States Are Taking the Lead on Regulating AI Pricing: Consumer Protection and Antitrust Concerns Drive Spate of New Legislation

Key Takeaways:

• States are actively regulating AI-driven pricing, with personalized pricing and pricing algorithms that use competitor data being two primary areas of focus.
• Approaches vary widely, with some states requiring disclosures for personalized pricing, and others imposing outright bans; and some states targeting only pricing algorithms that use non-public competitor data and others not making the distinction between public and non-public information.
• The legal landscape is rapidly evolving, with ongoing legislative proposals and increasing litigation making it essential for businesses to closely monitor this space. 

Introduction

Recent technological developments have enabled unprecedented usage of data- and AI-powered tools to set prices. While AI pricing technology has the potential to generate significant efficiencies by facilitating pricing that more accurately reflects supply-and-demand conditions, it has also spurred concern from legislators and enforcers about potential antitrust and consumer-protection implications. Two innovations in pricing have attracted particular scrutiny: algorithms that use consumers’ personal data to set personalized prices and algorithms that recommend prices based in part on competitors’ data.

As with AI regulation more broadly (see our prior alert), states have taken a leading role in regulating AI pricing. Several states have recently passed laws that fall into one of two categories: (1) consumer-protection-focused legislation restricting or requiring disclosure of the use of consumers’ personal data to set personalized prices; and (2) competition-focused laws targeting algorithms that use competitor data to recommend prices. And with many more states considering additional proposals, businesses considering or using AI pricing tools should monitor developments in this area closely.

Personalized Pricing Laws

New York, Maryland, and Connecticut have enacted legislation governing the use of personalized pricing. They either require businesses to disclose when a price was set using an algorithm (New York), ban the use of personalized pricing for certain products (Maryland), or adopt a combination of the two (Connecticut).

• New York – Algorithmic Pricing Disclosure Act, N.Y. Gen. Bus. Law § 349-a – Disclosure of personalized pricing.¹ New York’s Algorithmic Pricing Disclosure Act requires businesses to disclose to consumers when the business uses an algorithm that relies on personal data to set dynamic prices—i.e., prices that “fluctuate[] dependent on conditions.” In case of a violation, the New York Attorney General may send a cease-and-desist letter, and if the alleged violation continues, bring an action for injunctive relief and civil penalties of up to $1,000 per violation.² There is no private right of action.
• Maryland – Protection from Predatory Pricing Act, Md. Code, Com. Law §§ 13-321–322, 14-4701 – Ban on certain personalized pricing for food sales.³ Maryland enacted the first personalized pricing restriction specific to food sales. The Protection from Predatory Pricing Act applies to food retailers and third-party food delivery services and prohibits the use of consumer personal data to set higher food prices for a specific consumer. It also prohibits food retailers and third-party delivery services from using data that identifies a consumer as being a member of a protected class in a way that disadvantages the consumer. The law takes effect October 1, 2026. There is no private right of action, and the Maryland Attorney General must provide a 45-day cure period before bringing an enforcement action. Notably, the law has a number of carve-outs: for instance, it does not apply to promotional pricing, loyalty programs, subscription pricing, geography or cost-based price differences, and consumer-consented data exchanges.
• Connecticut – Public Act No. 26-64 – Disclosure of price-setting devices that result in price increases, and ban on use of personalized pricing by retailers and delivery services.⁴ Connecticut has taken a hybrid approach, combining a disclosure requirement with an outright ban on using personalized pricing for retailers and third-party delivery services in certain circumstances. Specifically, the law, which goes into effect October 1, 2026, prohibits retailers and third-party food delivery services from engaging in personalized (“surveillance”) pricing, subject to exceptions for retention discounts, cost-based differences, temporal supply-and-demand differences, and generally available discounted pricing programs. It also requires a specified disclosure when a seller uses a “price setting device” (defined as an “automated or programmed process that uses a consumer’s personal data to establish a price for a consumer good or consumer service”) to publish prices online, unless the seller only used the “price setting device” to offer discounts. The Attorney General may prosecute violations as deceptive trade practices.
  
  

Algorithmic Pricing Laws

New York, New Jersey, Connecticut, and California also have enacted legislation targeting algorithms that use competitors’ data to inform price or rent recommendations.

