Why AI Changes the Clear Cooperation Policy Discussion

The relationship between AI technology and data fragmentation is unlike it was before.

The year is 2006 and I am moving to NYC after college. I begin visiting dozens of listing websites - brokerages, management companies, and a brand new site called StreetEasy to find a rental. Jumping around between them is not a great user experience and full of inaccurate data.

Before the advent of centralized listings platforms like Zillow and Trulia, consumers were forced to navigate numerous, individual sites each offering only a portion of the inventory available. As the industry has moved towards standardization of MLS and property data in general (thanks in no small part to the work done by RESO), data is more transparent today than ever, and as such, more aggregators exist today than ever.

The recent discussion around a potential repeal of the NAR’s Clear Cooperation Policy, a policy that governs how and when listings must be posted on the MLS, has many sides to it. Advocates for the repeal cite the current policy’s potential to erode consumer choice when it comes to how a transaction around their home should occur. Proponents of the policy believe it creates a transparent marketplace of information that democratizes access to both the consumer and agents.

These discussions, however, have yet to consider the role of how AI technology can emerge in a world where the Clear Cooperation policy is rolled back. To cut to the chase — the potential re-fragmentation of listing data threatens to undo years of progress, paving the way for unreliable, AI-native aggregator sites. In this landscape, the MLSs will remain as critical guardians of data integrity.

The Return to Data Fragmentation

The search process before listing aggregators emerged frustrated many buyers and sellers and also limited market transparency. Imagine a scenario where the industry reverts to this scattered state. There are a few reasons why this is a real possibility:

• Regulatory changes: there is active review of the Clear Cooperation Policy that is also happening against the backdrop of sweeping regulatory change concerning how commissions are advertised and received.

• Brokerage decisions: as has happened in the past, brokerages with scale may decide to withhold listings to gain a competitive edge in attracting unique consumer attention for its agents and listings, particularly in the luxury space.

• Listing Distribution: unlike in 2006, there are hundreds of thousands of individual agent websites that syndicate listing information to consumers.

We must believe that history will repeat itself. As in 2006, when the search portal boom began, consumer forces will drive innovation in listing data aggregation. If Clear Cooperation is rolled back, these marketplace forces will emerge again — but this time around will be different. An AI-native aggregator is a very different product than what began to emerge 20 years ago given all of the capabilities that LLMs and Assistants already have.

The Rise of Aggregator Sites

In a siloed data environment, a vacuum is created — one that is quickly filled by opportunistic, aggregator sites. In this light, the real estate industry faces a pivotal moment. The potential re-fragmentation of listing data, coupled with advances in AI technologies, is set to usher in a new era of loosely-governed aggregators.

Unlike traditional web scraping tools, modern AI algorithms can navigate complex websites, interpret unstructured data, and adapt to changes in real-time. These capabilities make data aggregation faster, more efficient, and harder to block. Given these advances, the emergence of new, AI-native aggregator sites is inevitable. It’s fundamentally the same way that the Large Language Models (LLMs) trained themselves in the first place on the corpus of the internet.

These aggregator sites will attempt to reduce consumer frustration, and at the same time put brokerages in a double-bind: the more effort spent on making it harder for an AI to access data, will in turn make it harder for the consumer as well.

The MLS: More Crucial Than Ever

An MLS’s role as a trusted source of data will be amplified in an AI-native aggregation future. MLS systems can safeguard the interests of consumers and agents alike. Consumers will also want an unified way to search across listings that may not be formally listed on the MLS. Any such system should solve this problem in tandem with the MLS, so that the most comprehensive dataset is available and shared standards of authentication and management are upheld.

Regardless of how the Clear Cooperation policy decision plays out, the ways in which consumers will search and find properties is going to be pushed further by AI-native applications that have unprecedented abilities to pull information from a number of sources with a fraction of the technical complexity it would have required even 5 years ago.

It’s important that policymakers take this into consideration when thinking through how information practically gets syndicated and consumed.

Thanks for reading this week’s Sidekick newsletter - it’s been so exciting to see the community interested in AI and Real Estate grow so quickly!

Michael Martin
Co-Founder/Co-CEO
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