麦当劳用机器学习为各门店推荐菜单价格

McDonald’s is using machine-learning technology to recommend menu prices at individual restaurants, extending the use of AI into pricing decisions across its franchise network.

The system analyses transaction data from the fast-food chain’s restaurants and produces recommended prices for individual menu items based on conditions at each location. Reuters first detailed how the pricing technology is being used across the US and in some international markets.

According to Reuters, the pricing engine processes data from millions of daily transactions across McDonald’s US restaurants. Factors considered by the system include local competition and estimates of how sensitive customers in a particular area are to changes in price.

The technology uses machine-learning algorithms rather than generative AI. It analyses existing transaction and pricing data to produce recommendations, with McDonald’s describing the system as a tool that supports pricing decisions rather than automatically setting prices.

How the pricing system works

Reuters reviewed screenshots of the McDonald’s pricing platform and interviewed nine people with direct knowledge of the company’s pricing strategy. The platform includes information about nearby competitors, including publicly available menu prices from other restaurant chains.

Two company-operated McDonald’s restaurants about two miles apart in Fresno, California, were charging $5.69 and $6.89, respectively, for a Big Mac in September. The report did not establish whether the pricing engine caused the difference.

McDonald’s has used some form of AI-assisted pricing technology since at least 2019. The technology has since developed into a proprietary system that generates pricing recommendations for individual restaurant locations.

Company documents reviewed as part of the reporting show that recommendations are distributed to franchisees periodically. McDonald’s said the platform is optional and provides restaurant-specific recommendations that operators can consider when setting menu prices.

The system estimates willingness to pay at the restaurant level and generates recommendations for each location. The reporting did not indicate that McDonald’s uses individual customers’ personal data to generate customer-specific prices.

That separates the system from personalised pricing, where companies use information about individual consumers to determine what they should be charged. US regulators are examining those practices separately, including how personal data is used in pricing decisions.

Franchise control and pricing governance

McDonald’s says franchisees remain responsible for determining final menu prices. The company has also said restaurants operating only a few miles apart can face different costs and market conditions, contributing to differences in what customers pay.

McDonald’s says 90% of its US restaurants are independently owned and operated, with franchisees retaining the ability to set their own prices. Nearly 95% of its locations globally are run by franchisees.

McDonald’s also updated its global franchising standards from January 1, 2026, placing greater emphasis on customer value. Under those standards, franchisees continue to set prices and work directly with third-party pricing advisers, while McDonald’s evaluates the resulting customer value as part of its business reviews.

Some franchisees interviewed for the Reuters investigation said they had faced pressure to follow the pricing recommendations. McDonald’s disputed that characterisation and said operators remain free to determine their final prices.

The company also monitors differences between recommended and actual prices, according to the report. McDonald’s maintains that the pricing platform is advisory and that franchisees retain control over final menu prices.

Algorithmic pricing draws regulatory attention

The Federal Trade Commission is separately examining personalised pricing, which it defines as using personal data to set prices based on how much a business believes an individual consumer is willing to spend. In August 2026, the agency proposed guidance covering the use of such practices.

The FTC said personalised pricing is not automatically unlawful, but companies can face scrutiny if personal information is used in ways that are unfair or deceptive, including when relevant pricing practices are not disclosed. McDonald’s system differs from that model because it recommends prices at the restaurant level rather than setting customer-specific prices.

Screenshots of the McDonald’s pricing platform reviewed by Reuters also include an antitrust warning stating that restaurant owners “may be competitors of each other.” McDonald’s said the warning reflects its approach to competition-law compliance and does not indicate anticompetitive conduct.

US competition authorities have already addressed algorithmic pricing in other industries. In 2024, the Justice Department and FTC argued in hotel-pricing litigation that businesses cannot avoid antitrust rules simply by using software to generate pricing recommendations.

The Justice Department has also pursued RealPage over allegations that competing landlords supplied non-public pricing and leasing information to software used to generate rental-price recommendations. Under a proposed settlement announced in 2025, RealPage would face restrictions on using competitors’ non-public, competitively sensitive information when determining prices.

Those cases involve different markets and business models from McDonald’s, and US antitrust authorities have not accused McDonald’s of the conduct alleged in either case.

The Reuters investigation also found that McDonald’s has considered potential antitrust issues around its pricing programme and includes competition-law warnings in the platform provided to franchisees.

(Photo by Boshoku)

See also: McDonald’s tests Google-backed AI drive-thru ordering system

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