Artificial intelligence is changing how American retailers set prices, but the growing use of digital shelf labels and pricing algorithms has also raised a troubling question for shoppers: Could the price of an everyday product depend on who is buying it?
Major retailers are introducing technologies that make price updates faster and help businesses analyze customer demand. As the Associated Press reports, those developments are fueling concerns about transparency, personal data and the possibility of different customers paying different prices for identical products.
Yet an important distinction is often lost in the debate. Electronic shelf labels, dynamic pricing and personalized pricing are not the same thing. Although some pricing experiments have produced measurable differences between shoppers, available evidence does not establish that widespread personalized pricing is taking place across American supermarkets.
How AI and Digital Price Tags Change Retail Pricing
Retail pricing technology generally falls into several categories, each with different implications for businesses and consumers.
Electronic shelf labels are small digital displays that replace traditional paper price tags. Store employees can update prices electronically rather than manually replacing individual labels. The technology can reduce repetitive work and improve consistency between shelf displays and checkout systems.
These displays do not inherently identify customers, collect their personal information or calculate individualized prices.
Dynamic pricing involves adjusting prices in response to changing conditions, including demand, inventory, competition or supply costs. Airlines, hotels and ride-hailing services have long used variations of this approach. Prices can move downward as well as upward.
Personalized pricing is different. It involves tailoring prices or discounts using information associated with particular consumers or groups. Depending on the system, that information might include location, shopping history or online behavior. Regulators and consumer advocates sometimes describe practices involving personal-data monitoring as surveillance pricing.
AI-assisted pricing refers to software that analyzes information and helps recommend or determine prices. Artificial intelligence can support dynamic or personalized pricing, but using AI does not necessarily mean a company is doing either.
Understanding these distinctions matters because the technical ability to change prices quickly is not proof that a retailer is charging individual customers according to their personal characteristics.
What the Evidence Shows About Different Prices
A December 2025 investigation by Consumer Reports, Groundwork Collaborative and More Perfect Union provided a concrete example of price variation on a grocery-shopping platform.
The researchers examined Instacart prices during five tests conducted in September 2025. A total of 437 volunteers participated across four U.S. cities, comparing products offered by five Target and Safeway stores. After incomplete or incorrect submissions were excluded, 193 participants' submissions were included in the final analysis.
According to the published investigation, 74% of the grocery items examined appeared at multiple prices for different shoppers. Some identical products were displayed at as many as five prices at the same store and time.
For certain products, the differences reached as much as 23%. Those figures describe the tested products and participating shoppers, not average price differences across the U.S. grocery market.
Researchers compared prices displayed in shopping carts rather than completed purchases. Consequently, the study documents differences in offered prices without establishing the final amounts every participant would have paid.
The investigation also does not establish that sensitive personal information caused the differences. Instacart said the experiments randomly assigned shoppers to pricing groups and were not based on their individual characteristics or behavior.
Following public scrutiny, Instacart announced in December 2025 that it would discontinue the pricing experiments. Consumer Reports confirmed the announcement on December 22.
The findings demonstrate that shoppers can encounter different advertised prices for identical products. They do not, by themselves, prove widespread surveillance-based pricing or establish how frequently comparable experiments occur elsewhere.
Why Retailers Are Investing in Pricing Technology
For retailers, pricing technology offers operational advantages. Electronic labels can make it easier to implement approved price changes, while analytical systems can help businesses evaluate inventory, customer demand and competitive conditions.
Price optimization software may recommend discounts to clear excess inventory, identify products facing competitive pressure or estimate how changes could affect sales. Depending on a company's objectives, those recommendations could involve higher prices, lower prices or leaving existing prices unchanged.
Walmart has sought to address concerns surrounding its expanding use of electronic shelf labels.
In a published explanation of its digital shelf-label system, the retailer says prices are determined centrally and reviewed by employees. The company maintains that the displays show the same shelf prices to customers rather than determining prices according to individual identities.
Those statements describe Walmart's policy and intended use of the technology; they should not be interpreted as independent verification of every pricing decision.
Research also offers a more measured picture of electronic shelf labels than some public speculation suggests.
A study of a U.S. grocery chain that adopted electronic labels across more than 100 stores found virtually no surge pricing before or after their introduction. The researchers reported that temporary price increases remained exceptionally uncommon, with no statistically significant increase attributable to the rollout.
However, the study examined a particular retailer and cannot establish how every supermarket chain will use similar equipment.
The larger commercial question is how retailers balance pricing flexibility and operating efficiency against consumers' expectations of consistency and fairness. A system that improves operations could still create reputational or regulatory risks if customers cannot understand why prices differ.
How Regulators Are Responding to Surveillance Pricing
Federal and state authorities are increasingly examining whether businesses use personal information to determine what customers pay.
In January 2025, the Federal Trade Commission published initial findings from an investigation into surveillance-pricing intermediaries.
The FTC found that the examined firms offered technology capable of using detailed consumer information, including location, browsing activity and shopping behavior, to influence personalized prices, discounts or product recommendations.
According to the agency, those intermediaries worked with at least 250 clients selling goods and services across multiple industries.
That figure does not mean 250 retailers were independently proven to charge individualized prices. It identifies clients of the examined pricing technology providers, whose services and implementations can differ.
The FTC has also proposed an enforcement policy addressing potentially deceptive failures to disclose the use of personal data in individualized pricing. A proposed policy is not equivalent to an enacted nationwide ban or a final finding that a particular business violated the law.
At the state level, lawmakers have pursued more direct restrictions.
New Jersey enacted the Fair Price Protection Act on July 23, 2026. According to the governor's official announcement, the legislation restricts using consumers' personal data to determine individualized grocery prices while preserving certain loyalty and promotional arrangements.
The law also establishes a one-year moratorium on newly deployed electronic shelf labels, with exceptions for repairing or replacing existing installations. Its provisions have different implementation timelines, so enactment should not be confused with every restriction already taking effect.
Maryland and Connecticut have also enacted measures addressing surveillance-based pricing. Their approaches differ in the transactions covered and the requirements imposed on businesses.
These developments reflect growing regulatory concern, but they do not create a uniform national legal framework. Whether a particular pricing practice is restricted depends on the relevant jurisdiction, statutory definitions, exceptions and effective dates.
What Shoppers Should Watch Next
Consumers can compare advertised prices, review checkout totals and examine a retailer's disclosures, but it is often difficult to determine exactly which information an algorithm uses to generate a price.
A changing shelf price alone reveals little about the underlying decision. It could reflect an ordinary promotion, a supplier cost adjustment, an inventory decision or another business factor.
Similarly, two customers encountering different online prices does not automatically establish that personal data was used. Differences may result from promotions, purchasing channels, experimental pricing groups or other conditions.
The most important developments to watch are whether retailers disclose more about their pricing systems, whether regulators establish clearer rules for personal-data-based pricing, and whether independent researchers uncover additional evidence about how consumers are affected.
AI is giving businesses increasingly sophisticated tools to evaluate and manage prices. The unresolved issue is not simply how quickly those prices can change, but whether shoppers can understand the rules determining what they are asked to pay.
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