Retailers Gain Pricing Tools as Shoppers Face Opacity

The Federal Trade Commission alleged that Amazon’s Project Nessie helped generate more than $1 billion in excess profits by identifying products whose prices could rise, with competitors likely to follow. Amazon disputes the allegation, and a trial is scheduled for next year. The case centers on software that can shape prices across retail markets, as shoppers raise questions about how companies use data and algorithms.

Who Controls the Price

Businesses have used algorithmic pricing systems for decades. Artificial intelligence can help them spot patterns in sales, competitors’ prices and other information, then predict demand and estimate how prices could affect sales and profits. These tools support dynamic pricing, which responds to market conditions, and personalized pricing, which may draw on customers’ locations, incomes and web-browsing habits.

A survey by global consulting company Simon-Kucher of more than 2,200 business leaders across 28 countries and 39 industries found that 41% used AI software to gather market intelligence, including competitors’ prices. Another 28% used it for “real-time price optimization.” That term means selecting prices to advance business aims, such as increasing profits, attracting shoppers or clearing unsold goods.

The National Retail Federation, which represents large and small stores, described algorithmic pricing as a way to monitor and adjust prices according to supply, demand, seasonality, competitors’ prices and other factors. Retailers’ use of AI to set prices remains unclear.

Consumers know that prices change for flights, hotel rooms and rides. But digital price labels are spreading to major U.S. retailers, including Walmart and Whole Foods, raising concerns about price changes in everyday shopping. Walmart CEO John Furner wrote that the tags save workers’ time and keep prices current. He said they aren’t used to raise prices based on weather, time of day or an individual shopper. “We price the product, not the person,” Furner wrote.

Retailers generally update electronic shelf prices on a regular 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. Consumer advocates say the labels could eventually enable surge or personalized pricing, while labor unions have opposed the technology.

Data, Laws and Enforcement

Companies don’t always explain what customer data they collect or how they use it, adding to consumer suspicion. Katie Thomas, who leads an internal consumer behavior think tank at management consulting firm Kearney, said: “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.”

An FTC staff report released in January 2025 found that intermediaries offering tools to tailor prices and promotions worked with at least 250 clients, including grocery and clothing retailers. The prevalence of personalized pricing remains unclear. Maryland, New Jersey and Connecticut enacted restrictions on using shoppers’ personal data to determine prices. The Maryland and New Jersey laws focus on groceries, with exceptions for certain loyalty discounts and other promotional offers; Connecticut’s law covers a broader range of retail purchases.

Legislators in at least 30 states considered pricing bills this year, including measures addressing algorithmic and personalized pricing, according to the National Conference of State Legislatures. The FTC has proposed an enforcement policy warning that failing to disclose the use of personal data to set individualized prices could violate consumer protection law.

California prosecutors sued Target in 2022, alleging its app showed 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 geofencing technology to increase prices. The retailer denied personalizing prices based on guests’ data or behavior and said the app function was used to “provide guests with accurate pricing, which can vary across stores and channels.”

A 2025 investigation by Consumer Reports, Groundwork Collaborative and More Perfect Union found that Instacart showed shoppers different prices for identical products at the same stores. Instacart later ended what it described as tests that randomly assigned shoppers to groups, rather than setting prices based on personal information.

Corporate Claims and Wider Systems

In a 2023 antitrust lawsuit against Amazon, the FTC challenged Project Nessie among other practices. Amazon said the FTC’s allegations “grossly mischaracterize” the tool. It said the tool aimed to prevent retail price-matching from producing unsustainably low prices. Amazon said it tested the tool for a few years, found it didn’t work as intended and scrapped it before the lawsuit.

A recent consumer lawsuit against McDonald’s alleged its pricing system used nonpublic sales data from competing locations to coordinate prices. The Chicago-based company called the lawsuit “filled with inaccuracies” and said it makes the tool available to U.S. franchisees to help them set prices at their own restaurants.

A United Kingdom coalition of 23 organisations, including the English Premier League, warned the Albanese government that Australia could become a “content laundering nation” for AI companies if copyright laws are weakened. Separately, an Australian Financial Review headline said AI bots generate more than 57 per cent of web traffic and described risks for retail, banking and travel. Its summary said JPMorgan filters out external artificial intelligence agents; the page provided no further details from the item.