The Ongoing Legal Trajectory Against Remaining Entities

While the settlements with Greystar and the initial group of twenty-six other landlords have resolved claims for a significant slice of the market—affecting over 1.3 million units across 43 states and D.C., according to the state coalition announcements (Source: Mass.gov, Nov. 19, 2025)—the war is far from over. The main engagement continues against the software provider, RealPage, and the remaining property management firms who have not yet settled.

Cooperation as a Legal Lever

One of the most telling components of the Greystar settlements is the provision requiring them to act as a government cooperator. This is not a minor administrative detail; it’s a strategic move by enforcement agencies. By securing the cooperation of one of the largest defendants, the Department of Justice (DOJ) and the state attorneys general are leveraging a massive, knowledgeable entity to help build a stronger, more granular case against the holdouts. Think of it like the informant in a cartel case, only this time, the informant is a multi-billion-dollar property services entity.

This cooperation could provide the plaintiffs with internal documentation, communications logs, and a deep understanding of how the algorithms were *actually* deployed versus how they were advertised. For the remaining defendants, the stakes just got significantly higher. They are now facing not only the original government allegations but also the testimony and evidence provided by a former peer who has already capitulated on the operational use of the specific pricing tools.

RealPage’s Defense: Market Fundamentals Over Machine Code. Find out more about Algorithmic price signaling antitrust precedent.

RealPage, for its part, continues to vehemently defend its position, arguing that the high cost of rent is a reflection of fundamental, undeniable economic realities—namely, a severe housing supply shortage, not their software’s design. They maintain their tools are sophisticated yield management systems, akin to what an airline uses to price seats, and that any correlation in pricing is merely the result of independent actors making rational business decisions based on the best available market data. The company has, in recent filings, pointed to the varying outcomes in court—like the dismissal in the Mach v. Yardi Systems case cited in some legal analyses digital twin economics in real estate—as evidence that courts recognize the difference between independent optimization and illegal agreement.

However, the DOJ’s counter is powerful: training the machine to mimic the behavior of a cartel is functionally equivalent to operating one. The DOJ’s position, articulated in filings earlier this year, suggests that the knowing combination of sensitive, nonpublic pricing information into an algorithm that competitors rely upon can constitute concerted action under Section 1 of the Sherman Act (Source: JDSupra, Oct. 2, 2025). The future path of litigation against the holdouts—including major players like LivCor and Camden Property Trust—will be the ultimate test of this theory.

This evolving narrative means every property manager using *any* sophisticated pricing tool must stay on high alert. The implications for operational autonomy are vast. If courts validate the precedents set by these technology-focused settlements, the very nature of how property management firms utilize third-party data analysis will have to change. Will they revert to simpler, public-data-only tools? Or will they develop proprietary systems that are structurally incapable of absorbing competitor data? These are the high-stakes questions being answered right now.

The Technology That Binds: Algorithmic Coordination Across Sectors

This entire episode underscores a foundational theme that will dominate regulatory focus for the foreseeable future: the intersection of Big Data, AI, and essential services like housing, healthcare, and logistics will be under an intense microscope. The reverberations of this property management challenge will extend far beyond apartment rentals, offering a clear template for future enforcement actions.

When Software Becomes the Cartel Hub. Find out more about Algorithmic price signaling antitrust precedent guide.

The core legal challenge here is the concept of the “hub-and-spokes” conspiracy, traditionally applied to scenarios where a central entity coordinates prices among separate competitors. In the RealPage case, the software vendor is the hub, and the landlords are the spokes. The innovation—or transgression, depending on your viewpoint—is that the coordination mechanism is an algorithm trained on shared, non-public data.

We must understand this isn’t about banning AI; it’s about auditing its inputs and outputs. As one legal analyst noted, “training a machine to break the law is still breaking the law.” The move by states like California and New York to pass explicit legislation banning certain algorithmic uses highlights the speed at which the legislature is trying to catch up with the technology (Source: Baker McKenzie, Nov. 5, 2025). New York’s amendment to the Donnelly Act, for example, specifically targets tools that collect and analyze data from multiple property owners, regardless of the vendor’s location, with an effective date looming in December 2025.

This creates an immediate need for robust governance frameworks for property management technology. When a technology vendor’s product is central to the market’s competitive health, its design choices become matters of public policy, enforced by antitrust divisions.

The Fear of Price Uniformity: A Non-Economist’s View

Why should a property owner who believes they are simply optimizing revenue for a single portfolio care? Because the market only works when there is friction—when you are slightly better, slightly faster, or slightly cheaper than your neighbor on a given day. That friction drives consumer choice and innovation. When an algorithm, fed by the collective secrets of the market, starts pushing everyone toward a single, high-water mark for rent, that friction disappears. Tenants no longer have the incentive to shop around because the algorithm has effectively eliminated the lower-priced options before they ever hit the market.. Find out more about Algorithmic price signaling antitrust precedent tips.

It’s the creeping consensus that erodes the competitive landscape. If a property manager is told their recommended rent is $2,150, and the algorithm recommends $2,155 for the building next door based on its (secret) data, why would the first manager ever drop to $2,125 to capture a vacancy? They wouldn’t—and that’s the coordination regulators are targeting. This is the difference between knowing the market and *becoming* the market.

