A federal antitrust lawsuit filed this week alleges McDonald’s uses an AI-powered “pricing engine” to set menu prices across U.S. locations, overcharging customers for Big Macs and fries. McDonald’s denies the claim. The company says it doesn’t use AI to determine what individual customers will pay, and gives franchisees “tools, resources, research and recommendations to help them make informed decisions.”
The case arrives as food retailers race to digitize. The courtroom may be just one front in a larger fight over who gets to decide how prices are set.
The Technology Spreads
Earlier this year, Kroger said it uses an AI platform called FlashFood to mark down perishables nearing the end of their shelf life and market them to shoppers through an app. Electronic shelf labels, which display prices on digital screens, are becoming more common at Kroger, Amazon Fresh, Walmart and Whole Foods, along with U.K. supermarkets Tesco, Morrisons and Asda. Revolut recently trialed facial-recognition checkout in select coffee shops, allowing customers to pay with a glance. On Wednesday, Sainsbury’s released SmartLists, an AI feature that helps customers build shopping lists from typed meal ideas or uploaded photos.
Amazon Fresh, Whole Foods, Tesco, Morrisons, Asda and Revolut didn’t immediately respond to CNBC’s requests for comment on their AI use.
Walmart and Kroger, meanwhile, have said in recent years that they don’t use dynamic or surge pricing to set individualized prices. They say the tools help streamline operations.
What Experts Say
Dynamic pricing itself isn’t new. “Dynamic pricing means changing prices in response to changing market conditions, such as demand, timing, capacity or competitors’ prices,” said Miroslava Marinova, a senior lecturer of commercial law at the University of East London. “It is not new. Airlines, hotels, and ride-hailing services have used it for years.”
Marinova also acknowledged a point often lost in the alarm: dynamic and personalized pricing aren’t automatically harmful to shoppers. They can lower prices for some consumers, making some products and services more accessible.
The concern, she said, is that the distinction between the two is blurring. “Dynamic pricing responds primarily to market conditions, whereas personalised pricing uses information about the consumer to estimate willingness to pay,” she said. As retailers combine market data with detailed consumer data, “the boundary between dynamic and personalised pricing becomes thinner.” If shoppers can’t understand a price, compare it with what others pay, or switch suppliers, she warned, “the normal disciplining effect of consumer choice becomes weaker.”
The Inflation Measurement Problem
In April, two Bank of England economists, Clare Lombardelli and Rupal Patel, raised a different issue. More sophisticated technology, they said, is making prices change more often and become more individualized, while firms could charge “as close to the maximum price a consumer is willing to pay for a good or service.” They called this “perfect price discrimination.”
That creates a headache for statisticians. The consumer price index relies on a representative sample of prices. “That works well when prices mostly move slowly and uniformly,” the economists said. “But when prices shift continually – and differently for each shopper – the idea of a ‘representative’ price becomes strained.” Personalized pricing, they added, “splinters the consumer experience,” leaving households with different inflation rates and aggregate measures that may no longer reflect what families actually pay.
The State Response
Statehouses aren’t waiting. New York requires most businesses that use customers’ personal data to set prices to clearly disclose that use. Maryland has restricted food retailers and delivery services from using personalized, data-driven pricing to charge higher prices for certain food. New Jersey and Connecticut have enacted measures targeting “surveillance pricing.”
The patchwork is taking shape, with different states applying different rules to the same technology.
Why This Matters:
The McDonald’s suit and state laws raise a question that markets and regulators will wrestle with for years: when does a pricing tool become a legal problem? Retailers say AI helps them cut waste and run leaner operations. Plaintiffs and lawmakers see a risk of overcharging. Courts will now have to determine where legitimate price optimization ends. Meanwhile, a growing patchwork of state rules could raise compliance costs for national chains, costs that can ultimately reach shoppers. New York’s disclosure requirements address transparency without banning the practice outright. From that perspective, the approach leaves room for competition and consumer choice to do the disciplining, provided shoppers can actually see and compare what they’re being charged.