AI Has Entered an Era of ‘Collusion’ on Its Own

McDonald’s has been sued. The reason? “AI was aligning prices between stores.”

In the United States, 95% of McDonald’s approximately 13,000 locations are franchises—meaning they are independently operated. Originally, each store sets its own prices. This should have created a healthy system for consumers, driven by competition.

However, the lawsuit claims otherwise. The AI pricing tool introduced by McDonald’s allegedly siphoned off confidential sales data and pricing information from each store, effectively facilitating price adjustments between them. If humans agree in a closed room to set a certain price, that constitutes a clear price cartel. But when AI shares data behind the scenes, resulting in aligned prices—can this be considered collusion or optimization?

What has happened as a result? The average price of a Big Mac has risen by about 40% over the past five years, reaching $5.58. Consumers now face a situation where “the price is the same at any store.” Despite being independent, price competition has vanished.

This is not just a distant issue. What will happen to the pricing power of small businesses when AI-driven pricing mechanisms become widespread?

The Core Issue: ‘Invisible Synchronization by Algorithms’

What is noteworthy about this lawsuit is that no one has explicitly instructed to “raise prices.”

The AI tool aggregates data from each store and suggests an “optimal price.” Each store follows that suggestion. As a result, prices across the 13,000 locations move in the same direction. Without human decision-making, algorithms effectively control the pricing of the entire market.

This phenomenon is known as “algorithmic pricing,” which has already raised concerns in Amazon’s marketplace and the hotel industry. In 2024, the U.S. Department of Justice sued RealPage, a real estate tech company, claiming that its AI tool shared rent data among multiple landlords, resulting in unjustified rent increases—almost identical to the McDonald’s lawsuit.

In other words, AI can potentially kill competition in the name of ‘optimization.’

For small business owners, this becomes the first critical juncture. When they adopt AI pricing tools provided by large platforms simply because they are “convenient,” are they relinquishing their pricing power? Do they understand what those tools are doing behind the scenes?

Another Interesting Use of AI: Airbnb’s ‘SIFT’

The discussion about AI manipulating prices is not all bleak. There is another structurally interesting development.

Airbnb’s developed model, “SIFT (Search Intent-to-Filter Transformer),” predicts guest needs based on their search behavior and automatically suggests optimal filters.

Look at the numbers:

• Booking conversion rate: +51.9%
• Filter usage rate: +20%
• Guest search abandonment rate: significant decrease

What this means is that “it has become easier to find what one is looking for.” Traditionally, Airbnb has over 8 million listings, but about 60% of guests searched without using filters. As a result, irrelevant listings were displayed in abundance, leading to abandonment. SIFT solved that problem.

Here is a structural aspect that small businesses should pay attention to.

The essence of SIFT is not an AI that “manipulates prices,” but rather an AI that “enhances the matching accuracy between customers and products.” In other words, it creates a system where products can sell without needing to lower prices.

For owners of small accommodations, this is significant. Competing on price with large hotel chains is a losing battle. However, if their property is displayed precisely to a family searching for “a quiet place for kids,” they will be chosen based on experience rather than price. As matching accuracy improves, they can escape the price-cutting competition.

The Real Issues for Small Businesses

When comparing the McDonald’s lawsuit and Airbnb’s SIFT, it becomes clear that the role of AI in pricing is diametrically opposed.

What small businesses should consider is which side of AI utilization they are on.

If they merely follow the “recommended prices” provided by large platforms, that is the McDonald’s type. They are handing over their pricing power to algorithms. Many small businesses selling on Rakuten or Amazon may feel that “if I don’t align with the AI-suggested prices, my search ranking will drop.”

On the other hand, using their customer data to increase matching accuracy with “this proposal will resonate with this person” is the SIFT type. They compete based on the quality of proposals rather than price.

What Specifically Should Be Done?

“So, what should we ultimately do?”—We must delve into this.

1. Don’t Take Platform ‘Recommended Prices’ at Face Value

Rakuten, Amazon, Uber Eats. Every platform has AI-driven pricing suggestion features. While it’s easy to follow them, if all sellers adhere to the same algorithm, prices will become uniform. Setting prices based on one’s cost structure, regional characteristics, and customer demographics is a job for humans.

2. Invest in ‘AI that Enhances Matching Accuracy’

Instead of lowering prices, increase the “probability of reaching those who want it.” This is achievable even for small businesses.

Here’s a specific example. A local inn created a system that automatically sends personalized plan proposals via LINE based on past guest data (family composition, purpose of stay, season). The development cost was about 300,000 yen. As a result, the repeat rate increased from 23% to 41%. This led to an increase in monthly sales of about 800,000 yen. They can create such a system without relying on a 3 million yen consultant.

3. Show Customers the ‘Basis’ for Pricing

In an era where AI determines prices, companies that can explain “why this price” will gain trust. Whether it’s using local ingredients, having artisans finish by hand, or producing in small quantities—articulating and communicating that basis is a weapon unique to small businesses that larger corporations cannot replicate.

4. Be Aware of Legal Risks

The McDonald’s lawsuit could happen in Japan as well. Antitrust laws scrutinize actions that limit competition, even without “communication of intent.” Synchronization of prices through AI tools may become a regulatory target in the future. If using the same AI pricing tool as competitors, that risk should be kept in mind.

Pricing Power Is Not Something to ‘Hand Over’ but to ‘Hold On To’

AI is a tool. Like a knife, depending on how it is used, it can become a dish or a weapon.

What the McDonald’s lawsuit highlights is the reality that “if you hand over pricing to AI just because it’s convenient, you may find that you’ve lost control of your business.” This is not just a story for large corporations. Rather, small businesses that are highly dependent on platforms are more likely to fall into the same trap.

Conversely, what Airbnb’s SIFT illustrates is the potential that “if you enhance the quality of customer touchpoints with AI, you can escape price competition.”

If small businesses are going to use AI, they should use it not to have prices set for them but to ensure that customers understand and accept their prices.

Whether they understand this difference will significantly change the landscape three years from now.