Will Federal Ai Regulations Override State Housing Efforts?

President Donald Trump’s new executive order that creates a single federal framework for artificial intelligence (AI) is reverberating throughout the housing industry.

While states have been moving to regulate AI tools used in home pricing, marketing, tenant screening and mortgage decisions, the new order asserts federal authority over AI regulation.

The Department of Justice (DOJ) has also been instructed to challenge state laws deemed inconsistent with federal policy. Supporters say the move will simplify compliance and accelerate innovation, while critics argue it could weaken state-level safeguards aimed at transparency and consumer protection in housing.

A large source of debate is tied to how real estate data — particularly multiple listing service (MLS) data — is used to train and power AI systems, and who is accountable when these systems shape pricing, negotiations or consumer outcomes.

Sam DeBord, CEO of the Real Estate Standards Organization (RESO), emphasized the complex environment that agents, brokers and MLSs already operate within — with or without new AI-specific laws layered on top.

He said that being ready for the regulations that come next starts with understanding how MLS licensing works and who ultimately controls compliance.

“Real estate agents get licensed to use MLS data through their relationship with their brokerage, which is the participant in the MLS,” DeBord said. “So all of these parties are bound by the license that the MLS grants to advertise the clients’ listings according to those rules.

“They should all be monitoring where that data is used. It’s usually the MLS that’s responsible for compliance measures if its data is being used outside of the license terms.”

This structure matters as AI developers increasingly seek large, standardized datasets. DeBord said a national approach to AI oversight could, in theory, reduce confusion.

“Reasonable, consumer-centric, standard regulation across the country could bring a lot of efficiency for professionals and home buyers and sellers, as opposed to fragmented laws across states,” he said.

State AI laws meet federal preemption

Over the past two years, states have taken the lead on AI regulation — particularly where automated systems intersect with housing and credit.

Colorado enacted a law that treats AI used in housing and lending as “high-risk,” requiring impact assessments and consumer disclosures.

New York lawmakers have advanced bills targeting algorithmic discrimination in housing and credit decisions. Other states have adopted narrower measures focused on transparency or government use of AI.

Trump’s executive order threatens to override much of that work. It establishes a national policy favoring fewer restrictions, and it creates an AI Litigation Task Force within the DOJ to legally challenge state laws.

Mortgage industry trade groups, including the Mortgage Bankers Association (MBA), applauded the order, arguing that compliance with dozens of state AI laws would be costly and confusing.

“MBA welcomes President Trump’s executive order on AI and appreciates the Administration’s focus on establishing a clear, nationally consistent framework for emerging technologies,” Bob Broeksmit, the MBA’s president and CEO, said in a statement.

“Technology does not stop at a state border. We believe strongly that a unified federal approach is necessary to avoid a confusing patchwork of state laws and regulations that would stifle innovation and raise compliance and borrower costs.”

Housing advocates counter that states moved first precisely because federal law has not kept pace with rapidly evolving AI tools. Recent legislative pushes follow closely behind DOJ litigation against real estate software firm RealPage.

Federal prosecutors — joined by state attorneys general — sued RealPage during the Biden administration, alleging its property management software enabled landlords to coordinate rent pricing.

The case continued under Trump’s DOJ, with a settlement announced in November that will bar the company from using nonpublic data to set rents.

Opaque models and market accuracy

Beyond legal authority, industry experts say poorly regulated or opaque AI models can distort the very metrics agents and consumers rely on — pricing accuracy, days-on-market projections and automated recommendations used in negotiations.

DeBord said data quality and standardization are central to avoiding these pitfalls.

“Standardized data can help any technology system better understand and leverage the data it has access to,” DeBord said. “This is why we’re seeing international real estate data exchanges beginning to arise, using RESO standards as the interchange, or the universal language, to move between geographies and human languages.”

He said the industry’s long-term priorities should remain clear, regardless of the regulatory framework.

“The North Stars for real estate data companies should be transparency, accuracy and comprehensive data,” DeBord said. “The real estate industry has been opening up its data significantly over the past 20 years, with the vast majority of the data consumers need being available on the open web. Zillow‘s Zestimate is the best-known consumer pricing estimate, and it’s been around for 20 years.”

AI-driven estimates are not new, he added, but their influence is growing.

“AI companies will continue to explore new ways to make predictions with transaction data, and it’s important that agents, brokers, and MLSs can continue to provide the primary source of truth to the industry and its consumers to help technologists provide better products,” DeBord said.

“Those that produce poor results in their estimates and recommendations will be exposed by the market, as they have been in the past.”

Third-party AI tools and broker risk

Many agents and brokers rely on third-party platforms that use AI for lead generation, pricing guidance, marketing copy or negotiations insights.

If these tools later face legal or regulatory scrutiny, brokers may still bear reputational or legal risk. DeBord said professionals cannot outsource their core duties to software.

“It’s important that agents and brokers continue to keep their fiduciary and statutory duties to their customers and their profession top of mind,” he said. “There’s a bright line between business recommendations and legal advice — the latter of which should not be taken from an AI system.

“If the professionals can be transparent about where they are getting the information they’re using to make marketing and negotiation decisions, they can have transparent conversations with their customers who, at the end of the day, make any final decisions for their transactions.”

He cautioned against treating AI-generated insights as a substitute for experience.

“Web search advice is no replacement for a seasoned professional who has facilitated the process for years and knows the fallacies of pop culture about real estate that are likely to put a client in a bad position,” DeBord said.

Contracts, data standards and disclosures will play a growing role in clarifying responsibility as AI tools proliferate, he added.

National rules versus state complexity

Supporters of Trump’s order argue that a single federal standard will simplify compliance for brokers operating across markets. DeBord acknowledged this appeal, noting that real estate is already fragmented by local rules.

“Today there are 500 MLSs with different rules across the U.S.,” he said. “This is already a confusing business landscape for brokers to manage. Different AI laws in 50 states could make for an even more complex, fragmented market for agents, brokers and their clients to work within.”

And complexity carries real costs, he added.

“It would make the process of marketing more expensive and cumbersome,” DeBord said. “Real estate agents usually list about 200 different activities involved in listing and selling a property. Many work across state lines, so interstate complexity is not a welcome idea.”

Still, he emphasized that federal preemption is not automatically beneficial.

“Of course, the devil is in the details of getting the federal regulations right,” DeBord said. “But that’s the ideal place for regulation in terms of creating opportunities for innovation and clear, understandable protections for consumers.”

Transparency and trust

At the transaction level, agents are often expected to explain and defend pricing, marketing and negotiation strategies to clients. As AI plays a larger role in shaping these strategies, transparency becomes critical to maintaining trust.

DeBord said both consumers and professionals must be able to question AI outputs.

“The open, free web is a benefit to both consumers and professionals,” he said. “Both should be able to investigate and question the best options for their real estate dealings. With new AI platforms, there is faster access to more information, which is good.”

But speed and scale can also amplify errors.

“It’s also important that these platforms directly document their information sources and efficiently allow access for users to verify them,” DeBord said. “We’ve seen billion-dollar companies’ products create falsified quotes from famous people out of thin air.”

Verification is essential as AI-generated summaries and recommendations become more common, he added.

“While these systems’ synopses of data on the web are sometimes very useful in an AI (large language model) context, verifying the source data will be critical to ensuring that real estate consumers can trust the decisions they’re making based on AI systems’ recommendations,” DeBord said.

For agents, brokers and MLSs, an unsettled landscape remains. Federal preemption could reduce regulatory fragmentation, but it could also remove state-level guardrails that many see as essential to responsible AI use in housing.