• New York – N.Y. Gen. Bus. Law § 340-b – Prohibition on using algorithmic rate-setting by landlords and property managers.⁵ General Business Law § 340-b prohibits certain algorithmic rate-setting practices by residential landlords and property managers—banning the operation or licensing of software, data-analytics services, or algorithmic devices that perform a “coordinating function” for residential landlords. “Coordinating function” is defined as (1) collecting rent or occupancy information from multiple owners or managers; (2) processing that information computationally; and (3) recommending rent, occupancy, renewal, or other lease terms.
• New Jersey – Forbidding the Algorithmic Inflation of Rent (“FAIR”) Act (supplementing N.J.S.A. 56:9-1 et seq.) – Prohibition on using rent-setting algorithms to coordinate rental prices.⁶ Similar to the New York legislation, the FAIR Act prohibits rental property owners or their agents from using software (or any service or entity) that performs a “coordinating function” by collecting nonpublic rental information from multiple landlords, processing it computationally, and recommending rental prices, lease terms, or occupancy levels. The law also makes it unlawful for two or more rental property owners to engage in “consciously parallel pricing coordination”—which is notable because conscious parallelism is generally not considered unlawful under federal antitrust laws. The statute’s definition of “consciously parallel pricing coordination” as involving a “tacit or express agreement” on price may narrow the application of this provision.
• Connecticut – Public Act No. 25-1, § 32 – Prohibition on using “revenue management device” to set rental rates or occupancy levels.⁷ Connecticut has enacted a rental-housing algorithmic pricing statute, prohibiting the use of certain revenue management software to set rental rates or occupancy levels for residential units. Specifically, the statute targets software that performs calculations using nonpublic competitor data concerning rents or occupancy levels for purposes of advising landlords on occupancy levels or rent. Connecticut’s law is narrower than New York’s because it expressly limits the prohibition to tools using nonpublic competitor data, without imposing any restriction on the use of public data.
• California – Cal. Bus. & Prof. Code §§ 16729, 16756.1 – Prohibition on using “common pricing algorithm” to restrain trade.⁸ California’s new pricing-algorithm law amends the Cartwright Act—California’s primary antitrust statute—by prohibiting the use or distribution of a “common pricing algorithm” as part of a contract, combination, trust, or conspiracy to restrain trade. The law also prohibits using or distributing a common pricing algorithm if the person coerces another person to adopt a recommended price or commercial term. A “common pricing algorithm” is defined as technology used by two or more persons that uses competitor data to recommend, align, stabilize, set, or otherwise influence a price or commercial term. The provision is not limited to rent-setting and encompasses algorithms using public as well as confidential competitor data.

Proposed Legislation

Many states also are considering enacting restrictions on personalized pricing, with over a dozen states proposing or introducing bills in this area.⁹ Some prominent examples include:

• New York’s legislature has passed an amendment to its disclosure law that would outright prohibit businesses from using algorithms to set prices based on consumers’ personal data and require disclosure when dynamic pricing systems adjust prices more than once in a 24-hour period. The bill is on the Governor’s desk for signature.¹⁰
• California’s legislature is considering a bill that would prohibit retailers from engaging in “surveillance pricing,” which it defines as setting a customized price based on personally identifiable information collected through electronic surveillance technology.¹¹
• New Jersey’s Senate has proposed a law banning “personalized algorithmic pricing, surveillance pricing, or any pricing strategy that determines or varies the sale price of groceries and other foodstuffs based, in whole or in part, on personal data.”¹²
• Pennsylvania’s legislature is considering two bills on this issue, one of which would require businesses to disclose when prices are set using personalized data and another that would prohibit dynamic pricing on essential goods.¹³
• Illinois’s legislature also is considering two bills that would regulate personalized pricing algorithms. One would require disclosure and opt-out rights for personalized online pricing and prohibit the use of certain types of personal information for algorithmic pricing.¹⁴ The other would prohibit using “surveillance” data as part of an automated decision system to inform individualized prices or wages.¹⁵

Notably, however, several attempts to restrict AI pricing tools have been unsuccessful. In particular, Colorado Governor Jared Polis has vetoed two proposed AI pricing laws. First, in 2025, he vetoed a bill that would have banned landlords from using rent-setting algorithms, noting that any collusion among landlords would violate already existing antitrust laws.¹⁶ In his veto letter, Governor Polis expressed “grave concerns about prohibiting companies using algorithmic pricing software derived from multiple data sources from doing business in Colorado,” highlighting the “unintended consequences of creating a hostile environment for providers of rental housing” that could result in “further diminished supply of rental housing based on inadequate data.”¹⁷ Then, this June, Governor Polis vetoed a bill that would have prohibited the use of AI tools to set individualized prices and wages—he criticized the bill as too broad, potentially capturing “any technology that incidentally influences a price or wage amount,” which could “punish differentially lower prices, not just higher prices.”¹⁸

Conclusion

States have started regulating AI pricing using a variety of models. On the consumer protection front, some states focus on disclosure for algorithmic personalized pricing while some have outright bans. States also differ in the industries they target and the exceptions and carve-outs they allow. On the antitrust front, some states focus specifically on algorithmic rent-setting and others target pricing algorithms more broadly, and some states zero in on algorithms using non-public competitor data while others do not distinguish between public and non-public data. With a number of additional proposals under consideration, the diversity in state approaches to AI pricing is only likely to grow. And some states have gone beyond legislating, filing antitrust lawsuits alleging algorithmic price-fixing in residential housing¹⁹ and health insurance²⁰ sectors. Algorithmic pricing is a rapidly developing area of law, and the consequences of noncompliance are potentially severe. For more information, please reach out to one of the attorneys listed on the alert or your regular O’Melveny contact.

Table of Existing AI Pricing Laws