McDonald’s Faces AI Price-Fixing Lawsuit

McDonald’s is facing a proposed nationwide class-action lawsuit in the US alleging that the fast-food chain used an AI-powered pricing system to coordinate menu prices across independently operated restaurants. The complaint, filed in federal court in Illinois, argues that McDonald’s use of shared, nonpublic sales information and algorithm-generated pricing recommendations effectively reduced competition among franchisees and amounted to illegal price fixing.

McDonald’s strongly disputes that characterization. The company says its AI-assisted pricing tools do not set or change menu prices, do not use individual customers’ willingness to pay, and do not employ dynamic pricing. Instead, McDonald’s says franchisees independently decide what to charge and may use restaurant-specific pricing recommendations as one input in those decisions.

Key takeaways

• A proposed nationwide class action was filed against McDonald’s in the US District Court for the Northern District of Illinois on October 2, 2026.
• Plaintiff Michael Thomas alleges that McDonald’s centralized pricing technology enables price coordination among competing franchisees.
• The lawsuit invokes federal antitrust law, including Section 1 of the Sherman Act.
• The complaint alleges that McDonald’s pricing engine uses nonpublic, store-level sales information to generate recommendations.
• McDonald’s says its pricing tool provides optional recommendations, rather than setting or automatically changing prices.
• The company says franchisees independently determine menu prices.
• About 95% of McDonald’s roughly 14,000 US restaurants are operated by franchisees, according to AP.
• The case comes amid broader US scrutiny of algorithmic pricing in hotels, housing and other markets.
• US antitrust agencies have previously warned that companies cannot use algorithms to accomplish conduct that would be illegal if carried out by humans.
• The lawsuit is an allegation, not a finding that McDonald’s violated antitrust law.

What the McDonald’s lawsuit alleges

The case was brought by Illinois resident Michael Thomas, who is seeking to represent a potentially nationwide class of McDonald’s customers.

Court records show the complaint was filed on October 2 in the US District Court for the Northern District of Illinois. The case is listed as an antitrust action under 15 U.S.C. §1, which covers agreements that restrain trade.

At the heart of the complaint is McDonald’s use of technology to provide pricing recommendations to its franchisees.

The plaintiff alleges that McDonald’s has operated a centralized machine-learning pricing system that collects information from restaurants and uses it to recommend menu prices.

The lawsuit argues that the arrangement is problematic because McDonald’s franchisees can compete against one another in the same geographic markets.

If competing restaurants use the same centralized pricing system and receive recommendations generated from information collected across the network, the plaintiff argues, the system can reduce the incentive for individual restaurants to compete aggressively on price.

That is the legal theory the lawsuit will have to establish.

It is important, however, to distinguish the allegation from an established fact. The filing itself does not prove that McDonald’s or its franchisees illegally fixed prices.

McDonald’s says AI does not set menu prices

McDonald’s has rejected the central premise of the lawsuit.

In a fact sheet published on October 1, the company said its AI technology does not set the price of a Big Mac or any other menu item.

McDonald’s says its pricing recommendation tool provides restaurant-specific suggestions, while franchisees decide whether to use them and what prices to ultimately charge.

The company also says it does not use dynamic pricing.

That distinction is important because “AI pricing” can describe very different systems.

A system that automatically changes the price of a product based on demand is different from software that gives a restaurant owner a recommended price while leaving the final decision to that owner.

McDonald’s says its system belongs to the second category.

The company says its recommendations can consider factors such as local costs, demand, competition and economic conditions. It also says the tool does not determine what an individual customer is willing to pay.

McDonald’s therefore argues that the lawsuit is confusing an analytical recommendation with automated price setting.

Why the franchise model matters

The lawsuit’s legal argument depends heavily on the structure of McDonald’s business.

McDonald’s is not simply a company operating thousands of centrally managed restaurants.

Most of its US restaurants are operated by franchisees, which are independently owned businesses operating under the McDonald’s system.

AP reported that franchisees operate roughly 95% of McDonald’s approximately 14,000 US restaurants.

That creates an unusual competitive structure.

Two McDonald’s restaurants can potentially operate relatively close to each other while being owned by different franchisees. Those operators can therefore have an economic incentive to compete for the same customers.

The plaintiff argues that McDonald’s centralized pricing technology interferes with that competition.

McDonald’s counters that franchisees retain control over pricing.

