McDonald’s Uses AI to Recommend Local Menu Prices
Matthew Leo · Published October 1, 2026 · Business & Policy
McDonald's is using a machine-learning system to recommend menu prices at nearly 14,000 U.S. restaurants. It considers millions of daily transactions, local competition and what the company describes as customers' willingness to pay.
The system does not set a single price across the chain. It recommends a price for each item at each restaurant, and franchisees officially retain the final decision. The concern is how much practical freedom those operators have and whether customers know when an algorithm helped shape the price in front of them.
What Reuters found
A Reuters investigation found that McDonald's increasingly uses the pricing engine in the United States and some other markets. Five franchisees told the news service that the company pressured them to follow its recommendations, while McDonald's said operators remain free to set their own prices.
Reuters also checked the McDonald's app in September. One company-run restaurant in Fresno, California, listed a Big Mac at US$5.69. Another company-run location two miles away listed the same item at US$6.89, a 21 per cent difference. Reuters could not determine whether the pricing system caused that gap.
That caveat is important. Restaurant prices have long varied with rent, wages, local promotions and franchise decisions. The new element is a system that can process far more data and recommend changes at a much finer level.
This is not confirmed in Canada
Reuters reported use in the United States and some global markets, but the reporting did not confirm that McDonald's Canada uses the same engine. Mapletechie found no public Canadian documentation identifying which restaurants, if any, use it.
Canadian customers can still see location-based price differences in restaurant apps. A difference alone does not prove that an AI tool produced it. Anyone comparing prices should check the same item, size and promotion at nearby locations, and note whether delivery or third-party fees are included.
Why Canadian regulators are watching algorithms
Canada's Competition Bureau has already been studying the relationship between algorithmic pricing and competition. Its discussion paper on algorithmic pricing explains that software can improve ordinary pricing decisions but may also make it easier for rivals to coordinate or react quickly to one another.
The McDonald's system raises a related franchise question. If many nominally independent restaurants receive recommendations from the same corporate engine, regulators may want to know which data the system uses, how strongly operators are encouraged to follow it and whether it incorporates competitors' current prices.
None of that proves illegal coordination. It explains why the design and operation of the system matter more than the label “AI pricing.”
What customers should look for
McDonald's could reduce confusion by stating where the tool operates, how often recommendations change and whether personal account data affects an individual offer. The current reporting describes restaurant-level recommendations, not a different price generated for each person.
Customers who want to compare can change the selected restaurant in the official app before ordering. Screenshots taken at the same time can show whether nearby locations list different base prices, but they still cannot reveal why those prices differ.
For Canada, the unanswered question is straightforward: is the engine in use here, and if so, under what rules? Until McDonald's Canada answers that, claims that Canadian Big Macs are being priced by this specific system would go beyond the evidence.
Tags: McDonald's, algorithmic pricing, consumer prices, Canada