People pick up menus inside a McDonald’s restaurant in Times Square, Manhattan, New York City, September 29, 2026.
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Fast food giants and supermarkets are introducing a range of AI tools that could influence the prices shoppers pay, but experts warn that the proliferation of data-driven tools could make it easier to introduce personalized pricing.
Just this week, a federal antitrust lawsuit was filed. mcdonalds The fast food giant used an AI-powered “pricing engine” to set menu prices across its U.S. stores, alleging it was charging customers exorbitant amounts for Big Macs and fries.
McDonald’s denied using AI to determine individual customers’ willingness to pay, saying it provides franchisees with “tools, resources, research and recommendations to help them make informed decisions.”
Still, food companies around the world are digitizing their operations with the help of AI. Earlier this year, an American grocery chain kroger The company said it uses an AI platform called FlashFood to mark down fresh food near the end of its best-before date and sell it to shoppers through its app.
On the other hand, electronic shelf labels (ESL), which display the prices of in-store products on digital screens, are being used by Kroger and others. Amazon fresh, walmartWhole Foods.
The technology is also gaining traction in British supermarkets. tescoMorrisons and Asda. Most recently, global financial platform Revolut trialled facial recognition checkout in some coffee shops, allowing customers to pay with just a glance.
CNBC reached out to Amazon Fresh, Whole Foods, Tesco, Morrisons, Asda and Revolt for comment on their use of AI, but did not immediately respond.
As the use of AI becomes more common among retailers, experts warn that this could lead to more dynamic pricing. This refers to frequent and rapid real-time price changes that can dramatically impact the shopper experience.
“Dynamic pricing means changing prices in response to changing market conditions, such as demand, timing, capacity, and competitor prices,” Miroslava Marinova, a senior lecturer in commercial law at the University of East London, told CNBC. “This is not new. Airlines, hotels and ride-hailing services have been using it for years.”
In April, Bank of England economists Claire Lombardelli and Rupal Patel said that as technology becomes more sophisticated, price fluctuations become more frequent and more individualized, potentially leading to more companies charging “a price closer to the highest price consumers are willing to pay for goods and services,” which they define as “absolute price discrimination.”
Because the consumer price index is based on a representative sample of shoppers’ prices, this situation can make it difficult for statisticians to “measure and interpret” monthly inflation data.
BOE economists added: “This works well when prices move fairly slowly and evenly. However, when prices change continuously and vary from shopper to shopper, the idea of a ‘representative’ price becomes strained.”
AI collects more consumer data
While dynamic pricing has been working for a long time, BOE economist and Marinova noted that AI tools like ESL and facial recognition checkout are changing the amount of information companies can collect from consumers, from transaction history to browsing behavior, location and purchasing patterns.
On Wednesday, British supermarket chain Sainsbury’s launched SmartLists, an AI feature that helps customers create shopping lists and find items by simply uploading photos of what they need or entering meal ideas.
“This is also why the traditional distinction between dynamic pricing and personalized pricing is actually no longer clear-cut,” Marinova explained. “Dynamic pricing primarily reacts to market conditions, while personalized pricing uses information about the consumer to estimate willingness to pay.”
Because companies use both pricing systems, questions arise as to whether customer information is being used to determine the prices consumers see.
“The line between dynamic pricing and personalized pricing is becoming thinner as retailers combine market-level information with increasingly detailed consumer data,” Marinova added.
Walmart and Kroger have publicly argued in recent years that they no longer use dynamic or surge pricing to set personalized prices for customers, but instead use tools to streamline their operations.
Several U.S. states are moving to curb data-based pricing. New York state requires most companies that use customers’ personal data to clearly disclose it and set prices. Maryland restricts food retailers and delivery services from charging higher prices for certain foods using pricing based on personalized data, and New Jersey and Connecticut have enacted measures targeting “surveillance pricing.”
Consumer choice is violated
Dynamic, personalized pricing isn’t necessarily a bad thing for shoppers, Marinova said, explaining that it could allow for discounts on items and make some products and services more accessible for some consumers.
However, the risk of individualized pricing is that consumers no longer know whether the price they are getting reflects general market conditions or is influenced by information about their own behavior.
“That makes it very difficult to compare prices and know if different consumers are being offered different prices for the same product,” she says. “The normal disciplining effects of consumer choice are weakened when consumers cannot understand why they received a particular price, cannot compare it with prices offered by other suppliers, and cannot effectively switch to another supplier.”
BOE economists added that a further challenge is that personalized pricing is “fragmenting the consumer experience”, meaning households increasingly face different inflation rates.
“And when prices for the same thing differ, inflation becomes even more individualized and aggregate indicators may no longer reflect household experience,” they said.
