DOJ Threatens AI Innovation and Antitrust Law in RealPage Suit

Arizona Attorney General Kris Mayes’ letter demanding Attorney General Pam Bondi to protect renters from market manipulation argues the Department of Justice should intervene in the housing pricing software market—the exact opposite of what the government should do when it comes to antitrust policy.

Imploring Bondi to continue litigating a premature lawsuit the Biden administration initiated against the artificial intelligence-driven company RealPage may be well-intentioned from a political perspective, but it represents a misunderstanding of sound antitrust enforcement.

It would be a welcome development for the Trump administration to drop the case.

Pursuing the RealPage case would risk making a historic misstep that transcends the particular facts. It could effectively criminalize the use of pricing algorithms across the entire economy, stifle AI development, and cast a chilling effect over innovation across numerous economic sectors. Legal practitioners committed to the rule of law and empirical evidence must view this case with profound skepticism.

DOJ’s Argument

The crux of the DOJ’s complaint alleges that landlords using RealPage’s YieldStar pricing software—which uses supply and demand and other market data to recommend real-time rental pricing changes—engages in unlawful collusion to inflate apartment rents, violating Section 1 of the Sherman Act. The DOJ claims that such conduct represents “tacit” collusion simply because competing landlords choose to use the same software program, even though they don’t communicate with each other.

Worryingly, the RealPage lawsuit isn’t an isolated incident but part of a broader regulatory pattern targeting algorithmic pricing. In October 2024, the DOJ filed an amicus brief challenging the dismissal of a lawsuit against major Las Vegas hotels accused of using shared data and algorithms to inflate room rates.

Earlier, in March 2024, the DOJ and the Federal Trade Commission jointly filed a statement of interest in a similar case involving Atlantic City casino-hotels, asserting that competitors can’t use algorithms as a shield for unlawful agreements.

The DOJ’s interpretation of algorithmic pricing dangerously equates the use of sophisticated analytical tools with unlawful conspiracy. It suggests a regulatory agenda driven more by discomfort with new technology than by rigorous application of antitrust law.

This represents a significant and potentially hazardous departure from established antitrust precedent, blurring the lines between independent decision-making aided by data and explicit collusion.

A Faulty Case

The case against algorithmic AI misinterprets the Sherman Act by conflating lawful competitive behavior with illegal collusion. A core requirement for a Section 1 violation is the existence of an “agreement,” whether explicit or inferred from conduct that makes little economic sense absent collusion.

As analysis from legal scholars and economists has underscored, competitors independently adopting similar strategies in response to market conditions or available information isn’t collusion; it is the very essence of competition.

Established legal precedent reinforces this distinction between parallel conduct and competition. The US Supreme Court’s decision in Standard Sanitary Manufacturing Co. v. United States emphasized the need for a manifested agreement or concerted action beyond mere information exchange for collusion to exist under the Sherman Act.

Additionally, in In re: Text Messaging Antitrust Litigation, the US Court of Appeals for the Seventh Circuit—in an opinion authored by Judge Richard Posner—determined that “parallel behavior of a sort anomalous in a competitive market” alone isn’t proof of price fixing.

Economic Effects

Economists and technology fellows agree that the DOJ overexpanding the Sherman Act to go after algorithmic pricing could conflate competitive parallel behavior with illegal collusion and ultimately deter companies, particularly smaller ones lacking vast litigation resources, from using beneficial AI technologies in their businesses.

This broader approach to antitrust—one based more on shifting values than economics—risks regulating through fear and ambiguity rather than establishing clear rules of the road for emerging technologies such as AI.

The implications extend far beyond the residential rental market. Algorithmic pricing tools are ubiquitous, optimizing prices and resource allocation in industries ranging from airlines and hotels to ride-sharing services, cloud computing, and digital advertising.

If the DOJ’s theory prevails, the mere act of subscribing to and using a shared pricing algorithm—even without any explicit agreement among competitors to fix prices—could be construed as evidence of an antitrust conspiracy.

Companies would face an untenable choice: Leverage powerful tools to enhance efficiency and competitiveness or forgo these advantages out of fear of draconian legal exposure.

Outlook

Allowing this case and its underlying theory to proceed unchecked would pose significant legal and economic risks. It would inject profound uncertainty for any business employing algorithmic pricing tools. It would invite a flood of speculative private litigation targeting companies for merely using common software solutions.

Most damagingly, it could discourage the adoption of AI and machine learning across the economy, hindering productivity gains precisely when they are needed most.

A decision to drop the suit wouldn’t be “pro-corporate,” but rather a defense of the rule of law, a step toward innovation, and a necessary move to prevent legal uncertainty from stifling progress across the economy. It also would greatly benefit consumers—the primary intended beneficiaries of antitrust law.

The case is United States v. RealPage Inc., M.D.N.C., No. 1:24-cv-00710.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

John Reeves of Reeves Law LLC is a solo appellate lawyer based in St. Louis. He is a former assistant Missouri attorney general.

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