Artificial intelligence is sweeping the retail segment, impacting how consumers shop and reshaping how prices are set across the market. On the pricing front, what began as a technological tool for streamlining adjustments and improving margins has evolved into a legal flashpoint. As AI-powered pricing tools grow more advanced, so does scrutiny over their potential to distort competition, mislead consumers, and violate long-standing antitrust laws.
Retailers increasingly rely on dynamic pricing algorithms (and other AI-supported services) to adjust product prices based on real-time data, including consumer behavior, inventory levels, market trends, and competitor activity. But regulators, lawmakers, and the plaintiffs’ bar now are increasingly focusing their attention on whether these systems, when used by multiple market players, effectively enable firms to coordinate pricing – without ever directly communicating.
This convergence of innovation and antitrust risk has made algorithmic pricing one of the most closely watched legal battlegrounds of 2025.
Regulatory Scrutiny & New Legislation
Global competition authorities are no longer just observing. Over the past decade, international entities – ranging from the EU, the G7, and the OECD to Canada’s Competition Bureau – have been exploring (and, in Canada’s case, taking action over) the competitive risks posed by algorithm-driven pricing. In the U.S., the Department of Justice filed a proposed settlement with Greystar Management Services, resolving claims that its software facilitated price alignment across landlords by using confidential competitor data to generate rent recommendations.
At the same time, California has enacted AB 325 and SB 763 to bar the use of such tools in anticompetitive conspiracies and raised penalties for violations of the state’s antitrust statute. New York’s Algorithmic Pricing Disclosure Act, which went into effect on November 10, requires companies that use consumer data to set prices to notify customers with a clear message: “This price was set by an algorithm using your personal data.”
New York’s AI pricing law targets opaque price customization practices that rely on user-specific data. Supporters say it helps level the playing field for consumers, who are often unaware they may be charged more (or less) depending on who they are.
Not without pushback, the National Retail Federation (“NRF”) is challenging the law in federal court, arguing that it compels speech in violation of the First Amendment. The NRF claimed the disclosure unfairly stigmatizes a common and beneficial business practice – namely, using customer data to deliver personalized promotions or discounts. However, a federal court dismissed the challenge, ruling that the law only requires the disclosure of factual, uncontroversial information and is legally valid under the Zauderer standard, which governs commercial speech disclosures.
The NRF is in the process of appealing the decision, marking a significant constitutional test case for retail regulation in the age of AI.
Private Litigation Gains Steam
Meanwhile, private litigation is gaining traction in related sectors, especially hospitality. Since 2023, at least five federal class action lawsuits have accused hotel brands and pricing software vendors of using algorithmic tools to coordinate room rates. The cases argue that by pooling proprietary data into centralized platforms and receiving optimized price suggestions in return, hotels effectively engage in price fixing.
While these cases specifically target hotel industry, the underlying legal theories – including Section 1 of the Sherman Act, which prohibits “contracts, combinations, or conspiracies in restraint of trade” – have direct relevance for retail. Many retailers use similar AI tools for performance benchmarking and price recommendations.
It is worth noting that to date, multiple hotel algorithmic-pricing suits have been dismissed at the pleading stage due to a lack of evidence that competitors agreed to coordinate pricing. Courts emphasized that using the same pricing tool is not illegal on its own. In Gibson v. Cendyn, for example, the Ninth Circuit held that multiple hotels adopting the same software does not prove collusion unless there are additional “plus factors” – such as secret communications or shared intent – to support the inference of a conspiracy.
The same reasoning would likely apply to retail unless plaintiffs can show retailers went beyond mere parallel use and actually aligned their pricing strategies in concert.
This shift raises key questions for retailers: Can independent use of pricing software be construed as tacit collusion? Does participation in market intelligence platforms risk antitrust exposure? How much control should retailers retain over AI-generated pricing decisions?
THE BOTTOM LINE: Algorithmic pricing is not inherently illegal. But in today’s regulatory climate, how it is used – and how transparently it is disclosed – matters more than ever. What was once a quiet back-office optimization tool is now a front-page legal issue. And for retail in 2025, the stakes are high.
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