San Francisco Leads the Charge: Enforcing the Ban on Algorithmic Rent-Setting Software

San Francisco has taken a pioneering stance against the use of automated rent-setting software, often referred to as AI revenue management, and is now moving to amend its initial legislation to strengthen enforcement. This action places the city at the forefront of a growing national debate on technology's role in housing affordability and market competition.

San Francisco's Initial Ban: A National First

San Francisco became the first city in the nation to implement a local ban on automated rent-fixing software. This legislation, adding Section 37.10C to the Rent Ordinance, went into effect on October 14, 2024. The ban, initially introduced as File No. 240766 and later enacted as Ordinance No. 224-24, prohibits both the sale and use of these algorithmic devices for residential dwelling units in the city.

The ordinance defines an "algorithmic device" as a software program that uses algorithms to analyze "non-public competitor data" concerning local or statewide rents or occupancy levels. This "non-public competitor data" includes information not available to the general public, such as actual rent prices, occupancy rates, and lease start and end dates. The law aims to prevent landlords from indirectly coordinating to artificially inflate rents and vacancy rates.

Violations of this prohibition can lead to significant penalties. The City Attorney is authorized to file civil actions seeking damages, injunctive relief, restitution/return of illegal profits, and civil penalties of up to $1,000 per violation, along with reasonable attorney's fees if the City Attorney is the prevailing party. Individual tenants can also file civil actions for similar remedies. Each month a violation continues and each separate residential unit affected constitutes a distinct violation.

Proposed Amendment: Empowering Tenant Advocates

San Francisco's Board of Supervisors has also introduced File No. 240796, an ordinance to amend the existing Administrative Code related to the ban on automated rent-setting. This proposed amendment, which duplicated File No. 240766 in July 2024, primarily seeks to authorize tenant's rights organizations to enforce the prohibition against landlords' use of algorithmic devices. These non-profit organizations, with a primary mission of protecting tenants' rights, would be able to bring civil actions to enforce violations, seeking remedies including attorneys' fees and costs.

The Issues: A Heated Debate

The proposed legislation and the broader concept of banning rent-setting software have generated significant debate, with strong arguments from both proponents and opponents.

Arguments for the Ban (Proponents like the American Civil Liberties Union):

• Indirect Price Fixing: Proponents, including Lee Hepner of the American Economic Liberties Project, argue that "automated rent setting" or "AI revenue management" involves landlords delegating their rental price and supply decisions to a common decision-maker. This system enables landlords who should be competing to share non-public, competitively sensitive data. One landlord operator even noted that the software "helps us to work together... to make us all more successful in our pricing... we rarely make any overrides to the [pricing] recommendations".
• Market Distortion: The software, which uses live dynamic pricing based on a large dataset of over 16 million units and is responsible for pricing 8% of all rental units nationwide, is alleged to increase rents, restrict supply, and increase eviction rates. It is believed to have contributed to double-digit rent increases and higher vacancy rates in tandem.
• Increased Evictions/Turnover: A lessor defendant acknowledged that adopting RealPage's pricing increased turnover rates by 15 percentage points, leading to an additional $10 million in income by "pushing people out".
• Consolidation of Ownership: The software is seen as fueling the consolidation of corporate and private equity ownership of rental housing, disadvantaging smaller landlords.
• Legal Scrutiny: Numerous antitrust lawsuits have been filed against companies like RealPage, Inc. and Yardi Systems, Inc., alleging unlawful rent-fixing. These include lawsuits by the District of Columbia Attorney General (November 2023) and the Arizona Attorney General (February 2024), along with over 20 federal private class action lawsuits consolidated in Tennessee. The U.S. Department of Justice has also filed a Statement of Interest supporting regulation efforts, and the White House has made algorithmic price fixing a priority.
• Impact of Low Penetration: Proponents argue that even low market penetration (e.g., 5%) can lead to significant market manipulation (up to 70% in certain sub-markets) and have "spillover effects" into other property types.

Arguments Against the Ban (Opponents like RealPage, Inc. and American Consumer Institute):

• RealPage's Legal Representation: Gibson, Dunn & Crutcher LLP represents RealPage, Inc. and has challenged the claims made in support of the ban as "false and misleading".
• Recommendations, Not Decisions: RealPage asserts its software makes pricing recommendations, which landlords are free to accept or reject, and that landlords accept these recommendations on average less than 50% of the time. RealPage also states it never penalizes customers for declining recommendations.
• Focus on Occupancy: RealPage contends its products, such as YieldStar, include features for lease expiration management and move-in day optimization to help customers increase occupancy and align supply and demand, not solely to raise rents. The software recommends price changes in all directions, including reductions, to fill vacant units competitively.
• Lower Vacancy Rates: RealPage's data indicates that properties using its software generally have lower vacancy rates than the national average. They also clarify that "turnover rates" are not "eviction rates".
• Low Market Penetration: RealPage argues its market penetration in the San Francisco MSA is very low (around 6.1% for AIRM/YieldStar combined and 4% for LRO), and that claims of higher penetration based on its "RealPage Explore" tool are erroneous due to the tool's disclaimer that it does not list RealPage customers.
• Responsible Data Use: RealPage claims it uses non-public data only in anonymized, aggregated forms and does not share specific competitor information, viewing this as pro-competitive and consistent with antitrust laws. RealPage states the U.S. Department of Justice reviewed its products in 2017 and granted clearance.
• Broader Economic Factors: The American Consumer Institute (ACI) argues that File No. 240766 will have no impact on the structural problems causing high rent prices. They believe AI enhances business efficiency and consumer welfare, and that blaming algorithms avoids addressing complex issues like inflation, interest rates, and capacity. ACI points to Zillow data suggesting overall rent prices in San Francisco have actually fallen year-over-year. Opponents suggest San Francisco should focus on building more housing and removing "complicated roadblocks" such as exclusionary land use requirements and high building fees. Housing affordability, they argue, is a national problem driven by undersupply, increased demand, inflation, high mortgage rates, and burdensome zoning requirements, not revenue management software.

Other Jurisdictions Taking Action

San Francisco is part of a growing trend, with several other jurisdictions pursuing similar legislative measures:

• Berkeley, California, has already adopted an ordinance banning the sale or use of pricing algorithms for residential rents and occupancy levels.
• Jersey City, New Jersey, adopted an ordinance on May 21, 2025, aimed at preventing algorithmic rent-fixing in its rental housing market.
• Providence, Rhode Island, is currently considering an ordinance to prohibit algorithmic rent-setting devices.
• West Hollywood, California, where renters comprise approximately 80% of occupied units, plans to direct staff and the City Attorney to draft a similar ordinance.
• Other cities like San Diego, San Jose, Santa Monica, and Minneapolis have also proposed or are drafting similar legislation.
• At the state level, California Senator Sasha Renée Pérez introduced SB 52 in February 2025. This bill seeks to regulate algorithmic devices by prohibiting the use or sale of a single algorithm by multiple landlords in the same market or one that incorporates non-public competitor data.

The ongoing legislative and legal battles highlight the significant societal implications of AI in competitive markets, particularly in essential sectors like housing. As more cities and states consider these bans, the discussion about balancing technological innovation with equitable housing and consumer protection will undoubtedly continue to evolve.