RealPage AI Rent Pricing Software Enables Algorithmic Collusion Among Landlords

RealPage, a Texas-based property management software company, developed and deployed AI-powered pricing algorithms called YieldStar and AI Revenue Management that have been used by landlords across the United States since approximately 2017. The system collected detailed rental data from competing landlords, including lease rates, occupancy levels, and market conditions, then used this aggregated competitive intelligence to generate pricing recommendations for participating properties. In October 2022, a ProPublica investigation revealed how the algorithm functioned, showing that landlords using RealPage's software were sharing competitively sensitive information and receiving coordinated pricing guidance. The investigation found that in some markets, RealPage's software was used by landlords controlling significant portions of rental inventory, with the algorithm consistently recommending rent increases even when individual property managers might have preferred lower prices to maintain occupancy. The Department of Justice Antitrust Division launched a formal investigation in 2023, focusing on whether the AI pricing system facilitated illegal price-fixing among competitors in violation of federal antitrust laws. The investigation examined communications between RealPage and landlords, the algorithm's design and decision-making processes, and market concentration in cities where the software was widely adopted. Simultaneously, multiple class action lawsuits were filed across various federal districts, alleging that the coordinated pricing recommendations constituted a conspiracy to artificially inflate rents. The legal theory underlying both the DOJ investigation and private litigation centers on algorithmic collusion - the concept that AI systems can facilitate coordination between competitors without explicit agreements. Plaintiffs argue that by feeding competitors' data into a shared algorithm that generates pricing recommendations, landlords effectively outsourced price-setting decisions to a third party in a manner that achieves the same anticompetitive effects as traditional cartels. The cases cite economic evidence showing above-normal rent increases in markets with high RealPage adoption rates, with some studies suggesting billions in excess rents charged to tenants. The litigation has highlighted broader questions about AI governance in competitive markets, particularly regarding data sharing practices, algorithmic transparency, and the application of traditional antitrust law to algorithmic decision-making. RealPage has maintained that its software provides legitimate business intelligence and pricing optimization, arguing that the recommendations are not binding and that landlords retain ultimate pricing authority. However, internal communications revealed through discovery have shown RealPage marketing its ability to help landlords avoid "race to the bottom" pricing competition.