McDonald's Sued Over AI Tool That Recommends Prices to Franchisees
A Illinois consumer has sued McDonald's over an AI system that recommends menu prices to US franchisees, alleging it may enable price coordination. The company denies it.

McDonald's is facing a lawsuit in the United States over an artificial intelligence tool it has used for years to recommend menu prices. The complaint, filed on 2 October by Illinois consumer Michael Thomas, argues the system could help coordinate prices among restaurants that are supposed to compete independently.
According to the case, the tool analyses each restaurant's sales, its location and competitors' prices, then calculates what every menu item should cost. Thomas alleges McDonald's uses commercial data that franchisees would not normally share with one another, including each location's sales results, to recommend prices that could reduce competition and push costs up.
Thomas, who usually buys a cheeseburger, fries and a soft drink, began questioning the system after noticing price differences between nearby restaurants.
McDonald's says the AI does not set prices
The company rejects the accusations. It says its tools only offer recommendations that franchisees can accept or ignore. In a statement on its website, McDonald's insists it does not use dynamic pricing and that the AI does not automatically change what customers pay.
McDonald's also notes that about 95% of its 14,000 US restaurants are run by franchisees, who are responsible for setting their own prices. The plaintiffs counter that the company holds enough sway over those operators to pressure them into following the system's recommendations. An earlier investigation had reported that some franchisees felt such pressure, an interpretation McDonald's rejects.
What happens next
The lawsuit asks for permission to represent other affected consumers as a class and seeks compensation. No court has yet ruled on whether the tool was actually used to coordinate prices, so the allegations remain unproven.
The case adds to growing scrutiny of algorithmic pricing software, where the question is whether shared data and common recommendations can amount to coordination even when each business formally sets its own prices.
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