According to HousingWire, leaders from two major MLS systems are pushing the real estate industry to fundamentally rethink how it governs data in an age of artificial intelligence. The challenge they're facing is that current MLS governance relies mainly on contracts, which become almost impossible to enforce once data leaves the system and gets used by AI tools. Tim Dain, CEO of NorthStar MLS, and Art Carter, CEO of California Regional MLS, say the industry needs to build what Dain calls an "orchestration layer" that tracks who is using data, what they're using it for, where it shows up, and under what terms.
The real pressure is coming from brokerages themselves, who want much more visibility and control over their own data contributions. Carter points out that as brokerages experiment with different AI tools and business models, they're increasingly frustrated by one-size-fits-all MLS policies. The two leaders have been working together for about 16 months on solutions that would let MLS systems manage data rights at a much more granular level, moving beyond simple role-based access to systems where permissions can be set field by field and record by record.
What makes this especially urgent, Carter notes, is that brokerages are already uploading MLS data into AI tools like Claude with essentially no oversight. Rather than try to lock down these tools entirely, Carter believes MLSs need to create frameworks where brokers can use AI responsibly while protecting the underlying data. Dain's vision includes a policy engine that could incorporate federal requirements like fair housing law, state rules, MLS policies, and individual brokerage requirements all in a way that machines can actually enforce automatically.
The stakes are substantial because the current cooperative MLS model depends on brokerages being willing to contribute their data freely. Carter warned that if brokerages lose confidence in how their data is protected and governed, they may simply stop contributing it to the system. He also raised a concern that resonates across the whole industry: if real estate companies don't establish proper governance now, they risk eventually having to buy back intelligence and insights that were generated from their own data in the first place.
Dain has proposed a future model where the economics of the MLS system itself change to reward contribution and charge for extraction. In this vision, a brokerage that uploads a full listing with broad distribution rights would earn more credit than one uploading comparable sales data after a closing. Over time, this approach could apply to leads, buyer information, and other datasets flowing through the housing ecosystem, creating incentives that keep everyone motivated to share rather than hoard.
What I am seeing locally in the Bay Area and across the East Bay is that brokerages are already experimenting with these tools whether the MLS systems are ready or not. Fremont and Oakland agents I work with are curious about how AI can help them analyze market trends and manage their data more efficiently, but they're also understandably worried about what happens to their proprietary information. Getting this governance right now will determine whether AI becomes a tool that benefits the whole market or a way for big tech companies to profit from data that local brokers spent years building.
