State regulation of algorithmic pricing is accelerating. California, Connecticut, Maryland, and New Jersey have enacted new restrictions, while New York lawmakers have passed a bill that would go further than the state’s existing disclosure regime if it becomes law.
For businesses, the key distinction is the data driving the price. California and Connecticut restrict certain tools that use competitor data to address antitrust concerns, while Connecticut, Maryland, New York, and New Jersey address consumer-specific pricing based on personal data to address unfairness and deception concerns. The rules also vary by industry, product, disclosure duty, exception, remedy, and effective date.
These developments arrive against the backdrop of litigation and enforcement involving algorithmic rent-setting tools and growing scrutiny of personalized pricing.
Several provisions are already in effect; others phase in through 2027. The practical question is no longer simply whether software changes prices, but what data it uses, for which products, in which states, and for whom.
This GT Alert summarizes the state-law developments and highlights practical compliance considerations for businesses that develop, sell, or use algorithmic pricing tools.
California: Cartwright Act Targets ‘Common Pricing Algorithms’
California’s Assembly Bill (AB) 325, signed into law by Gov. Gavin Newsom on Oct. 6, 2025, amended the Cartwright Act to make it unlawful to use or distribute a “common pricing algorithm” as part of a contract, combination in the form of a trust, or conspiracy to restrain trade or commerce.
A “common pricing algorithm” is a methodology, including a computer, software, or other 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 law separately prohibits using or distributing a common pricing algorithm when a person “coerces” another person to set or adopt a recommended price or commercial term. Because the statute does not define “coerces,” courts will have to determine the provision’s reach.
AB 325 also changes the pleading requirements for certain Cartwright Act conspiracy claims, attempting to make it easier for plaintiffs to survive the pleading stage.
AB 325 took effect Jan. 1, 2026.
Connecticut: Surveillance-Pricing Rules and an Algorithmic Rent-Setting Ban
Connecticut has enacted two distinct sets of algorithmic-pricing restrictions: consumer rules governing “surveillance pricing” and an antitrust rule barring certain residential rent-setting software. The consumer rules were revised several times in 2026; the operative provisions now appear in Public Act 26-130.[1]
Consumer Surveillance-Pricing Rules Effective July 1, 2027
Beginning July 1, 2027, Connecticut will generally prohibit retail sellers and third-party delivery services from engaging in surveillance pricing. Other persons doing business in Connecticut that use surveillance pricing in online transactions generally must provide a disclosure unless the price is discounted or is a bona fide market price.
The statute defines “surveillance pricing” as establishing a customized price for a consumer or group of consumers based, at least in part, on personal data collected through technology and obtained directly or indirectly.
When the disclosure rule applies, the relevant online advertisement, promotion, label, display, offer, or other price communication must state (or use substantially similar language):
“THIS PRICE WAS INCREASED USING YOUR PERSONAL DATA”
The retail prohibition includes detailed exclusions for specified discounts, loyalty and rewards programs, customer-acquisition or retention offers, justifiable cost or market differences, pricing-error corrections, and similar practices.
Businesses may wish to document the basis for any claimed exclusion because the statute distinguishes permitted discounts and cost-based differences from consumer-specific pricing based on personal data.
Residential Rent-Setting Ban Already in Effect
Separately, Connecticut’s November 2025 special-session law, House Bill 8002 (P.A. 25-1), prohibits any person from using a “revenue management device” to set rental rates or occupancy levels for residential dwelling units. That provision took effect Jan. 1, 2026.
A “revenue management device” is software that uses one or more programmed or automated processes to calculate nonpublic competitor data about local or statewide rents or occupancy levels for the purpose of advising a landlord whether to leave a unit vacant or how much rent the landlord may obtain.
The definition excludes, among other things, reports that publish existing rental data only in aggregated form without recommending future rents or occupancy levels, and products used to establish rent or income limits under government affordable-housing programs.
Violations are subject to investigation and enforcement under the Connecticut Antitrust Act.
Maryland: Restricting Personalized Pricing in Food Retail and Delivery
Maryland’s Protection from Predatory Pricing Act (House Bill 895, Ch. 154), signed by Gov. Wes Moore on April 28, 2026, and effective Oct. 1, 2026, restricts certain uses of dynamic pricing and personal data by large food retailers and third-party food delivery service providers. Unlike earlier versions of the bill, the enacted law does not impose a broader algorithmic-pricing disclosure requirement on merchants generally.
The Act defines “dynamic pricing” as the discriminatory practice of offering or setting a personalized price for a good or service that is specific to a consumer based on that consumer’s personal data, regardless of whether the seller collected or purchased the data.
