New Montgomery County Law Prohibits Rent-Setting Algorithms

I've set a goal of listening to music by a new artist or composer every day. With millions of recordings available through streaming services, I thought it would be easy to find music from a variety of artists and genres.

But when I open my streaming app, it feels like the streaming service is determined to thwart my goal of expanding my listening scope. Instead of seeing new and different music, I have to scroll through dozens of recommendations that I listen to recordings of pieces I've already heard, performances by artists on my playlists, and music of the genres I’ve already listened to.

I ask myself how a service with so much music can make it so difficult to discover something new. But I already know the answer -- streaming service algorithms aren’t designed to help us expand our musical interests. Rather, the algorithms analyze our listening habits, including what we play, what we skip, and what other people with similar tastes enjoy. The algorithms aren’t designed to then recommend music we're likely to enjoy based on those patterns.

Algorithms can be amazing tools. They can analyze enormous amounts of information in seconds and make recommendations that might take a person hours to develop. But their recommendations depend on the instructions and information they're given and what they're programmed to accomplish. And in the case of music playlists, the instructions assume we want to listen to more of the same, rather than something new.

Algorithms are used in many industries. Algorithms can set concert ticket prices or the price you pay at the grocery checkout. In multifamily real estate, landlords can use algorithms to recommend rental rates and concessions they offer to tenants.

These uses of algorithms to set prices have drawn scrutiny, including lawsuits, and in some jurisdictions, laws prohibiting their use when they affect consumer pricing. For instance, Montgomery County, Maryland, where my office is located, recently passed Bill 8-26, which prohibits landlords from using certain algorithmic pricing systems to determine residential rents, following a similar law adopted by Rockville, Maryland (a city located in the County) last summer. This article discusses Bill 8-26, how rent algorithms work, and why they have drawn criticism.

How Rent-Setting Algorithms Work

Suppose you own a 200-unit apartment building with several vacant units. You want to get the most possible rent to help pay your expenses and make a profit, but you also don’t want those units to stay empty for long.

You might start by looking at nearby apartment buildings’ quoted rental rates for similar apartments. A building that’s older or has fewer amenities than yours might not charge as much as you can, and of course, a new building with better amenities or a better location might be able to attract tenants even at a higher rental rate. You know it could violate antitrust laws if you were to share information with other owners to set prices, but you could check the other buildings’ websites to see how many vacant units they advertise to understand what the supply looks like, and you could use your own statistics about inquiries to gauge demand for apartments.

Traditionally, property managers gather this type of information through advertisements, market surveys, and “secret shopper” telephone calls in which they pretend to be a prospective tenant. Then, the property manager would analyze that data and decide on a rental rate based on their personal experience with tenant behavior in the market. Rent algorithms save property managers that time by compiling that data and recommending a rental rate in minutes or seconds, rather than hours or days.

But that’s not all rent algorithms do. They also improve the accuracy of the data available to landlords. Public information isn’t always accurate or complete – after all, what landlord wants to advertise that their building is half empty. And secret shoppers learn the “asking rents,” but they don’t find out how much the landlord really ends up charging tenants.

Companies that offer rent setting algorithms often also have access to non-public information, such as how many units really are vacant, how many tenants don’t renew their leases, and how much landlords are really charging for rent. And the rent-setting algorithm might use that non-public information when establishing property rents.

That’s one objection to rent-setting algorithms. There’s a concern that they may provide landlords with indirect access to non-public rental data that they wouldn’t be able to lawfully obtain from their competitors.  Rent-setting algorithms in theory recommend rents based on market conditions and supply and demand, but some are concerned that the algorithm might instead artificially inflate rents.

What Does Bill 8-26 Do?

As passed, Bill 8-26 doesn’t prohibit all rent algorithms. The law only prohibits use of algorithms that use nonpublic competitor data to recommend rents, fees, lease terms, or occupancy levels. The law defines non-public information to include “information that is not available to the general public concerning actual rent prices, occupancy rates, lease start and end dates, and other similar data regarding a property other than a property that is owned or managed by the landlord who is the recipient or user of the generated recommendation, when such data is less than 90 days old.”

The law would allow a landlord to use a pricing algorithm based on its own rental data or based on historical data from other landlords that it at least 90 days old. The law doesn’t apply at all to products or services used to determine rent or income limits for affordable housing programs, nor does the law apply to individuals who own only one rental unit in the county.

The legislation also prohibits landlord price coordination and non-competition practices and subscription to algorithm devices or price coordination services (apparently even if the service isn’t used to set rents).

Other Rent-Setting Algorithm Laws

Montgomery County and Rockville aren’t the only jurisdictions that prohibit rent-setting algorithms. New York, Connecticut, New Jersey, and California have passed laws restricting rent-setting algorithms. New York and Connecticut already restrict certain systems that use rental information from multiple landlords to recommend rents or occupancy levels. New Jersey’s FAIR Act, which will take effect July 1, 2027. Rather than specifically prohibiting particular rental pricing algorithms, California’s law addresses rent-setting algorithms in the price setting laws by evaluating whether competing landlords use the technology as part of unlawful price coordination.

Maryland legislators introduced statewide legislation in 2026, but it didn't pass. And, in 2025, Colorado Governor Jared Polis vetoed a law that would have outlawed rent-setting algorithms in part on the basis that existing antitrust laws already prohibit unlawful price-fixing.

The future of laws prohibiting rent-setting algorithms remains uncertain. In September 2026, a federal judge temporarily blocked enforcement of part of New York's law in a case brought by RealPage (a company that provides the algorithms), expressing concern that New York’s prohibition might restrict use of publicly available information. This concern shouldn’t exist for Montgomery County’s law, however, since its restriction only applies to non-public information.  

For landlords with properties in several jurisdictions, the result is a patchwork of laws with different definitions, exceptions, and enforcement provisions. So, a pricing program that can be used for one building might be prohibited for another a few miles away.

What This Means for Landlords

Montgomery County Landlords may need to return to decades-old practices, such as market surveys, online listings, and secret shoppers, to set rents. In effect, the new laws may force landlords and property managers to reinstate practices used before computerized data aggregation and revenue management systems became available.

A property manager wants to know what competing properties are charging for two-bedroom apartments can check the property’s website. They also may be able to contact leasing offices posing as a prospective tenant and ask about rents, amenities, fees, and concessions. 

But landlords shouldn’t assume that market research is lawful just because it doesn't involve an algorithm. While independently collecting information available to all prospective tenants might be acceptable, landlords who exchange pricing, lease term, and occupancy information with competitors risk running afoul of antitrust and other laws. To that end, landlords shouldn’t assume that using a data service is okay just because the information is aggregated and anonymous.

Conclusion

When I tried to find new music, the algorithm got in my way. Because I didn’t want computer-generated recommendations, I had to use the old-fashioned search function, research top 100 lists, and read articles about trending songs.

Landlords and property managers may need to do something similar and revert to 20th-century pricing research and strategies – skills that younger individuals may have to learn anew. The laws also require that landlords ask questions as they research data because they’ll need to know the age of historical data and where it came from to prevent running afoul of the laws.

Technology can make market research faster and easier, and algorithms can process that data and make rent recommendations more quickly than a property manager could do on their own. While the ability to pivot to respond to rapidly changing market conditions might be attractive, using algorithms or non-public data to make rental decisions is increasingly being overtly outlawed. Even where there aren’t laws specifically prohibiting use of non-public data, using that data may be violate existing antitrust and other laws.

© 2026 by Elizabeth A. Whitman

Any references to clients and their legal situations have been modified to protect client confidentiality.

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