The legal question will therefore go beyond whether AI is involved.

It will involve how the technology is used, what information is shared, how recommendations are generated, what franchise agreements require, and how much discretion individual operators actually retain.

The data-sharing question is central

One of the most significant aspects of the case is not necessarily the artificial intelligence itself.

It is the data available to the system.

According to the allegations, McDonald’s pricing technology can draw on information generated by restaurants across the system, including store-level sales information.

Normally, competitors have limited access to each other’s commercially sensitive information.

If competing businesses independently gather their own sales data, each business can use that information to make its own pricing decisions.

The lawsuit argues that a centralized system changes that dynamic.

Instead of each restaurant independently determining its pricing strategy from its own information, the system can incorporate information generated across a much larger network.

That is where algorithmic pricing becomes an antitrust issue.

The question is not simply whether an algorithm recommends $5.99 rather than $5.49.

The more consequential question is whether competitors are effectively using a common information system to coordinate their pricing behavior.

AI does not create an exemption from antitrust law

The broader legal issue is already familiar to US antitrust authorities.

In 2024, the US Department of Justice and Federal Trade Commission filed a joint statement of interest in an algorithmic hotel-pricing case.

The agencies argued that competitors cannot use an algorithm to accomplish conduct that would violate antitrust law if humans coordinated the same conduct.

They also said competitors can potentially violate antitrust rules even if they retain some discretion over the final price.

In other words, simply calling something a “recommendation” does not automatically make it legally safe.

The circumstances surrounding the recommendation matter.

The DOJ has continued to make this point. In 2026 remarks, Deputy Assistant Attorney General Daniel Glad said technology can change how competitors communicate and how prices are generated, but it does not change the underlying requirement that competitors make independent competitive decisions.

That principle could become particularly important in the McDonald’s case.

The difference between a recommendation and price fixing

Consider two hypothetical systems.

In the first, a McDonald’s franchisee asks software to analyse local wages, rent, ingredient costs, customer demand and nearby competitors. The software recommends a price. The franchisee independently decides whether to accept it.

In the second, competing franchisees provide commercially sensitive information to a centralized platform, receive coordinated recommendations based on that information and are pressured or required to follow those recommendations.

The two systems may look similar from the outside.

Legally, however, they could be very different.

The plaintiff’s challenge is essentially asking a court to determine whether McDonald’s system falls closer to the second model than the first.

McDonald’s insists it falls into the first.

That factual dispute will be central to the case.

McDonald’s prices have risen substantially

The lawsuit also comes against a backdrop of significant increases in US fast-food prices.

Restaurant Business reported that McDonald’s prices increased about 40% between 2019 and 2024, based on company statements.

The increase does not by itself establish illegal conduct.

Restaurants faced higher labour costs, food costs, real estate expenses, transportation costs and other inflationary pressures during that period.

McDonald’s has also been attempting to balance pricing with value offerings as lower-income consumers have become more cautious about restaurant spending.

The plaintiff nevertheless points to the broader price increase as evidence of the consumer impact of McDonald’s pricing practices.

That argument will have to overcome the question of what actually caused the price increases.

Higher prices alone do not establish price fixing.

Franchisees do not always follow McDonald’s recommendations

There is also evidence supporting McDonald’s claim that franchisees retain meaningful pricing discretion.

During an August investor call, CEO Chris Kempczinski said only around 60% of US restaurants were offering McDonald’s proposed $3-and-under menu.

That matters because it suggests the company does not simply press a button and impose identical prices across its network.

McDonald’s has also said franchisees are not required to accept its pricing recommendations.

The plaintiff, however, argues that formal discretion is not necessarily the same as genuine independence.

The complaint reportedly points to McDonald’s influence over franchisees and the company’s value standards as evidence that recommendations can carry significant practical pressure.

That creates another factual question for the litigation: How voluntary are the recommendations in practice?

Why algorithmic pricing is becoming an antitrust issue

The McDonald’s case is part of a much larger debate about algorithmic pricing.

Companies increasingly use software to analyse enormous quantities of data and recommend prices.

The technology can process variables that would be difficult for a human pricing team to examine continuously.

For a restaurant, that could include:

Pricing input	Potential use
Local demand	Estimate customer willingness to buy
Competitor prices	Understand local competitive conditions
Store-level sales	Identify high- and low-performing items
Local costs	Adjust for wages, rent and operating expenses
Product mix	Recommend prices for individual menu items
Historical transactions	Identify pricing and demand patterns

None of those inputs is inherently illegal.

