WASHINGTON, D.C. – November 21, 2025 – Several U.S. states are moving aggressively to curb data-driven pricing practices that critics say unfairly raise costs for consumers. The efforts, building on the work of former Federal Trade Commission (FTC) Chair Lina Khan, aim to limit the use of algorithms and artificial intelligence that analyze personal and competitor data to adjust prices in real time.

While the White House considers executive action to preempt state laws on artificial intelligence, states are continuing to push legislation to protect shoppers, renters, and workers from practices deemed unfair or anti-competitive.

“Even as the federal government backslides, states are stepping up,” said Lina Khan, now co-chair of New York City Mayor-elect Zohran Mamdani’s transition team.

State-Led Action Against Algorithmic Collusion

In October, New York passed legislation preventing landlords from colluding on rental prices using algorithms. California implemented a broader ban on algorithmic collusion, restricting companies from using AI and third-party software to set prices based on competitor or consumer data.

Currently, 19 states are reviewing bills to regulate how businesses use software that leverages competitor and customer data to set rental housing prices, according to the American Economic Liberties Project (AELP), a nonpartisan antimonopoly think tank.

“You can’t talk about affordability without understanding how prices are set,” said Lee Hepner, senior legal counsel at AELP. “And how prices are set is evolving in real time with the advent of new tools.”

The legislation reflects a bipartisan concern over consumer protection, with Republican lawmakers such as Utah’s Tyler Clancy proposing measures to give consumers more control over the data collected on them and how it is used to determine pricing.

How Data-Driven Pricing Works

Retailers, travel companies, and online platforms increasingly rely on granular consumer data, including past purchases, browsing behavior, location, and media consumption. This data is used to target promotions and discounts—but critics warn it can also be used to charge different prices based on perceived willingness to pay, a practice known as price discrimination.

For example, travel booking platforms may display higher prices for the same hotel in San Francisco compared to Phoenix or Kansas City. In 2025, Delta Air Lines faced congressional scrutiny over plans to use AI in ticket pricing, though the airline has said AI would not be used to set individualized fares.

“Ultimately, what we are concerned about is different people paying different prices based on who a company thinks they are,” said Grace Gedye, policy analyst at Consumer Reports, a nonprofit consumer advocacy group.

Regulatory Context and Implications

The state-led initiatives are part of a broader effort to regulate Big Tech and AI-driven commerce. Lawmakers are seeking to increase transparency, prevent anti-competitive practices, and protect consumers from exploitative pricing algorithms. As AI tools and machine learning systems become central to commerce, these regulations could reshape how pricing, advertising, and discounts are managed across industries.

The outcome of these laws could influence both retail and housing markets, ensuring fairness and preventing companies from exploiting consumer data to maximize profits.