Federal regulators are investigating whether major retailers, airlines, and app-based companies use personal information to determine what customers pay—and what gig workers earn. The question is whether two people could receive different offers because an algorithm knows more about them than they realize.
Imagine shopping online for groceries, booking a flight, or ordering a ride. You see a price, decide whether it is reasonable, and make your purchase. But what if someone else, looking at exactly the same product or service, receives a different offer—not because of supply and demand, but because a computer has analyzed what each of you might be willing to pay?
That possibility is now the subject of a major federal investigation.
On October 28, the Federal Trade Commission (FTC) ordered nine prominent companies to provide detailed information about how they use personal data and automated systems to determine consumer prices and, in some cases, worker compensation.
The companies are Walmart, Target, Delta Air Lines, United Airlines, JetBlue, Uber, Lyft, DoorDash, and Instacart.
The investigation reaches into everyday transactions, from supermarket purchases and airline tickets to ride-hailing and food delivery. Its central question is simple: Are companies using what they know about individual customers to decide how much money to charge them?
The inquiry does not establish that any of the companies are engaging in improper personalized pricing. Rather, regulators are demanding information to determine what practices actually exist.
When the Price Depends on Who You Are
Businesses have always adjusted prices. Airlines charge different fares depending on availability and booking dates. Hotels increase rates during busy periods, while stores offer discounts to loyalty-program members.
But personalized pricing introduces a different possibility.
Instead of setting a price based primarily on the product, the market, or the time of purchase, a company could use information about an individual customer to calculate what that particular person might be willing to spend.
That information could include location, shopping history, browsing behavior, previous purchases, or interactions with an app.
For example, imagine two customers searching for the same household product. An algorithm might estimate that one is highly price-sensitive while the other is likely to purchase immediately, even at a higher price. In theory, the company could present different offers to each.
This example illustrates the concern under investigation; it is not evidence that any particular company named by the FTC is doing so.
Artificial intelligence makes such strategies potentially more sophisticated because it can analyze large volumes of behavioral data and identify patterns that would be difficult for human employees to detect.
Regulators sometimes call this practice surveillance pricing, although not every personalized discount or algorithmic price adjustment is necessarily harmful or unlawful.
What the FTC Wants to Know
The FTC’s orders seek information about the data, technologies, and procedures companies use when determining prices.
Investigators want to understand whether consumers are offered different prices for the same goods or services based on personal characteristics, participation in loyalty programs, or other information gathered through digital platforms.
The agency is also examining whether companies use artificial intelligence or other automated decision-making systems to make those distinctions.
The nine companies have 45 days from receiving the orders to respond. The FTC has authority to seek federal court enforcement if they fail to comply.
The investigation builds on an earlier FTC study of companies that supply retailers with data-driven pricing technology. Preliminary findings released in January 2025 indicated that such intermediaries could use information ranging from browsing history and geographic location to movements of a mouse on a webpage.
That earlier study examined the technology providers rather than directly establishing how individual retailers set their prices. The new inquiry is intended to obtain answers from the businesses that sell products and services to consumers.
The Other Side of the Investigation: What Workers Get Paid
There is another dimension to the FTC’s investigation that may be just as consequential.
The agency is asking whether ride-hailing and delivery companies use information about individual drivers to determine how much they are offered for particular jobs.
Unlike a traditional employee receiving a fixed hourly wage, an independent driver may see a changing payment offer for each trip or delivery.
The FTC wants to know whether those offers are influenced by factors such as a driver’s phone usage or history of accepting assignments.
Consider two drivers offered similar trips under comparable conditions. Could a platform’s algorithm offer one driver less money because it predicts that person is more likely to accept a lower payment?
That is a hypothetical example of the issue regulators are examining, not a finding about any particular platform.
For millions of people who depend on app-based work, understanding how compensation is calculated could be as important as knowing how customers are charged.
The investigation raises a broader question about algorithmic management: when software makes economic decisions affecting workers, how much should those workers be allowed to know about the rules?
What the Companies Are Saying
Several companies have rejected the suggestion that they use personal information to impose individualized prices.
Delta Air Lines said it does not use, test, or plan to use fare products that target customers with individualized offers based on personal data. JetBlue similarly said that its fares depend on demand and seat availability, rather than personal browsing histories or individual customer profiles.
Walmart’s leadership has also said the retailer does not use information such as customers’ income, shopping history, or willingness to pay to set personalized prices and does not intend to do so.
Instacart has said that retailers determine product prices on its platform and that shopper compensation is based on job-related factors.
These statements matter because there is a significant difference between the technological ability to personalize prices and evidence that a specific company actually does so.
The FTC’s investigation is designed to examine that distinction.
Dynamic Pricing Is Not the Same as Personalized Pricing
One of the most important distinctions for consumers is the difference between prices that change for everyone and prices that change because of who is shopping.
Dynamic pricing responds to circumstances such as demand, availability, or time. A ride may cost more during a rainstorm, for example, because more customers are requesting cars.
Personalized pricing uses information about a particular consumer to determine an individual offer.
The two approaches can overlap, and both may use algorithms. But their implications for privacy and fairness are different.
A changing price is not, by itself, proof that a company is analyzing personal data to charge someone more.
The concern becomes greater when customers do not know what information is being used, cannot understand why their offers differ, or have little practical ability to challenge the result.
What Consumers Can Do Right Now
Until regulators provide more information, consumers should avoid assuming that every price difference is evidence of surveillance pricing. Still, there are practical ways to become more informed shoppers.
Compare offers across competing websites and apps before making significant purchases. For travel, look at the full price, including fees, rather than focusing only on the first advertised fare.
Review privacy settings and consider whether a retailer or service really needs access to your precise location, contacts, or other personal information. Understand that using a private browsing window does not necessarily prevent a company from recognizing you through an account, device information, or other identifiers.
Be aware that loyalty programs may exchange discounts or rewards for access to purchasing data. Such programs are not inherently improper, but customers should understand the trade-off.
If two people notice different prices for the same product, they should check whether the offers truly involve identical items, locations, dates, fees, and eligibility conditions before drawing conclusions.
Gig workers can also keep records of trip offers, mileage, time, and compensation. Those records may help them evaluate whether the work remains profitable, even when the platform’s pricing formula is not fully visible.
A Bigger Question About the Digital Economy
The FTC’s investigation comes at a time when artificial intelligence is making it easier for companies to predict consumer behavior and automate business decisions.
Used responsibly, those capabilities can improve efficiency, reduce costs, and help companies offer relevant discounts.
But they also create a troubling possibility: a marketplace in which the price of a product depends not only on what it costs or what competitors charge, but on what a company has learned about the person buying it.
For workers, the corresponding concern is whether algorithms could use knowledge of individual circumstances or behavior to influence how much someone is paid.
The FTC has not yet answered those questions. Its investigation may help determine how widespread such practices are and whether additional consumer protections are needed.
For now, the most important issue is transparency.
When artificial intelligence helps decide what we pay—or what we earn—consumers and workers deserve to understand whose interests the algorithm is serving.
Sources:
This report is based on the FTC’s official statement of October 28, 2026, coverage by Reuters and the Associated Press, and the FTC’s preliminary findings on personalized pricing published in January 2025.
