California lawmakers are moving to restrict a rapidly emerging form of artificial-intelligence-driven commerce known as “surveillance pricing,” in which companies can use consumers’ personal information to determine individualized prices. Supporters of the proposed restrictions argue that advances in AI and data collection could allow businesses to quietly determine how much each customer is willing—or desperate enough—to pay.
The practice resembles personalized advertising but applies the same data-driven technology directly to prices. Companies or third-party providers can potentially analyze information such as a shopper’s income, ZIP Code, browsing history, previous purchases, family circumstances and online behavior to estimate that person’s willingness to pay.
Even remarkably small digital behaviors can become useful signals. A Federal Trade Commission investigation found that companies offering AI-powered pricing services could collect information such as IP addresses and language settings, as well as whether someone highlighted a product name or how far down a shopping page they scrolled.
That information could potentially reveal urgency.
For example, if an algorithm identifies someone as a new parent searching for a baby thermometer, it might prioritize more expensive products. Choosing expedited delivery could provide another signal that the shopper urgently needs the item and might tolerate a higher price.
California lawmakers want to establish limits before the technology becomes more widespread.
Assembly Bill 2564, introduced by Democratic Assemblymember Christopher Ward of San Diego, would prohibit retailers from using personal data to determine individual prices through AI or other technologies. The measure passed the California Senate on August 31 and returned to the Assembly for concurrence before potentially heading to Gov. Gavin Newsom.
California is not acting alone. New Jersey has already restricted surveillance pricing, while similar legislation has advanced elsewhere. Federal regulators are also increasing scrutiny. California Attorney General Rob Bonta launched an investigative sweep earlier this year examining whether personalized pricing practices could violate the California Consumer Privacy Act.
Concerns about individualized pricing are not entirely theoretical. California reached a $5-million settlement with Target in 2022 following allegations that prices displayed through its mobile application changed according to a customer’s location. Target did not admit wrongdoing.
Consumer advocates worry that increasingly sophisticated AI systems could take such practices much further. A person’s neighborhood, spending patterns or perceived financial circumstances might theoretically influence what an algorithm decides they should pay.
But economists caution that personalized pricing is more complicated than simply charging wealthier or more desperate consumers higher prices.
Research involving ZipRecruiter found that when the company experimented with personalized prices for employers, more than 60% of customers received prices below an estimated optimal uniform rate. Personalized pricing allowed the company to attract additional customers while simultaneously increasing revenue.
That finding has fueled opposition to outright bans. Critics argue that regulations written too broadly could unintentionally prevent businesses from offering personalized discounts. Colorado Gov. Jared Polis vetoed similar legislation in June partly because he believed it could restrict companies from lowering prices as well as raising them. California’s current proposal contains exceptions intended to preserve certain discounts.
Supporters counter that the deeper issue is transparency and fairness.
Consumers have traditionally expected that a product carries roughly the same price regardless of who is looking at it. Surveillance pricing could undermine that assumption by creating a marketplace where two people see different prices without understanding why.
The issue also reflects broader anxiety about digital privacy. Around three-quarters of Americans are concerned about how companies and governments use their personal information, while another survey cited by the Los Angeles Times found that 76% considered it unfair for retailers to determine prices using personal data.
The debate ultimately represents another challenge created by the combination of artificial intelligence, massive consumer datasets and increasingly sophisticated algorithms. AI can help businesses understand demand and potentially offer targeted discounts, but the same technology can identify precisely how much an individual consumer might tolerate paying.
California’s proposed ban therefore asks a fundamental question about the future of online commerce: Should companies be allowed to use what they know about you not simply to decide what advertisements you see, but to determine the price you personally pay?
As AI becomes more deeply integrated into retail, the answer could reshape how Americans understand something once considered straightforward—the price tag.
