States Accelerate Crackdown on Algorithmic Pricing, Raising Compliance Stakes

State efforts to regulate algorithmic pricing are accelerating, replacing a handful of isolated restrictions with an increasingly complex patchwork of antitrust, consumer protection and data privacy rules.

California, Connecticut, Maryland and New Jersey have enacted restrictions targeting different pricing practices, while New York lawmakers are considering replacing the state’s disclosure requirement with a broader prohibition. Illinois, Pennsylvania and other states also are weighing measures, according to a Greenberg Traurig analysis.

The expanding activity means businesses can no longer assess pricing software simply by asking whether it uses an algorithm. Their exposure may depend on the data processed by the system, the products being priced, the customer’s location and whether the algorithm raises a price, offers a discount or recommends terms to multiple competitors.

California’s AB 325, effective Jan. 1, amended the Cartwright Act to prohibit using or distributing a “common pricing algorithm” as part of an agreement or conspiracy restraining trade. The definition covers technology used by two or more persons that processes competitor data to recommend, align, stabilize or otherwise influence prices or commercial terms.

The law also prohibits using such an algorithm to coerce another party into adopting a recommended price. Because “coerces” is undefined, courts will likely determine the provision’s reach, per Greenberg. Changes to pleading requirements could also make it easier for plaintiffs to advance certain Cartwright Act conspiracy claims.

Connecticut has adopted both consumer surveillance-pricing restrictions and an algorithmic rent-setting ban. Beginning July 1, 2027, retailers and third-party delivery services generally will be prohibited from using personal data collected through technology to establish customized prices. Other businesses conducting online transactions may be required to display the warning: “THIS PRICE WAS INCREASED USING YOUR PERSONAL DATA.”

Connecticut’s separate ban on using certain revenue-management software to set residential rents or occupancy levels took effect Jan. 1. It targets systems that analyze nonpublic competitor information to advise landlords about rents or whether to leave units vacant.

Maryland is taking a narrower, sector-specific approach. Its Protection from Predatory Pricing Act, effective Oct. 1, restricts large food retailers and third-party food-delivery providers from using personal data to charge an individual consumer more for tax-exempt food.

The law includes exceptions for loyalty programs, subscriptions, promotions, objective cost differences and some geographic or market conditions. Maryland’s attorney general must provide notice and 45 days to cure a violation before bringing an enforcement action.

New York currently requires businesses using personal data to set personalized prices to disclose: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” But the state legislature passed the One Fair Price Act in June, which would replace disclosure with a broader ban on surveillance pricing.

If enacted, the law would generally prohibit businesses from using surveillance pricing, publishing offers based on it or processing personal data to facilitate it. The attorney general could seek injunctions, restitution and penalties of up to $5,000 for a first violation and $20,000 for subsequent violations. New York City lawmakers are considering their own prohibition.

New Jersey’s Fair Price Protection Act, signed in July, prohibits using personal data and algorithmic systems to vary prices for groceries and a broad category of household products. The main restriction takes effect Aug. 1, 2027. The state also will impose a one-year moratorium beginning Feb. 1, 2027, on new electronic shelf labels while regulators study their relationship to surveillance pricing.

For businesses, the acceleration calls for a system-by-system compliance review, according to the Greenberg analysis. Companies should inventory every tool that recommends or changes prices, identify whether it uses personal or competitor data, and map each application against state-specific products, exceptions, disclosures and effective dates.

Vendor contracts also should require transparency about data sources and model inputs. Businesses relying on loyalty programs, individualized discounts or cost-based pricing should document why those practices qualify for statutory exceptions.

Federal scrutiny adds another layer. The Federal Trade Commission has acknowledged it lacks authority to prohibit personalized pricing categorically, but warned that failing to disclose how consumer data affects prices may violate existing federal law. As state measures proliferate, pricing governance is rapidly becoming a combined antitrust, privacy and consumer-protection responsibility.