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Current Developments in DOJ Antitrust Actions
Over the past two years, the U.S. Department of Justice ("DOJ") Antitrust Division has pursued an aggressive enforcement agenda, targeting monopolistic behavior, algorithmic coordination, and anti-competitive mergers across sectors with a primary interest in regulating the technology industry.
In April 2025, the DOJ secured a landmark victory in its ad-tech monopolization case against Google, with the court ruling that Google illegally monopolized publisher ad servers and ad exchanges, thereby harming online publishers and advertisers. The ruling represents one of the first high-profile wins against a dominant digital-advertising intermediary in decades. In a parallel search monopoly case, the court found Google had violated Section 2 of the Sherman Act by locking up distribution through default search contracts with Apple, Samsung, and other device makers. The September 2025 remedies order restricted Google's ability to pay for default search status and required date-sharing access to rivals.
Beyond Big Tech, the DOJ has expanded into algorithmic and labor-market enforcement. In July 2025, the Division announced the first-ever antitrust whistleblower-rewards program, offering informants 15-30 percent of any criminal fine exceeding $1 million for actionable tips. It has also emphasized labor-market competition by prosecuting wage-fixing and anti-poaching agreements.
How is the DOJ Taking Aim at Big Tech Companies
Under the current administration, the DOJ's most visible efforts focus on the structural dominance of Big Tech platforms, notably Google and Apple, which have been viewed as digital gatekeepers that use data and litigious delay tactics to maintain monopolies.
The DOJ's actions against Google illustrate a two-pronged strategy: dismantling its control over market share of search engine traffic and its vertical dominance in advertising technology. In a case regarding search market share, the DOJ argued that Google paid over $20 billion annually to device manufacturers and browser developers (including Apple and Mozilla) to make Google the default search engine, foreclosing rival engines such as Bing, DuckDuckGo, and Ecosia. The ruling found Google's conduct "unlawfully maintained monopolies" in search and search advertising. In the remedies phase conducted in September 2025, the court prohibited exclusive-default contracts and mandated that Google share certain query-data streams with competitors to facilitate market entry.
Simultaneously, the DOJ targeted Google's end-to-end control of the digital-advertising stack—from the published ad server (DFP) to the exchange (AdX) to advertiser-buying tools. The government claimed this vertical integration let Google both buy and sell ads in markets it controlled. The government claimed this vertical integration let Google both buy and sell ads in markets it controlled. The April 2025 verdict found Google monopolized and tied these products unlawfully, and the DOJ is now seeking structural relief, including a potential divestiture of AdX or DFP.
The DOJ's March 2024 lawsuit against Apple attacks a different form of market power: the walled-garden smartphone ecosystem. The complaint alleges Apple leverages its control over iOS, the App Store, and hardware interfaces to exclude cross-platform apps, payment processors, and messaging services—raising consumer switching costs and suppressing competition in app distribution and mobile wallets. Apple's motion to dismiss was denied in June 2025, allowing discovery to proceed. The DOJ's theory mirrors its Google approach: focusing on "ecosystem foreclosure," not just pricing. Potential remedies could force Apple to permit third-party app stores, open its near-field communication (NFC) system for mobile payments, and allow greater interoperability in messaging and accessories.
Price-Fixing Algorithms
A more novel DOJ concern involves price-fixing algorithms—software systems that coordinate pricing among competitors, often without direct human collusion. These algorithms use shared data inputs and optimization models to recommend or automatically set prices across firms. When multiple competitors contribute non-public pricing data to a common platform, and the platform outputs harmonized pricing recommendations, the DOJ considers it a hub-and-spoke conspiracy facilitated by technology.
A leading example is United States v. RealPage Inc. filed in August 2024. RealPage sells property-management software widely used in the U.S. rental-housing market. The DOJ's complaint alleged RealPage collected sensitive rental and occupancy data from thousands of landlords and used it to generate algorithmic rent recommendations. Participating landlords allegedly adopted these recommendations resulting in higher, synchronized rents across competing properties. RealPage's algorithms, such as "YieldStar" and "AIRM," effectively replaced independent pricing decision with a data-driven hub coordinating competitors' rents.
In January 2025, the DOJ expanded the case by adding major landlords like Greystar and AvalonBay as co-defendants, and in August 2025, Greystar agreed to a proposed consent decree requiring it to stop using RealPage's data-driven pricing recommendations and to cease sharing non-public rent data. The agency characterized the case as emblematic of "digital collusion," asserting that "training a machine to collude is still collusion." The DOJ's position underscores that traditional antitrust rules—especially Section 1's ban on concerted action—apply equally to algorithm-mediated coordination.
The RealPage case has broader implications beyond housing. DOJ officials have indicated they are examining algorithmic pricing in health care, travel, and e-commerce, where similar data-pooling models could fix prices indirectly. The agency has warned that sharing competitively sensitive data with a third-party vendor—especially when that vendor serves multiple competitors—can create unlawful coordination even absent explicit agreement. Firms relying on dynamic-pricing or revenue-management tools are therefore reassessing compliance policies to ensure algorithms use only public or firm-specific data.
Price-fixing algorithms introduce a frontier for modern antitrust enforcement: they highlight how AI and data platforms can entrench collusion at scale. The RealPage litigation signals the DOJ's intent to ensure technological mediation does not become a loophole to evade antitrust law. Going forward, the agency's focus on algorithmic coordination, combined with its whistleblower-rewards program, suggests a growing pipeline of cases in which software vendors and their clients face joint liability for algorithmic collusion.
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