In a previous piece, we explored how AI in real estate is moving beyond experimentation and into execution. The industry is no longer asking whether AI matters, but how to actually make it work.
According to The Appraisal and Keyway’s recent AI Adoption Survey, while nearly half of real estate firms are actively piloting AI, less than 10% have deployed it at scale. The gap is no longer about intent. It’s about execution. And increasingly, the firms that are closing that gap share a common characteristic: They understand the value of organized and normalized data.
From Adoption to Execution—and What Comes Next
The first wave of AI adoption in real estate was defined by experimentation. Firms tested tools, explored use cases, and ran pilots across underwriting, leasing, and asset management.
The next phase is about execution, and how AI is being embedded into workflows and used to drive real outcomes. But as firms move into this stage, a new limitation becomes clear.
Even when AI is deployed, results vary significantly. Some organizations see measurable improvements in speed, accuracy, and decision-making. Others see minimal impact.
The difference is in how companies tackle and execute on the solution.
Why Data Readiness Is Emerging as a Key Advantage
Real estate has always had access to data: Leases, rent rolls, operating statements, market reports. The issue has never been availability, but usability.
Much of this data remains fragmented across PDFs, spreadsheets, emails, and legacy systems. With the wrong AI tool, the problem is worsened by hallucinations and non-repeatable outcomes. Then, the result is predictable: Limited impact to the organization.
As Eglae Recchia, CEO of Keyway, explains: “AI is only as powerful as the data used to run it. If your data is fragmented or incomplete, your decisions will be too. Being data-ready means moving beyond raw data to connected, structured, and usable information; data that can actually support decision-making and scale across workflows”.
Data Alone Doesn’t Create Value—Workflows Do
Understanding your data and how to leverage it is just step one.
Many firms have made progress in organizing data, yet still struggle to translate it into faster or better decisions. The missing link is the ability to act on it efficiently.
This is where embedded workflows become critical.
AI delivers real value when it is not treated as a standalone tool, but as a workflow layer: Integrated directly into how teams work across commercial real estate, sourcing deals, executing on loans, and building relationships.
Instead of generating insights that sit in dashboards or reports, AI becomes part of the operational fabric: Reading documents, structuring data, triggering analyses, and informing decisions in real time.
“The real shift isn’t AI as a tool, it’s AI embedded in workflows. Before we were about taking data and building insights. We are now moving from building insights to executing on outputs. That’s when you move from ideas to action”, explains Recchia.
The Cost of Not Being Ready
Teams continue to spend weeks reconciling information across documents, underwriting often relies on incomplete or outdated inputs, portfolio risks are identified only after performance declines, and opportunities are missed because they are not visible early enough.
In a slower, more stable market, these inefficiencies were manageable. In today’s environment, defined by volatility, tighter capital, and increased competition, they are not.
Firms that are not leveraging technology such as Keyway are not just slower, they are operating with less visibility, less precision, and ultimately, more risk.
A New Layer of Competitive Advantage
Historically, competitive advantage in real estate came from relationships, local expertise, and access to deals. Those factors remain important.
But they are no longer sufficient on their own.
Today, advantage is increasingly defined by a combination of data readiness, workflow integration, and the ability to operationalize AI at scale.
Firms that bring these elements together are able to identify market shifts earlier, underwrite with greater consistency, detect risks before they materialize, and allocate capital with more confidence.
This changes the nature of competition—from who has access to information, to who can act on it first.
The New Divide
As AI adoption continues to grow, the industry is entering a new phase, and the divide is no longer between firms that are using AI and those that are not. It’s between those that have built the operational foundation to support it—and those that haven’t.
Two firms can deploy similar technologies and achieve very different outcomes depending on how their data is leveraged, how workflows are designed, and how their teams adapt to change.
That’s why the real divide is no longer technological; it’s operational.
Final Thought
Real estate has always been about making better decisions faster and with more conviction.
What’s changing is how those decisions are made.
The first phase of AI in real estate was about experimentation. The second is about execution. The next phase is about infrastructure—building the data and workflow foundations that allow AI to scale.
Being data-ready is becoming a critical part of that foundation. The firms that lead will be those that combine data readiness with embedded workflows and operational execution—turning information into action, and action into results.
Because ultimately, AI doesn’t create value on its own. Execution does.