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The last stretch of 2025 saw significant developments in antitrust litigation involving algorithmic pricing and listing services in the real estate sector. As artificial-intelligence driven software and other real estate business practices continue to generate antitrust litigation, companies should remain vigilant about the risks of incorporating new technologies and listing policies into their business models.

Algorithmic Pricing: Settlements and New Legislation.

Four settlements involving algorithmic pricing tools, also known as “revenue management” software, suggest that firms using such technology without proper controls may face the risk of expensive litigation and/or potential liability. At the center of this emerging litigation trend is an ongoing multidistrict litigation involving claims brought by government enforcers and private plaintiffs against RealPage, Inc. (“RealPage”), a provider of revenue management software in the multifamily residential housing industry. Plaintiffs sued RealPage and a number of landlords for using its algorithm, which they allege “inputs a melting pot of confidential competitor information … and spits out price recommendations based on that private competitor data.”^[1] Plaintiffs claim that this allows landlords to ascertain competitors’ rents, discounts, and occupancy rates, and in some cases, coordinate renewal increases.[2] In 2023, the MDL court denied a motion to dismiss the plaintiffs’ claims, finding a plausible risk of anticompetitive effects from the exchange of “sensitive pricing and supply data” by firms who control much of the multifamily housing market.[3]

• On November 19, 2025, defendant Greystar Management Services LLC (“Greystar”) reached a $7 million settlement in a parallel lawsuit brought by nine State Attorneys General, thereby resolving claims that it used the RealPage algorithm to share competitively sensitive data and generate pricing recommendations.[4] Greystar also entered a consent decree under which it has not admitted liability, but will refrain from using any anticompetitive algorithm that generates pricing recommendations using its competitors’ competitively sensitive data and accept a court-appointed monitor for the use of any other algorithmic pricing software.[5] The States’ case continues against five other rental management companies.
• On November 21, 2025, 26 defendant firms in the RealPage MDL entered a court-approved settlement for a total of $141.8 million.[6] The settlement states that it does not represent an admission of liability by the settling defendants. According to plaintiffs, these defendants were “property managers only,” and “many of the smallest” in terms of total volume of commerce. One of the larger individual settling defendants, Greystar, settled for $50 million.[7] Litigation continues against the non-settling firms.
• On November 24, 2025, the Department of Justice settled with RealPage under a consent decree, imposing the supervision of a court-appointed monitor, barring RealPage from marketing algorithms that incorporate competitively sensitive information that is less than 1 year old or related to active leases, and requiring antitrust compliance measures. RealPage has not admitted liability, but has agreed to adhere to the proposed consent decree.[8]
• On December 23, 2025, the DOJ reached a similar settlement and consent decree with defendant landlord LivCor, LLC (a Blackstone portfolio company).[9]

Three states, California, New York, and Connecticut, have enacted specific algorithmic pricing laws:

