)
Artificial intelligence deployment in commercial real estate is widespread, with approximately 90% of companies using the technology in some form. But how many can confidently quantify its impact?
According to JLL’s 2025 Global Real Estate Technology Survey, after implementing AI, only 5% of those surveyed reached their expected goals.
This stark contrast is something that has plagued the CRE industry, said Reeves Davis, JLL’s president of technology solutions. Companies get excited about AI and rush to get a shiny product over the finish line. But when it comes to the efficacy of the product itself, things can fall short.
“It’s been really interesting to watch the flow and how people’s expectations change in this space,” Davis said. “It mirrors plenty of cycles and other trends that we see in technology. When there are super high expectations, you’re met with a slight decrease in excitement when reality hits, and then you have to determine what value is actually being created.”
One reality the industry is confronting, Davis said, is that generating, or creating, software isn’t the same thing as maintaining it.
Data is the key differentiator between what makes or breaks an AI program, he said. Enthusiasm for the technology itself is one thing, but having the data that gives companies a leg up on the competition and allows them to efficiently act on their ideas is where the real unlock happens.
“You need data at scale,” Davis said. “You need to be able to see across the entire industry of what's going on. Otherwise, every organization is trying to roll their own intelligence into a platform, and when all they see is their own portfolio, it's a far more limited scope.”
Every company goes through a phase of experimentation, Davis said. What can they do that’s the most novel? How can they fill a gap, either within their own operations or solve for a broader market gap?
Recognizing that many companies are either trying to build out their own proprietary AI platforms or to deploy systems like Anthropic’s Claude, OpenAI’s ChatGPT or Google’s Gemini, Davis said the most important thing to remember is to set goals, track progress and understand return on investment.
And while some ideas will succeed and some won’t, accepting the fact that a normal cycle of experimentation does have some waste is crucial, Davis said. There is some expectation of failure, but learning from that failure makes that experience worthwhile.
“The cycle is so fast,” he said. “The speed of it is faster than anything we've ever seen before. The introduction of the internet or cellphones was a massive change to our culture, but they took years. We're looking at cycles that operate in months or even weeks now.”
In addition to the fact that building out proprietary AI platforms is typically difficult, it is capital- and time-intensive, Davis said. Rather than spending time building these systems natively, companies should focus on their core mission — and leave the development and management of AI infrastructure to firms whose main focus is delivering these capabilities.
“For example, we don't build our own HR or finance software in-house,” he said. “I would argue that very few people do, and it's because someone else has an advantage that we can leverage.”
The benefits of AI, however, are clear-cut. It makes employees feel more productive during their workday, enabling them to analyze more quickly, broker deals with more precision and be more confident in decision-making. But this new speed to market that AI allows doesn’t remove the need for accountability, Davis said.
Put simply, if an AI platform isn’t producing results as intended or fails to include important information, who is to be held responsible?
Davis said companies hire JLL to help them create real estate outcomes, and technology is just a way to achieve those outcomes. Technology in and of itself isn’t the outcome.
“AI may make the process faster or more consistent, but ultimately, we still have a significant amount of humans in the loop that are taking that insight, taking that workflow and making a strategic decision,” he said.
Davis said companies that create value from AI will do a few things to set them apart from the rest.
First, they will be intentional about identifying and prioritizing high-value AI opportunities that resonate most with their business. They will then set achievable goals that they can execute as a company. This will likely call for investment in employee training to support companywide adoption, Davis said.
And as with any new business initiatives, there will be successes and there will be outcomes that fall flat. Davis said that is why it is crucial for companies to track their AI spending and the outcomes associated with their budgets.
“If they don’t embed accountability for AI cost and outcomes directly into their budgets, they risk investing in technology without a clear understanding of what it’s bringing to the business,” he said.
As AI matures, it should reach the point where a company’s AI strategy will become “indistinguishable” from its overall business model, Davis said.
Not only is AI here to stay, but it is going to be an essential part of how commercial real estate does business — and those who know how to leverage it effectively will have a competitive advantage.
“Companies need to think about where they have data at scale that can be used to achieve things that others cannot,” Davis said. “The reality is that we are tapping about 10% of the capability today of frontier models. While those continue to improve, there’s tremendous headroom to diffuse the use of AI throughout an organization.”
This article was produced in collaboration between JLL and Studio B. Bisnow news staff was not involved in the production of this content.
Studio B is Bisnow’s in-house content and design studio. To learn more about how Studio B can help your team, reach out to studio@bisnow.com.
)
)
)
)
)
)
)
)
)
)
)
)