The antitrust risk can arise from how the information is collected, shared and used among competitors.

That is why regulators have increasingly focused on algorithmic coordination.

The technology could create a new compliance problem

The case presents a difficult challenge for companies adopting AI.

Traditional antitrust compliance often focuses on obvious human behaviour: meetings between competitors, emails discussing prices or explicit agreements to avoid undercutting one another.

Algorithmic systems can create a more complicated evidence trail.

A company may not need a manager to tell a competitor, “Do not lower your price.”

Instead, competitors could potentially rely on the same pricing infrastructure, shared data or third-party recommendation system.

That can produce similar economic effects without conventional direct communication.

The DOJ and FTC have already acknowledged this concern in algorithmic-pricing litigation.

For businesses, the lesson is that AI adoption does not eliminate competition-law responsibilities.

It can actually create new compliance questions.

What McDonald’s could face if the case advances

The lawsuit seeks class-action status on behalf of potentially millions of McDonald’s customers.

The plaintiff is seeking damages and an injunction that would restrict the alleged anticompetitive practices.

But the case still has to clear several procedural and substantive hurdles.

First, the court will have to consider whether the proposed class can be certified.

Second, the plaintiff will need to substantiate the allegations concerning McDonald’s pricing system.

Third, the plaintiff will need to establish the elements necessary for an antitrust claim.

McDonald’s is expected to argue that franchisees independently set prices, that its recommendations are optional and that its use of pricing analytics is legitimate.

The company has described the allegations as speculative and uninformed.

Why this case matters beyond McDonald’s

The most important consequence of the lawsuit may extend well beyond fast food.

Retailers, hotels, airlines, landlords, online marketplaces and other businesses increasingly use algorithms to optimise prices.

If courts establish that certain forms of shared data and algorithmic recommendations amount to unlawful coordination, companies may need to redesign how those systems work.

That could include restricting the data fed into pricing engines, separating competitors’ information, adding compliance controls or ensuring that pricing decisions remain genuinely independent.

On the other hand, if McDonald’s successfully demonstrates that independently controlled recommendations are lawful, companies could gain greater clarity about how AI-assisted pricing can be deployed without violating antitrust rules.

Either outcome could influence the design of future AI pricing systems.

The bigger picture

The McDonald’s lawsuit is not really about whether artificial intelligence is allowed to recommend the price of a burger.

It is about whether an AI system can change the competitive relationship between businesses that are supposed to make independent pricing decisions.

McDonald’s says its technology simply gives franchisees better information. The plaintiff argues that centralising competitors’ data and feeding them algorithmically generated recommendations can effectively coordinate prices even without an explicit agreement between individual restaurants.

That distinction is becoming increasingly important as businesses replace human pricing processes with automated analytics.

The technology may be new, but the legal principle is not: companies cannot escape competition law simply by putting an algorithm between themselves and the pricing decision.

FAQs

Is McDonald’s actually being accused of using AI to set Big Mac prices?

The lawsuit alleges that McDonald’s AI-powered pricing system helps coordinate menu prices. McDonald’s denies that AI sets prices and says franchisees independently make the final pricing decisions.

Has a court found McDonald’s guilty of price fixing?

No. The case is a newly filed proposed class action. The allegations have not been proven in court.

What is the main antitrust issue?

The key issue is whether McDonald’s use of shared, nonpublic franchisee data and centralized pricing recommendations unlawfully coordinates pricing among businesses that otherwise compete with each other.

Could the lawsuit affect other companies using AI pricing?

Potentially. A court decision addressing when algorithmic recommendations, shared data or pricing platforms cross the line into unlawful coordination could influence how other industries design and use automated pricing systems.

Looking Ahead

The next stage of the McDonald’s case will be less about the label “AI” and more about the mechanics of the pricing system. The court will likely have to examine what data enters the platform, how recommendations are generated, whether franchisees are genuinely free to reject them and whether the system has the effect of reducing independent price competition.

For the broader AI industry, the case is an early warning that algorithmic efficiency and antitrust compliance must develop together. As pricing engines become more sophisticated, companies will need to demonstrate not only that their models work, but also that the way those models collect information and influence competing businesses remains legally defensible.