• Effective October 6, 2025, California amended the Cartwright Act (its state antitrust law) to make it unlawful to use a common pricing algorithm as part of a conspiracy to restrain trade or commerce, or to coerce another person to set or adopt a recommended price or commercial term recommended by a common pricing algorithm.[10] Prior to this amendment, the Cartwright Act already prohibited contracts, combinations, or conspiracies that restrain trade. What the new law makes clear is that activities that previously violated the Cartwright Act remain unlawful even when a common pricing algorithm is used, and that the use of common pricing algorithms is per se unlawful if coercive price-setting is involved. This ban on collusive use of common pricing algorithms includes any software or other technology that uses data from two or more competitors “to recommend, align, stabilize, set, or otherwise influence a price or commercial term.” According to the Floor Analysis for the bill, it “applies regardless of whether the underlying data is public or private, reflecting the understanding that even public data can enable collusion when processed similarly across competitors.”^[11] Whereas prior versions of the bill specifically prohibited pricing algorithms using “nonpublic competitor data,”^[12] the bill was passed without that language. Given the bill’s express requirement of a collusive agreement in restraint of trade,^[13] some have argued that using an algorithm trained on public data will create liability only if the “collective use of the pricing tool occurred as part of a contract, combination, or conspiracy to restrain trade, or if one [firm] coerced others to adopt or adhere to the algorithm’s outputs.”^[14] Courts have yet to interpret the new law to give guidance concerning its scope and application. The amendment also relaxes the pleading standard by relieving plaintiffs of the burden to “allege facts tending to exclude the possibility of independent action.”[15] Under a parallel amendment increasing criminal penalties, corporate violations are capped at $6 million or twice the amount of pecuniary gain to the violator or pecuniary loss to the victim, along with a civil penalty of up to $1 million. Individual violators can face imprisonment of up to three years, as well as fines between $250,000 to $1 million.[16]
• Effective December 15, 2025, New York amended the Donnelly Act (its state antitrust law) to prohibit the use of algorithms to set rental rates. The amendment makes it unlawful for landlords to make decisions about pricing, renewal, occupancy, or other lease terms “based on recommendations from a software, data analytics service, or algorithmic device” under certain conditions. Namely, the algorithm may not collect “historical or contemporaneous prices, supply levels, or lease or rental contract termination and renewal dates … from two or more residential rental property owners or managers” and analyze that information to recommend “rental prices, lease renewal terms, ideal occupancy levels, or other lease terms and conditions.” The law draws no distinction between information that is public and historical, as opposed to confidential and current. Violations carry four years imprisonment and a maximum fine of $100,000 for individuals, and a maximum fine of $1 million for corporations.
• Effective January 1, 2026, Connecticut passed an omnibus bill, Section 32 of which amended the Connecticut Antitrust Act to prohibit any person from using “a revenue management device to set rental rates or occupancy levels for residential dwelling units.”[18] The prohibition expressly includes information that is “anonymized” and provided by a third party rather than a competitor, but unlike California and New York, explicitly restricts only those algorithms that use “nonpublic competitor data.” Connecticut legislators are also contemplating another proposed bill that would “prohibit residential rental property owners from using pricing algorithms and competitors’ sensitive data to set rental prices.”[19]

Others may soon follow suit. At the federal level, Congress is also considering a bill that would make it “unlawful for a person to use or distribute any pricing algorithm that uses, incorporates, or was trained with nonpublic competitor data.”[20]

Real Estate Listing Services.

Two lawsuits against Zillow showcase the continuing intersection of antitrust law with real estate listing markets. In Compass, Inc. v. Zillow, Inc., No. 1:25-cv-5201-JAV-SDA (S.D.N.Y.), a major national real estate brokerage (Compass) sued the leading online real estate marketplace (Zillow), alleging that Zillow engaged in anticompetitive tactics by banning “office listings” marketed exclusively on brokerage websites. As alleged, Zillow and other online real estate marketplaces agreed to block from their search platforms any property marketed off Zillow for more than a day, and allow the listing back onto their platforms only if the seller fires the listing agent and brokerage and hires a new agent and brokerage to manage the listing.[21] This precludes Compass and other brokerages from sharing listings internally with other Compass agents before posting them to Multiple Listing Services (MLS) databases, which automatically port the listing over to marketplaces like Zillow.[22] According to Compass, Zillow unlawfully seeks to maintain its dominance over the residential real estate search engine market by steering buyers away from brokerage firms’ exclusive office listings.[23] Compass has moved for a preliminary injunction, and in November 2025 the district court held a four-day evidentiary hearing on that motion, which remains pending.[24]

In Taylor v. Zillow Inc., No. 2:25-cv-1818 (W.D. Wash.), a putative class of homebuyers sued Zillow for allegedly steering them without disclosure toward Zillow agents rather than the agent hired by the seller to list the property. Plaintiffs allege that Zillow agents accessed these leads through a paid referral program, allowing Zillow to derive significant revenue from both referrals and a commission of up to 40% paid by agents.[25] The plaintiffs filed an amended complaint on December 29, 2025,[26] teeing up a potential motion to dismiss from Zillow.

