With Congress unable to find a solution to the regulatory briar patch of rules and regulations state and local governments fomented around AI last year, 2026 is shaping up to be the year that the AI patchwork arrives. Algorithmic pricing generally and price controls specifically are at the center of the debate.
These laws have been an absolute mess. Algorithmic pricing definitions are broad enough to accidentally rope in happy-hour discounts, with other bills targeting specific sectors ranging from real estate to grocery stores. A bill in Maine would have banned changing prices when demand fluctuates in grocery stores and restaurants, undermining simple supply and demand responses.
In California, a much broader bill was introduced last year to ban using consumer data to change prices, an idea Tennessee recently imported. California lawmakers ended up enacting different, overly broad regulations to restrict the use of a “common pricing algorithm” to set even basic prices. The definitions are so broad — and its applications so vague — that the California law might “accidentally regulate effectively all market transactions,” in one expert’s view.
Then there’s New York. Last year, its Legislature passed the Algorithmic Pricing Disclosure Act, which requires companies to spout a government-written line on their products in the name of transparency. Following pressure from government officials, Instacart, the online retail and delivery company, suspended its use of data in item price testing — but that wasn’t enough for New York’s regulatory enforcers.
In early January New York Attorney General Letitia James’ office sent a threatening letter to Instacart, warning the company that it may have violated New York’s algorithmic pricing law. In an op-ed, James revealed what everybody already knew: More legislation is coming. “This legislative session, we need to work together to address this issue in the strongest way possible,” she wrote.
Pricing decisions — whether or not they are AI-enabled — are best left to market forces and the ongoing interplay of different companies, new rivals and consumers. When firms develop new pricing schemes, rivals react when they sense mistakes and see an opening to offer better options. Just because an AI tool was used to help set prices, it should not automatically be cause for concern. New algorithmically tailored offerings can help expand personalized product offerings and price competition over time. This can help consumers find better deals tailored to their needs while offloading some hassles to an AI agent working for them to handle some transactions.
Some of those new AI-enabled options are already on the way. Google and a coalition of major retailers recently announced a new Universal Commerce Protocol and Agent Payments Protocol to make it easier for vendors and consumers to use AI agents to help make purchasing decisions more personalized and seamless. Critics decried Google’s move — one called it “an NSA for capitalism” — and called for regulation because it will allegedly spy on us and create price-fixing schemes. That is preposterous and paternalistic. Unlike government programs, using private AI tools is voluntary and can provide consumers with real benefits. Pre-emptive bans or pricing regulations based on worst-case hypothetical thinking should not serve as the basis of public policy.
To the extent algorithmic pricing policies require greater regulatory oversight, it should generally come at the federal level, where antitrust officials already possess a diverse toolkit to police marketplace developments. Federal antitrust officials can address any allegations of “algorithmic price fixing” with the same legal toolkit they have long used. Moreover, the federal government and state attorneys general have a variety of consumer protection laws and other rules that already address unfair and deceptive practices, whether an algorithm is used or not.
While AI pricing disclosure laws are less problematic than direct price controls, they can still create confusion if multiple jurisdictions are layering on different transparency mandates. And consumers sometimes experience “disclosure fatigue” from excessive warnings, as seen with European cookie pop-ups.
State lawmakers should reject onerous new regulatory pricing regulations that will significantly undermine nationwide competition and deprive consumers of important new AI-enabled services. With so many new laws already on the books, they would be wise to focus instead on expanding AI opportunities for their citizens by clearing the deck of existing barriers to innovation and investment in their states, not creating new roadblocks to competition and choice.
Adam Thierer is a senior fellow for technology and innovation at the R Street Institute. Logan Kolas is the director of technology policy at the American Consumer Institute.
Governing's opinion columns reflect the views of their authors and not necessarily those of Governing's editors or management.
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