I’m writing this from Marco Island, where leaders from MIAMI REALTORS®, RWorld and BeachesMLS have come together to plan for 2027 and beyond.
As I prepare to serve on the BeachesMLS Board in 2027, I’ve been thinking about what artificial intelligence means for an MLS organization—and, more importantly, what it can mean for the brokerages and agents we serve.
I don’t believe the objective should simply be to adopt more AI.
I think we have an opportunity to build something much more valuable: the infrastructure, safeguards, scrutiny and member capabilities necessary to help brokerages and agents use AI effectively and responsibly to build better businesses and better serve their clients.
Building the Foundation
We aren’t starting from zero.
The combined organization brings together AI initiatives and capabilities including Flexmls AI listing input, Sidekick, Infinityy AI and work around a custom MCP server that can create new ways for AI systems to interact with MLS data.
Those capabilities matter, but individual products will come and go. AI models themselves are changing extraordinarily quickly.
That’s why I believe the bigger opportunity is infrastructure.
If we build the right data architecture, permissions, integrations and systems, we don’t have to predict which AI model or application will dominate three years from now. We can build an organization capable of adapting as the technology changes.
That’s something I’ve heard Dionna Hall (Co-CEO) emphasize repeatedly. Dionna brings a strong technology background to her leadership, and I’ve appreciated her focus on building the infrastructure necessary to support what comes next.
The People Behind It
Technology alone won’t determine whether this works.
I’ve worked with Kim Hansen (COO, Beaches/RWorld) since serving on the BeachesMLS Joint Task Force representing JTHS following the dissolution of Regional MLS. Kim has been terrific to work with, and I’ve developed a real appreciation for the operational work required to turn ideas into systems that serve brokerages and agents.
I’ve also really enjoyed getting to know Greg Manship (MLS & Data Integrations) and the breadth of MLS technology experience he brings. Greg recently invited me to participate in the BeachesMLS MCP server pilot project, something I’m particularly excited about. It gives me an opportunity to explore firsthand how AI can interact with authoritative MLS data—and how brokerages and agents might ultimately put that capability to work.
My conversations about AI with Evian White De Leon (COO, MIAMI REALTORS®) go back more than a year, well before the merger. We’ve had an ongoing dialogue about where AI is headed and how we find the right solutions to serve the membership. I’ve particularly appreciated her willingness to explore what’s possible while also asking the harder questions that come with these technologies.
I also have tremendous appreciation for Teresa “TK” King Kinney (Co-CEO)—not only for her many years of leadership, but for the ongoing support and encouragement she has given me personally. I’m grateful for the opportunities she has provided me to contribute, learn and become more involved over the years. I’m also grateful for Michael Curiel and Woodly Cherizol (MIAMI MLS) and the knowledge and experience they bring.
The combination of these organizations brings those perspectives and capabilities together. That’s a significant opportunity.
AI Needs Scrutiny
One subject I care particularly deeply about is scrutiny.
AI is extraordinarily capable, but it also has a tendency to try to be helpful—to give us an answer.
Sometimes the right answer is: We don’t know. Or: The data doesn’t support that conclusion.
As AI becomes easier to use, getting an answer isn’t necessarily the difficult part. Determining whether that answer deserves to be trusted is.
To me, scrutiny means more than checking whether a number is correct. It means questioning the underlying data, methodology and assumptions. It means looking for bias, considering Fair Housing implications, understanding the source of the information and making sure MLS rules, brokerage policies, privacy requirements and other obligations are respected. And it means knowing when human judgment needs to take over.
I apply the same standard in Why I’m Building an AI Brain. The question of whether clients can find and verify that expertise also shapes AI Search Is Changing What It Means to Be an Authority in Real Estate.
The industry also appropriately talks about AI guardrails. We need them. But guardrails and scrutiny aren’t quite the same thing.
Guardrails establish boundaries. Scrutiny teaches us to question what happens inside those boundaries.
At the scale of approximately 94,000 members, no organization can anticipate every question someone might eventually ask an AI system. We need both.
From AI Access to AI Capability
The other enormous opportunity is education.
Not every member will want to become deeply involved with AI. They shouldn’t have to. But for those who do, I would like us to help create a path to becoming exceptionally capable.
That means going beyond better prompting. It means helping brokerages and agents use AI to understand markets, analyze MLS data, prepare for listing appointments, identify opportunities, improve client communications, work with their own information and automate repetitive tasks.
And it means teaching them to recognize when the data is inadequate, when an assumption needs to be challenged, when Fair Housing or compliance deserves additional scrutiny, and when they shouldn’t trust the answer AI has produced.
My hope isn’t simply that our members use more AI. It’s that the members who choose to use it become exceptionally good at it—and translate that capability into stronger businesses and better service to their clients.
Why the MLS Matters Even More
AI may actually make the MLS more important, not less.
AI increases the value of trustworthy data.
The large AI models know an extraordinary amount, but they don’t independently possess everything an MLS organization does: authoritative local real estate information, rules governing its use, historical context and relationships with the brokerages and agents who create and maintain that information.
We don’t need to compete with the companies building the world’s largest AI models. We need to make sure our data and infrastructure can work effectively with whatever technologies emerge.
That’s why I believe the BeachesMLS MCP project could be particularly important. The opportunity isn’t simply MCP itself. It’s the larger idea of creating secure, governed ways for AI systems to work with authoritative MLS information while preserving the permissions and data integrity that make that information valuable.
Looking Toward 2027
I don’t pretend to know what AI will look like at the end of 2027, much less five years from now. None of us does.
That’s precisely why the foundation matters.
My hope is that BeachesMLS continues building the infrastructure necessary to support what comes next; develops thoughtful safeguards and a culture of scrutiny around accuracy, methodology, bias, Fair Housing and professional responsibility; and gives interested members the education and tools they need to develop meaningful AI capabilities.
We have the technology. We have valuable MLS data. And we have people with deep experience in technology, operations, MLS systems, law, compliance and member service.
Now we have an opportunity to bring those pieces together.
Success won’t ultimately be measured by how many AI products we’ve adopted. It will be measured by what our brokerages and agents are able to accomplish with them—and whether we’ve helped them develop the judgment to use them well.
That’s the work I’m excited to be part of in 2027 and beyond.