Actionable Takeaways for PropTech and Property Owners

This legal and regulatory pivot demands a proactive response, not a reactive scramble after the next amended complaint lands. Whether you are a software developer building the next-generation tool or a portfolio manager deciding which tool to license, the mandate is clear: prioritize transparency and build defenses against perceived coordination.

For Technology Providers: Auditing the Code for Antitrust Risk

Your product’s value proposition must shift from “market-leading optimization” to “transparent, compliant market insight.”

1. Data Segregation and Certification: Implement immutable, auditable proof that your algorithms are trained only on publicly available data, or on data siloed *per client* where outputs cannot reveal competitor-specific inputs. If you must use client data, adopt a structure that forces aggregation to a very high, anonymized level before any output is generated.. Find out more about Algorithmic price signaling antitrust precedent strategies.
2. Sunset Clauses for Risk-Prone Features: Following the lead of some of the initial settlements, proactively decommission features identified as high-risk. If the DOJ or a state AG has singled out a specific way a tool uses data (like the discontinued Lease Rent Options, or LRO, product), eliminate that capability immediately from all clients, not just the ones settling.
3. Embrace External Monitoring: The Greystar settlement with the states mandates accepting a court-appointed monitor if a third-party pricing algorithm is used (Source: CT.gov, Nov. 19, 2025). Tech companies should consider building in a “Compliance Mode” that voluntarily submits to third-party, non-governmental audits to certify data hygiene and output neutrality. This builds trust when regulators come knocking.
4. Rethink Client Meetings: The ban on attending RealPage-hosted meetings of competing landlords is a direct warning against facilitating *any* communication channels where operational parameters for your software might be discussed. Do not host forums where your clients can discuss what parameters they are setting in your tool.

For Property Management Firms: Reclaiming Operational Autonomy

The era of outsourcing core pricing intelligence without deep due diligence is over. Your firm’s competitive posture now depends on your technology governance.

• Demand Data Lineage Reports: Before signing a new contract for any revenue management software, demand a clear, written schematic of what data is ingested, how it is combined, and what controls exist to prevent the use of your proprietary renewal or concession data to influence a competitor’s output.. Find out more about Algorithmic price signaling antitrust precedent overview.
• Establish Clear Internal Walls: Ensure the teams setting strategic pricing parameters are separate from the teams feeding operational data into third-party tools. Create an internal firewall, documented in policy, that prevents the sharing of non-public pipeline data with any external service that also serves a direct competitor.
• Analyze Public Data More Deeply: If the legal landscape is shifting toward suspicion of aggregated, non-public data, your competitive edge must shift back to superior, human-driven analysis of publicly available trends. Invest in training your analysts on market fundamentals rather than relying on a ‘black box’ recommendation. This is about building your future of property management operations knowledge base internally.
• Review Existing Agreements: If you are one of the landlords still fighting the case against RealPage and co-defendants, a full, realistic risk assessment against the known settlement terms (cooperation, data ban, monitoring) is paramount. The legal cost of fighting the trend is often higher than the cost of settling early.

The Ripple Effect: Beyond the Apartment Door

The implications of this evolving narrative cannot be overstated. This is a template. Any industry relying on sophisticated algorithmic coordination tools—from insurance underwriting to logistics pricing—should be watching the outcomes in the Middle District of North Carolina very closely.. Find out more about Greystar anticompetitive rent pricing scheme settlement definition guide.

If courts ultimately validate the idea that sharing non-public data into a common algorithm can constitute a per se violation of antitrust law, it fundamentally redefines digital collusion. This extends the regulatory gaze into areas like:

• Healthcare Administration: Tools that aggregate patient data from competing hospital systems to suggest optimal billing rates.
• Logistics and Shipping: Software that coordinates shipping rates based on the proprietary capacity data of multiple trucking companies.
• E-commerce Pricing Engines: Platforms that blend proprietary sales velocity data from multiple sellers on a single marketplace.

The core principle being established is simple: Competition requires independent decision-making. When technology creates a system where independent actors *must* feed their secrets into a common machine to get a competitive price recommendation, the independence is compromised. Regulators are asserting that they have the authority to look past the convenience of the software and examine the anticompetitive structure it enables.

This forces a philosophical shift. Property management, an industry long defined by localized, relationship-based competition, is now being redefined by data science, and the law is rushing in to ensure that science serves the consumer, not just the provider.

Conclusion: The Cost of Coordination in an Algorithmic Age

The settlements involving Greystar are more than just financial remedies or operational restrictions; they are foundational documents in the history of technology antitrust enforcement. As of November 19, 2025, we have concrete judicial interpretations, through consent decrees, that set a clear, conservative path forward: Your data inputs must not be your competitor’s insight. The risk of algorithmic price signaling is real, and the precedent is set by the parties who chose cooperation over protracted legal battles.

For the property management sector, the path forward requires a commitment to ethical, transparent, and fiercely competitive business practices. The industry must move beyond simply asking, “Is this tool legal?” to asking, “Is this tool transparently competitive?” The remaining legal trajectory against RealPage and the other holdouts will only cement these new rules, but the blueprint is already visible in the agreements already signed.

The next lease renewal you process, the next software contract you sign—it all takes place under the long shadow of this litigation. Don’t wait for a court order to clean up your data sharing. The time to reassess your reliance on centralized, proprietary data-fed algorithms is right now.

What is your organization doing to proactively audit its reliance on aggregated pricing data? Share your thoughts on how these precedents will reshape the broader proptech landscape in the comments below.