McDonald’s Faces Lawsuit Over AI Pricing System
McDonald’s is facing a lawsuit over its AI pricing system. Illinois resident Michael Thomas has filed a lawsuit in the federal court in Chicago, seeking to represent all McDonald’s customers in the United States to claim damages, alleging that the company used AI to coordinate menu prices between franchise and company-owned stores, potentially violating the U.S. Antitrust Law.
The lawsuit was filed on October 2nd. The plaintiff believes that McDonald’s franchise stores should independently determine prices, but the company aggregated a large amount of non-public sales data from numerous restaurants to train pricing algorithms, and then provided price recommendations to individual restaurants. The lawsuit alleges that this practice led to restaurants that should have been competing against each other participating in price coordination, weakening price competition and causing consumers to pay higher prices.
Thomas claims that he has frequently dined at different McDonald’s restaurants and has paid different prices for the same item at different times. He hopes to represent millions of affected customers in the U.S. for compensation.
Currently, the court has not determined that McDonald’s has violated the law, nor has it approved the case to proceed as a class-action lawsuit.
According to a previous investigation by Reuters, the implicated AI system analyzes millions of transactions from nearly 14,000 McDonald’s restaurants across the U.S. and then uses machine learning to provide pricing recommendations to the restaurants. Factors considered by the system include the local customers’ price sensitivity and the publicly available menu prices of nearby competitors.
McDonald’s has stated that the allegations are speculative. The company has clarified that the AI system only provides pricing recommendations and does not determine how much a Big Mac or other items should be priced at, as franchisees still have the autonomy to set their own prices. The company also denied adjusting prices in real-time based on individual customers or specific time periods.