Fast-food giants and supermarkets are launching a range of AI tools that may affect the prices consumers pay, but experts warn that the spread of data-driven tools could make personalized pricing more feasible.

Just this week, a federal antitrust lawsuit filed against McDonald's alleged that the fast-food giant uses a "pricing engine" driven by AI to set menu prices at stores across the United States, charging consumers more for Big Macs and fries.

McDonald's denies using AI to determine how much individual customers are willing to pay, and states that the company provides franchisees with "tools, resources, research, and advice to help them make informed decisions."

Nevertheless, global food companies are increasingly leveraging AI to drive operational digitization. Earlier this year, the American chain grocer Kroger announced that it was using a platform called FlashFood to discount perishable goods nearing their expiration dates, and to push these discounts to shoppers through an app.

At the same time, electronic shelf labels ( ESLs ) – which are technologies that display product prices on digital screens inside stores – are becoming increasingly common in supermarkets such as Kroger , Amazon Fresh , Walmart , and Whole Foods .

This technology is also becoming increasingly popular in British supermarkets, including Tesco, Morrisons, and Asda. Recently, the global financial platform Revolut has also piloted facial recognition checkout in some coffee shops, allowing customers to pay with just a glance.

CNBC contacted Amazon Fresh, Whole Foods, Tesco, Morrisons, Asda, and Revolut regarding the usage of AI to seek their comments, but did not receive a response immediately.

As the use of AI in the retail industry becomes increasingly common, experts warn that this may lead to more dynamic pricing, where prices change frequently and rapidly based on real-time conditions, thereby significantly affecting the shopping experience for consumers.

Miroslava Marinova, a senior lecturer in business law at the University of East London, said to CNBC: "Dynamic pricing refers to adjusting prices according to constantly changing market conditions, such as demand, time, capacity, or the prices of competitors. It's nothing new. Airlines, hotels, and online car-hailing services have been using it for many years."

Central Bank of England economists Clare Lombardelli and Rupal Patel stated in April that more advanced technologies are leading to more frequent and personalized price changes, which may encourage more businesses to charge consumers "as close as possible to the highest price they are willing to pay for a particular good or service." They refer to this as "perfect price discrimination."

These situations may make it more difficult for statisticians to “measure and interpret” monthly inflation data, as the Consumer Price Index is based on a representative sample of shoppers’ prices.

An economist from the Bank of England added, "This method works well when prices change slowly and consistently for the most part. However, when prices are constantly changing—and vary for each shopper—the concept of a 'representative' price becomes tenuous."

AI Collects more consumer data

Although dynamic pricing has long existed, economists at the Bank of England and Marinova point out that tools such as ESLs and facial recognition checkout are changing the amount of consumer information that businesses can collect, including transaction history, browsing behavior, geographical location, and purchasing patterns, among others.

On Wednesday, the British chain supermarket Sainsbury launched “SmartLists”, which is a AI feature that helps customers create shopping lists and find products by uploading photos of the items needed or by entering ideas for meals.

Marinova explains, "This is also why the distinction between dynamic pricing and personalized pricing is becoming less clear in practice. Dynamic pricing mainly responds to market conditions, while personalized pricing utilizes information about consumers to estimate their willingness to pay."

As companies begin to use both pricing systems simultaneously, there are doubts from the outside world as to whether customer information is being used to determine the prices that consumers see.

Marinova added, "When retailers combine market-level information with increasingly detailed consumer data, the lines between dynamic pricing and personalized pricing become blurrier."

Walmart and Kroger have publicly asserted in recent years that they do not use dynamic pricing or peak pricing to set personalized prices for different customers, but rather use relevant tools to simplify operations.

Several states in the United States are taking measures to restrict data-driven pricing. New York State requires that most companies that use customers' personal data for pricing must clearly disclose this information. Maryland has restricted food retailers and delivery services from using personalized, data-driven pricing to charge higher prices for certain foods, while New Jersey and Connecticut have also enacted measures targeting “monitoring pricing.”

Consumers are at a disadvantage in their choices.

Marinova indicates that dynamic pricing and personalized pricing are not necessarily harmful to consumers, as they can provide discounts for some consumers, making certain goods and services more accessible.

However, the risk of personalized pricing is that consumers no longer know whether the prices they see reflect the general market conditions or are influenced by their own behavioral information.

She said, "This will make price comparisons more difficult, and it will also be harder to determine whether another consumer has been offered a different price for the same product. If consumers cannot understand why they are paying a certain price, cannot compare it with the prices others are paying, and cannot effectively switch to other suppliers, then the normal regulatory role of consumers in the market will be weakened."

British Central Bank economists added that another challenge is that personalized pricing will "fragment the consumer experience," which means that households will face increasingly different inflation rates.

They say, "When the same item has different prices, inflation becomes more personalized—and overall indicators may no longer reflect the actual experiences of households."