The restrictions apply to:
- “Food retailers,” defined as merchants operating establishments of at least 15,000 square feet that sell food exempt from Maryland sales and use tax; and
- “Third-party delivery service providers,” defined as merchants that facilitate, as a consumer service, the delivery of such tax-exempt food. The definition excludes food retailers themselves.
Subject to specified exceptions, a covered food retailer or delivery provider may not (1) use dynamic pricing to set a higher price for tax-exempt food for a specific consumer, or (2) use personal data to set a higher price for such food for a single consumer. Notably, the enacted legislation does not retain language from an earlier version that would have extended the second prohibition to pricing for a “group of consumers.”
The Act separately restricts covered businesses’ use of protected-class data, defined as information that identifies, directly or by implication, a characteristic protected from discrimination under Maryland or federal law. A covered business may not use that data to offer, advertise, or sell a consumer good or service to the affected consumer if doing so has the effect of withholding or denying an accommodation, advantage, or privilege accorded to others.
Among other exceptions, the food-sector pricing restrictions do not apply to certain promotional pricing and customer-retention offers; loyalty, membership, and rewards programs; subscription pricing; price differences based on objective costs or certain geographic, supply, or demand factors; and pricing-error corrections.
The Consumer Protection Division of the Maryland Attorney General’s Office may enforce violations, which are subject to civil penalties under the Maryland Consumer Protection Act. The division must provide notice and a 45-day opportunity to cure before initiating an enforcement action, and a timely cure bars enforcement for that violation. The Predatory Pricing Act expressly states that a violation of the Act does not create a private right of action—under that law or any other Maryland law.
New York: Disclosure Requirements Today, Potential Ban Tomorrow
New York law already requires disclosure of certain personalized algorithmic pricing. Under N.Y. Gen. Bus. Law § 349-a, an entity that sets the price of a specific good or service using “personalized algorithmic pricing” and advertises, promotes, labels, or publishes that personalized price to a New York consumer using personal data specific to that consumer must clearly and conspicuously state:
“THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA”
“Personalized algorithmic pricing” means dynamic pricing set by an algorithm that uses personal data. The disclosure requirement took effect Nov. 10, 2025.
Pending One Fair Price Act
The New York Legislature passed the One Fair Price Act (Senate Bill 8623B /Assembly Bill 9349B) on June 4, 2026. As of Sept. 2, 2026, however, the bill had not been delivered to or signed by the governor and therefore was not yet law.[2] If enacted, it would take effect 180 days after becoming law.
The bill would replace the current disclosure requirement with a broader prohibition on “surveillance pricing,” defined generally as pricing set completely or partly by an algorithm that uses personal data to offer different prices to different customers for the same goods or services. Qualifying bona fide custom discounts are excluded from that definition.[3]
If enacted, the bill generally would prohibit businesses and service providers acting on behalf of businesses from using surveillance pricing to set or adjust a reference price or consumer price; advertising, promoting, labeling, or publishing an offer or other pricing communication using surveillance pricing; and collecting, using, selling, retaining, sharing for valuable consideration, or disclosing personal data to facilitate surveillance pricing.
The bill preserves qualifying bona fide custom discounts, including specified loyalty, membership, rewards, and other individualized discounts, subject to detailed eligibility, disclosure, uniformity, and data-use requirements. It also contains exceptions for certain insurance activities, creditworthiness-based pricing using consumer-report data, and pricing required or expressly authorized by federal or state law.
If enacted, the One Fair Price Act would authorize the New York Attorney General, on five days’ notice, to seek an order enjoining or restraining alleged violations. Where a violation is established, the court would order restitution and damages to aggrieved parties, where appropriate, and may impose civil penalties of up to $5,000 for a first violation and $20,000 for each subsequent violation.
Notably, the New York City Council is also considering legislation (Int. No. 891-2026) regarding surveillance pricing, which has received significant pushback from industry stakeholders. If enacted, the bill would impose a broad prohibition on the use of surveillance pricing by persons that sell, lease, or rent goods or services — whether online or in person.
New Jersey: Grocery Surveillance Pricing, Electronic Shelf Labels, and Rent-Setting Algorithms
New Jersey Gov. Mikie Sherrill signed the Fair Price Protection Act (Senate Bill 3612/Assembly Bill 4085) on July 23, 2026. The Act makes it an unlawful practice under the New Jersey Consumer Fraud Act for a person to use surveillance pricing — or another pricing strategy that determines or varies the sale price of “groceries and other foodstuffs” — based, in whole or in part, on personal data.
The main surveillance-pricing prohibition takes effect Aug. 1, 2027. A separate one-year moratorium on the new use of electronic shelf labels begins Feb. 1, 2027.
