Comfort and Trust – May 18, 2026
Commercial real estate’s rapid adoption of artificial intelligence doesn’t mean the industry is fully acclimated to using it
What happens when the technology of the future comes to an industry that historically has been slow to adopt new technologies? Call it growing pains, and a couple of recent studies suggest that while commercial real estate firms have moved to embrace artificial intelligence, they’re keeping it at arm’s length.
We reported last week on a survey conducted by the National Association of Real Estate Investment Managers which found that although institutional real estate has made AI a front-burner priority, implementation is still a question mark. “Everyone agrees AI matters,” NAREIM says in an executive summary of the study. “Almost no one feels ready for it. That tension shows up in nearly every section of this survey.”
Few of the 72 investment managers surveyed by NAREIM and Juniper Square cited technology access as the issue, since the tools are already available. A recurring theme was governance and data quality, followed by talent and culture. “These are organizational problems, not technology problems, and they are a lot harder to fix than buying another piece of software,” says NAREIM.
Conversely, another new study suggests that technology may be the root of the problem. A survey of 255 CRE professionals across brokerage, lending and capital markets, development and asset management, conducted by First American Data & Analytics and DealGround, found that 66% of respondents use AI weekly or daily, but only 5% trust it enough to inform decision-making on deals.
The findings suggest that although AI adoption is accelerating, trust remains the barrier between experimentation and workflow transformation. Fifty-three percent of respondents said they use AI for support only and exclude it from final decision-making, while another 17% say they use it only with heavy verification.
Open-ended responses from survey respondents illustrate this trust issue. “The data that AI pulls its answers from is not vetted by me, therefore I cannot validate the accuracy of the information without doing my own research,” said one respondent. Another commented, “No matter how many times I told it to only pull accurate information from the lease, it would still put inaccurate numbers, make assumptions, and change information.”
First American Data and DealGround say these concerns point to a broader challenge facing AI in commercial real estate: “many CRE workflows depend on explainability, provenance and defensible outputs. Unlike lower-risk consumer applications, commercial real estate professionals often work with fragmented historical data, unstructured documents, and legacy systems where even small inaccuracies can create significant operational or financial consequences.”
The result is that many firms appear to be moving cautiously toward AI implementation rather than fully automating strategic workflows. “The market is not rejecting AI technology outright — it is pressure-testing whether current AI systems can consistently produce reliable, auditable outputs using relevant data across complex real estate operations,” says the First American/DealGround study.
“Brokers will adopt tools that fit how they actually work, but they will not stake a deal on outputs they don’t trust,” said Dan Mosher, CEO and co-founder of DealGround. “The next phase of AI in CRE will go beyond answering questions to help professionals execute inside real workflows.”
Fair enough. However, there may be another factor to consider. The market knowledge that a broker or investor carries around may be the glue that holds the fragmented data together when structuring transactions. It may be that AI systems at present require more straightforward input from users who understand how to speak the systems’ language, and that the 5% of survey respondents who use AI in decision-making have cracked that code. Communication, after all, is a two-way street.