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As litigation in these areas continues, firms should exercise extra diligence to mitigate risk. Experienced antitrust counsel should be consulted to review any use of algorithmic software related to business decision-making to ensure appropriate controls are in place. Similarly, any real estate association policies regarding listings or internal referral programs should be carefully reviewed by outside counsel.

Wiggin and Dana routinely advises clients in connection with the full range of antitrust, consumer protection, and unfair trade practices matters, including potential transactions, mergers and merger investigations, and representations before the FTC, DOJ, and offices of state attorneys general. Wiggin and Dana also regularly advises clients concerning evolving antitrust, consumer protection, and unfair trade practices, and regulatory landscapes.

[1] In re RealPage, Inc., Rental Software Antitrust Litig. (No. II), 709 F. Supp. 3d 478, 512 (M.D. Tenn. 2023).

[2] Id.

[3] Id. at 520, 528.

[4] Joint Motion of Plaintiff States and Greystar Management Services, LLC for Entry of Consent Judgment and Dismissal with Prejudice, available at https://portal.ct.gov/-/media/ag/press_releases/2025/greystar.pdf?rev=08ab78c1127e421f8cc53999e31a1d10&hash=3BC01962F47009654EAB967CE0DCBC61.

[5] Id. 

[6] https://business.cch.com/ald/InreRealPageIncRentalSoftwareAntitrustLitigaitonSettlementOrder11212025.pdf.

[7] See RealPage Settlement Filings.pdf (Exhibit A).

[8] https://www.justice.gov/opa/media/1419406/dl.

[9] https://www.justice.gov/atr/media/1422661/dl?inline.

[10] https://legiscan.com/CA/text/AB325/id/3272268/California-2025-AB325-Chaptered.html, Section 1.

[11] https://trackbill.com/s3/bills/CA/2025/AB/325/analyses/assembly-floor-analysis.pdf.

[12] See Assembly Bill 325 (Jan. 27, 2025), at https://legiscan.com/CA/text/AB325/id/3084704 (“A person shall not use or distribute any pricing algorithm that uses, incorporates, or was trained with nonpublic competitor data.”); id. (“‘Nonpublic data’ means information that is not widely available or easily accessible to the public, including information about prices, commercial terms, and related products or services, regardless of whether the data is attributable to a specific competitor or anonymized. Nonpublic data includes public-facing data made available under terms of service that prohibit the use of that data.”).

[13] https://legiscan.com/CA/text/AB325/id/3272268 (“It shall be unlawful for a person 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 in violation of this chapter.”).

[14] Lee F. Berger, Michael L. Weiner, and Weisiyu Jiang, Coordination by Code: Rethinking Antitrust Liability in the Age of AI Pricing, 40 ANTITRUST 24, 27 (Fall 2025).

[15] Id. Section 2.

[16] https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB763.

[17] N.Y. Gen. Bus. Law § 340-b.

[18] https://www.cga.ct.gov/2025/ACT/PA/PDF/2025PA-00001-R00HB-08002SS1-PA.PDF.

[19] https://www.cga.ct.gov/2025/TOB/H/PDF/2025HB-06497-R00-HB.PDF.

[20] https://www.congress.gov/bill/119th-congress/senate-bill/232/text.

[21] ECF 1 (Complaint) ¶¶ 1-3.

[22] Id. ¶¶ 4-5, 8-9.

[23] Id. ¶¶ 10-11.

[24] ECF 23 (Motion for Preliminary Injunction); see also https://www.realestatenews.com/2025/11/25/compass-v-zillow-hearing-who-made-the-stronger-case.

[25] ECF 1 (Complaint) ¶¶ 1-10.

[26] ECF 45 (Amended Complaint).