The Big Mac Price Is Looking Back

Reuters reports that McDonald’s is exploring the use of artificial intelligence in pricing as retailers adopt software that can forecast demand and refine offers. McDonald’s operates through a large franchise system, so any practical use would have to pass through store economics, local menus and franchisee decisions. The available reporting does not establish that McDonald’s is currently charging two identified customers different prices for the same item, nor does it fully specify the markets, tests or customer data that would govern such a result.

There is an ordinary business case for the technology. A restaurant can use sales patterns, time of day, inventory and local demand to reduce waste, staff a rush and offer a discount when traffic is slow. Stores already charge different prices across locations because rent, wages and franchise costs differ. A breakfast promotion that changes by market is dynamic pricing. It is not automatically surveillance pricing.

The line moves when the system stops asking what this store should charge and starts asking what this particular customer might endure. Location, device type, visit time and loyalty history can become clues about urgency and willingness to pay. WIRED reports that consumer advocate Lindsay Owens received a 515-page file after requesting the data associated with her McDonald’s app interactions; it included an estimate that she had a zero percent chance of leaving as a customer. Loyalty, in that model, can look less like something to reward than something safe to tax.

The menu board used to state the bargain before the buyer approached. An individualized system can reverse the order: identify the buyer, calculate the attachment, then produce the offer. That does not prove unlawful discrimination, and different coupons are not necessarily different base prices. It does mean that customers need enough information to distinguish a discount from a higher starting point wearing a discount’s paper hat.

Shoppers can perform a rough audit now. Compare the app with the in-store board and public web menu, check the same order while signed out, inspect delivery markups, and keep receipts from repeat purchases. These comparisons will not reveal every input, but they can show whether the apparent deal survives outside a loyalty profile. An app-only bargain may still be worthwhile; the customer should know what data purchased it.

Regulators should require more than a general notice that automation is involved. A restaurant using AI to shape offers should disclose the base price, categories of data used, possible range of variation, availability of an opt-out and whether franchisees control the final amount. The receipt should explain the promotion well enough to reproduce it. Until then, the practical test is simple: if the seller knows why the Big Mac cost that much, the buyer should be allowed to know too.