“Surveillance pricing” includes pricing determined, adjusted, optimized, or recommended by an algorithm or automated system using personal data when that pricing results in price variation among individual consumers or groups of consumers. It also reaches pricing based on data collected through electronic surveillance technologies.
- The covered “groceries and other foodstuffs” category is broad: it includes food and beverages as well as paper products, household cleaning items, health and beauty products, frozen foods, and pet food and supplies. It excludes food or beverages prepared for immediate consumption by an establishment primarily engaged in preparing and selling food or beverages.
- Permitted price differences include certain reasonable cost-based differences, subject to a once-per-24-hour price-change limit; bona fide discounts with publicly and conspicuously disclosed eligibility criteria that are uniformly offered based on those criteria; and qualifying loyalty-program discounts.
- When personal data is used to provide a permitted price difference, the Act prohibits using that data for another purpose without the consumer’s consent.
Beginning Feb. 1, 2027, the Act imposes a one-year moratorium on the new use of electronic shelf labels. New labels may nevertheless be purchased, installed, or deployed solely to repair or replace labels that were already operating at the same place of business before the moratorium took effect. The New Jersey Innovation Authority, in consultation with the Division of Consumer Affairs, must study the effects of electronic shelf labels and their impact on surveillance pricing.
After the moratorium expires, new electronic shelf labels may be used subject to the Consumer Fraud Act, other applicable law and regulations, and any subsequent legislative action.
For violations of the Fair Price Protection Act, the New Jersey Attorney General may seek injunctive relief, enforce compliance, obtain actual monetary damages incurred from each negligent-or-greater violation, and seek other restitution, penalties, or relief. Because the pricing prohibition constitutes an unlawful practice under the Consumer Fraud Act, additional remedies available under that statute may also apply, including treble damages.
Separate Antitrust Rule for Algorithmic Rent-Setting
Three days before signing the Fair Price Protection Act, Gov. Sherrill signed the Forbidding the Algorithmic Inflation of Rent (FAIR) Act. The law supplements the New Jersey Antitrust Act and prohibits specified forms of parallel pricing coordination and coordinating functions involving residential rental pricing, including conduct involving algorithmic devices and competitively sensitive information. It takes effect July 1, 2027.
Key Takeaways for Businesses
State regulation of algorithmic pricing is no longer following a single model. Exposure turns on the data that a tool uses, the product or industry involved, the consumer’s location, and whether the practice is a price increase, discount, recommendation, or coordinated pricing function.
Businesses that develop, distribute, or use algorithmic pricing tools should consider the following:
- Inventory tools and data inputs. Identify every system that recommends, sets, or changes prices, and document whether it uses competitor data, consumer personal data, or both.
- Map use cases to state rules. For each tool, map the covered products, jurisdictions, disclosure duties, prohibitions, exceptions, enforcement mechanisms, and effective dates — especially discount and loyalty-program conditions.
- Vet vendors and build a change calendar. Require vendors to explain data sources and model inputs, address legal compliance contractually, and track 2027 implementation dates and later rulemaking.
Businesses should also monitor the legislative pipeline. Illinois, Pennsylvania, and other states continue to consider algorithmic-pricing measures, and the details remain fluid.
At the federal level, the FTC on Aug. 19, 2026, proposed an enforcement policy statement on personalized pricing, as we noted in an earlier GT Alert. The Commission emphasized that it does not have authority to ban personalized pricing in all circumstances, but said businesses that fail to tell consumers how personal data is used to set a price may violate the FTC Act and other laws it enforces.
From a compliance perspective, companies may wish to identify pricing systems now, document why each use case falls inside or outside a prohibition, disclosure duty, or exception, and be prepared to update that analysis as state rules continue to evolve.
[1] Connecticut Gov. Ned Lamont signed Senate Bill 4 (P.A. 26-64) on May 27, 2026, House Bill 5222 (P.A. 26-100) on June 2, 2026, and House Bill 5563 (P.A. 26-130) on June 4, 2026. P.A. 26-130 contains the operative surveillance-pricing provisions, which primarily take effect on July 1, 2027.
[2] In New York, legislation may be signed by the governor on the condition that changes be made in a future bill passed by the legislature, which is known as a “chapter amendment.” In that instance, the underlying bill would be enacted, but would be amended relatively quickly by the legislature in the new session beginning in January 2027. This might materially alter the provisions of the current legislation.
[3] The exception for bone fide custom discounts might require, for most businesses, that they can offer only strictly uniform benefits to a member of a reward or loyalty program, and in certain instances, can use past history within the provider’s system. The exception still restricts the use of most consumer data to personalize offers other than certain data based on age (e.g., senior citizen), military service, status as a teacher, or employees.