MLS Leaders Call for AI-Driven Real Estate Data Governance

Leaders from two of the largest Multiple Listing Services (MLS) in the United States have called for a fundamental rethinking of how real estate data is governed, in response to the increasing influence of artificial intelligence. Tim Dain, CEO of NorthStar MLS, and Art Carter, CEO of California Regional MLS (CRMLS), articulated this need during a discussion at HousingWire's AI Summit. They emphasized that the current infrastructure for managing real estate data is insufficient for an AI-driven industry and that brokerages require greater visibility into how their contributed information is being utilized.

Dain clarified that the proposed shift is not about "control" but rather about establishing robust "governance." He suggested that the industry has sometimes been perceived as overly controlling, leading to frustration among users of MLS data. Instead, Dain proposed building an "orchestration layer" that can precisely identify who is accessing data, for what specific purpose, where it is being displayed, and under what agreed-upon terms. This layer would be built upon proper entitlements, authentication protocols, and clear guidelines for data utilization and deployment. This approach aims to move beyond the limitations of current systems, which often struggle to provide such granular insights.

Carter echoed Dain's sentiments, highlighting that brokerages are increasingly demanding more authority over the data they submit to MLS systems. He described the ongoing industry debates as "noise," but identified the core issue as brokers seeking enhanced control and granular understanding of their data's dissemination. This includes knowing precisely where their data is going, how it is being transmitted, and which specific elements are being shared. Carter noted that most MLSs currently lack the necessary infrastructure to offer this level of detail and transparency. CRMLS and NorthStar MLS have been collaborating on this challenge for approximately 16 months, indicating a significant, ongoing effort to develop solutions.

The impetus for this reevaluation stems from AI's growing capacity to access, analyze, and deploy real estate information in novel ways. As AI tools become more sophisticated, the ability to track and manage the flow of sensitive property data becomes paramount. The current MLS data models, largely designed before the widespread adoption of advanced AI, may not adequately address the complexities of AI-driven analysis and application. The leaders' call suggests a proactive approach to ensure data integrity, compliance, and broker confidence in a rapidly evolving technological landscape. The proposed governance model aims to foster a more transparent and accountable ecosystem for real estate data, benefiting both data providers and consumers of real estate information.