Are You Being Taken Advantage of by AI Surveillance Pricing?

Nearly a decade ago, Uber revealed that customers are more willing to pay surge prices when their phones are about to die. This insight fueled a belief that ride-hailing apps like Uber use algorithms to adjust prices based on individual behavior, referred to as "surveillance pricing." A similar myth persists about airlines using search history to increase flight prices, despite being unfounded.

While surveillance pricing is not yet widespread, experts indicate it is on the rise. Consultants are beginning to offer surveillance pricing strategies to various industries. In response, the Federal Trade Commission (FTC) has ordered eight companies involved in AI-driven surveillance pricing to provide data regarding its impact on privacy, competition, and consumer protection. According to FTC Chair Lina Khan, “The technology is there, the incentives are there, the data is certainly there to facilitate this targeting.”

Surveillance pricing—often called “dynamic pricing,” “personalized pricing,” or “price optimization”—offers consumers different prices for identical products based on several factors, including the device used for shopping, location, demographic data, credit history, and past browsing behavior.

Khan emphasized the risks posed by firms that exploit personal data: “Americans deserve to know whether businesses are using detailed consumer data to implement surveillance pricing. The FTC’s inquiry will illuminate this opaque pricing ecosystem.”

Some companies are already testing Uber-style surge pricing. For example, JetBlue recently introduced “peak” and “off-peak” pricing for checked baggage fees. Walmart plans to deploy digital price tags in 2,300 stores within the next few years, allowing prices to fluctuate based on factors like weather conditions and product expiration dates. Wendy's intends to introduce “dynamic pricing” in 2025, while Amazon previously operated an algorithm, Project Nessie, which measured optimal price increases before competitors reacted.

These dynamic pricing models differ from surveillance pricing, which relies specifically on individual consumer data to determine their willingness to pay. The FTC's orders were issued to Mastercard, Revionics, Bloomreach, Chase, Task, Pros, Accenture, and McKinsey & Co. under its 6(b) authority, which permits studies without a specific law enforcement aim. An FTC representative stated that these eight firms promote AI and machine learning technologies to create personalized purchasing experiences, but none have been accused of wrongdoing.

The FTC aims to clarify opaque practices that could significantly impact consumer purchasing behaviors, particularly focusing on potential harms faced by specific groups, such as women and rural consumers. The requested information includes:

- Types of surveillance pricing products and services offered

- Data sources used for these products or services

- Target audiences for surveillance pricing products and services

- Impact on consumers subject to surveillance pricing

An FTC official noted that understanding the scope of surveillance pricing practices is essential, as reports indicate that various sectors—including grocery, restaurant, travel, and hospitality—are either considering or implementing these pricing strategies. They concluded, “The technology is there, the incentives are there, the data is certainly available for targeted pricing, signaling that this practice is likely to expand.”