U.S. consumers are not merely exasperated by elevated prices; they are incensed and bewildered by the increasingly sophisticated, technology-driven mechanisms through which restaurant chains and major retailers are determining those prices.

Digital price tags are rapidly supplanting their paper counterparts in grocery aisles.

Artificial intelligence tools assist businesses in determining what to charge by anticipating how customers might respond.

Terms such as “dynamic pricing” and “surveillance pricing” are fomenting anxiety on social media, where users speculate as to whether different people are being charged disparate prices for the same product.

Americans have grown inured to fluctuating prices when booking flights, hotel rooms and rides, yet the prospect of quotidian expenditure being shaped by algorithms they do not comprehend and personal data they may not even realize they are divulging has struck a raw nerve.

“There are major tensions unfolding at present between who will truly wield power with some of these algorithms and the deployment of bots and AI: the companies or the shopper,” said Katie Thomas, who leads an internal consumer behavior think tank at the management consulting firm Kearney.

Companies employing the technology contend that certain apprehensions stem from misconceptions concerning the modus operandi of their pricing instruments.

Walmart CEO John Furner remarked in a blog post last month that digital price tags conserve workers’ time and ensure prices remain current.

He asserted that the labels are not deployed to inflate prices in response to weather conditions, time of day or the individual shopper.

“We price the product, not the person,” Furner wrote.

Yet companies are not invariably transparent regarding the customer data they collect and the manner in which it is used—a circumstance that has rendered consumers suspicious and given rise to speculation.

By way of illustration, social media posts falsely imply that the electronic shelf labels Walmart intends to install in all its U.S. stores scan shoppers’ faces or cellphones in order to set individualized prices, Thomas said.

Lawmakers and regulators are taking action.

According to the National Conference of State Legislatures, legislators in no fewer than 30 states have this year weighed pricing bills, among them measures addressing algorithmic and personalized pricing.

The Federal Trade Commission has proposed an enforcement policy cautioning businesses that any failure to disclose their utilization of personal data for the purpose of setting individualized prices could constitute a violation of consumer protection law.

The following constitute a selection of the pricing practices and technologies attracting scrutiny.

What it is: Dynamic pricing entails the calibration of prices in accordance with fluctuating market conditions, supply and demand among them.

An airline that adjusts ticket prices as departures approach is employing dynamic pricing.

Uber’s practice of elevating fares when demand outstrips the supply of available drivers, such as during rush hour, constitutes a variant of dynamic pricing known as surge pricing.

Why it matters: Frequent price fluctuations extend far beyond the realm of food.

Decodo, a web data company, tracked price changes throughout 2025 across products spanning electronics, clothing, and home improvement supplies.

Roughly half of the U.S. changes it recorded were decreases, contrary to consumers’ assumptions that dynamic pricing serves only to raise prices, said Gabriele Vitke, a senior product marketing manager.

What they are: digital displays that afford stores the means to update shelf prices electronically, obviating the need to replace paper tags.

Why it matters: Digital price labels, long established in Europe and Asia, are attracting heightened scrutiny as they proliferate among major U.S. retailers such as Walmart and Whole Foods.

Consumer advocates have contended that digital labels could ultimately be deployed for surge pricing or personalized pricing.

Labor unions, too, have voiced opposition to the technology.

Electronic shelf labels facilitate more frequent price adjustments yet do not necessarily precipitate higher prices during periods of robust demand.

Retailers typically revise electronic shelf prices on a regular schedule, often weekly, because shoppers prize consistency, said Asa Farquhar of Relex Solutions, a retail technology company.

Researchers who tracked prices at an unnamed grocery chain found “virtually no surge pricing” after the labels were introduced.

“Altering prices over the course of the day, in the manner of airlines or rideshare applications, is exceedingly uncommon in grocery and general merchandise at present,” Farquhar said.

What it is: Personalized pricing entails proffering customers differential prices and discounts predicated upon their locations, incomes, web-browsing habits and other information pertaining to individuals or groups of shoppers.

Certain advocacy groups and regulators employ the term “surveillance pricing” to denote the selfsame practice.

Why it matters: The extent to which businesses deploy personal information to customize prices remains unclear.

An FTC staff report released in January 2025 found that intermediaries proffering tools capable of tailoring prices and promotions had worked with at least 250 clients, including grocery and clothing retailers.

Lawmakers in Maryland, New Jersey and Connecticut have recently enacted restrictions on the use of 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 encompasses a broader range of retail purchases.

In 2022, California prosecutors filed suit against Target, alleging that the retailer’s app had displayed lower prices before shoppers entered stores and then raised them once they were inside.

Target agreed to a $5 million settlement and a prohibition on employing so-called geofencing technology to raise prices.

Target asserted that the app functionality in question was designed to “provide guests with accurate pricing, which can vary across stores and channels.”

The retailer maintained that it did not personalize prices on the basis of a guest’s data or behavior and remains “committed to clear, transparent pricing.”

Disparate pricing does not ipso facto imply that personal data was exploited.

Last year, an investigation conducted by Consumer Reports, Groundwork Collaborative and More Perfect Union ascertained that shoppers on Instacart were presented with divergent prices for identical products at the same stores.

Instacart subsequently discontinued what it characterized as tests that randomly assigned shoppers to groups rather than setting prices on the basis of their personal information.

What it is: Algorithmic pricing employs software to recommend or automatically set prices.

Companies have deployed such systems for decades.

AI can assist the software in discerning patterns in sales, competitors’ prices and other information so as 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: The prevalence with which retailers harness AI to inform price-setting remains indeterminate, yet research indicates that businesses across industries are increasingly embracing it.

Simon-Kucher, a global consulting firm, surveyed upwards of 2,200 business leaders spanning 28 countries and 39 industries last year, and 41% reported employing AI software to gather market intelligence, including competitors’ prices.

A further 28% said they deployed it for “real-time price optimization.”

Price optimization denotes the selection of prices calculated to further business objectives, such as augmenting profits, attracting shoppers or clearing unsold goods.

The National Retail Federation, which represents both large and small retailers, said algorithmic pricing constitutes a novel means of accomplishing what retailers have always done: monitoring and adjusting prices in accordance with supply, demand, seasonality, competitors’ prices and other factors.

Certain lawsuits have alleged that companies employed pricing algorithms with a view to undermining competition.

A 2023 antitrust suit instituted by the FTC against Amazon contested, inter alia, an algorithmic instrument designated Project Nessie.

The agency contended that Amazon deployed said tool to pinpoint products whose prices it could elevate with competitors inclined to follow suit, thereby accruing in excess of $1 billion in surplus profits.

A trial has been scheduled for next year, with Amazon contending that the FTC's allegations "grossly mischaracterize" the pricing tool.

Project Nessie was intended to prevent retail price-matching practices from generating unsustainably low prices, the e-commerce giant said.

Amazon said it had tested the tool for a few years, but it did not work as intended and was scrapped before the federal agency’s lawsuit.

A recent consumer lawsuit against McDonald’s alleged that its pricing system exploits nonpublic sales data from competing locations in order to coordinate prices.

The Chicago-based burger giant contended that the lawsuit was “filled with inaccuracies” and that the company makes the tool available to U.S. franchisees to assist them in setting prices at their individual restaurants.