looks like consumer and legal backlash will increasingly limit the extent to which retailers can boost profits by looking over your shoulder, 24/7.
