MLS leaders: AI demands new real estate data governance

Key facts

• MLS leaders Tim Dain and Art Carter believe AI necessitates a new approach to real estate data governance.
• They advocate for an "orchestration layer" for data authentication and utilization, moving beyond traditional control.
• Brokerages desire greater control and granularity over how their contributed data is used.
• Current MLS systems often lack the infrastructure for such granular control.
• A "charge for extraction, reward for contribution" model is proposed to incentivize data sharing.
• MLSs are increasingly viewed as data companies responsible for managing information, especially with AI agents acting on behalf of users.

Leaders from two of the largest Multiple Listing Services (MLS) in the U.S. have stated that the rise of artificial intelligence requires a fundamental rethinking of how real estate data is governed.

Tim Dain, CEO of NorthStar MLS, and Art Carter, CEO of California Regional MLS (CRMLS), discussed the issue at HousingWire's AI Summit, highlighting the need for greater transparency and control for brokerages over the data they contribute to MLS systems. They emphasized that the goal is not absolute control but rather establishing an "orchestration layer" that ensures proper authentication, entitlements, and utilization of data, especially as AI agents increasingly act on behalf of users.

Carter noted that many MLSs currently lack the infrastructure to provide the granular oversight that brokerages are demanding. Both executives acknowledged that MLSs are evolving into data companies and must adapt their policies to accommodate diverse business models and AI strategies. Dain proposed a policy engine that can incorporate federal, state, and brokerage-specific rules, making them machine-readable and enforceable.

A significant concern raised is that if MLSs fail to address these governance challenges, brokerages may become unwilling to contribute their data, which is considered vital to the entire housing ecosystem. To incentivize contributions, Dain suggested a "charge for extraction, reward for contribution" model, where users who extract significant value from the data would pay more, with funds potentially redirected to those who contribute data.

Both leaders stressed that this is not a future problem but a current one, with Carter citing instances of brokerages uploading MLS data into AI tools like Anthropic's Claude without any governance. They believe that improved governance is essential for enabling innovation safely and at scale, allowing wider access to data while ensuring compliance and protecting the integrity of the information.