- A new survey from First American Data & Analytics and DealGround found 66% of CRE professionals use AI weekly or daily, but only 5% fully trust it for real-world decision-making.
- Current AI adoption is concentrated in lower-risk workflows like market research, lease abstraction, and marketing, while demand is growing for transaction automation and reliable comps.
- The findings suggest CRE’s next phase of AI adoption will depend less on awareness and more on trusted data, workflow integration, and output accuracy.
Commercial real estate has embraced AI faster than many expected, but the industry still isn’t ready to hand over critical decisions to machines.
A new survey from First American Data & Analytics and DealGround found that 66% of direct CRE respondents now use AI weekly or daily, yet only 5% say they fully trust AI enough to influence real estate decisions. The report, based on responses from 255 CRE professionals, paints a picture of an industry actively experimenting with AI while keeping humans firmly in control.
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Adoption is happening at the top
AI usage is no longer limited to junior analysts or marketing teams. According to the survey, 75.9% of VP-level and higher respondents use AI weekly or daily, signaling that adoption has reached senior leadership ranks.
Still, the report found most firms treat AI as a support tool rather than a decision-maker. More than half of respondents said they use AI for workflow assistance only, while another 17% said they rely on “heavy verification” before using AI-generated outputs in decisions.
“The industry is not struggling with whether to adopt AI — it is struggling with how to use it effectively,” said Matt Key, VP of Data at First American Data & Analytics. “AI is only as powerful as the data behind it.”
The details
The survey identified market research and comparable analysis as CRE’s leading AI use case, accounting for 20% of responses. Lease abstracting and document review followed at 15.3%, while marketing and presentation support represented 13.7%.
“AI is great for sorting through big data sets — like looking for properties that meet your criteria, extracting data from leasing docs, and market research like comps and ownership information,” said Dan Mosher, CEO & Co-founder of DealGround. “AI is moving from answering questions to doing more deal work.”
Underwriting and financial modeling remain less common, reflecting the industry’s reluctance to trust AI in higher-risk workflows. The report also found that 31% of respondents said AI has not delivered meaningful time savings yet, though roughly 69% reported saving at least one hour per week.
Trust issues, not pricing, remain the industry’s biggest obstacle. Among non-extensive AI users, 34% said they don’t know which tools to use, while 32% cited concerns about output accuracy. Only 5% identified cost or unclear ROI as the primary barrier.
A data-quality problem
One of the clearest themes throughout the report is that CRE professionals see AI’s limitations as a data problem as much as a technology problem.
Respondents repeatedly cited concerns around stale records, inconsistent property data, missing legal references, and unverifiable outputs. The report argues CRE’s next phase of AI adoption will depend on standardized, continuously updated property data professionals can actually verify and trust.
That challenge becomes especially important in fragmented CRE markets, where incomplete comps data and inconsistent records already create friction for brokers, lenders, and investors.
Why it matters
The report highlights a growing divide between AI experimentation and operational trust inside CRE firms. While AI has already earned a role in research, document handling, and marketing, the industry still hesitates to deploy it in workflows tied directly to valuation, underwriting, or transactions.
That caution matters because CRE’s next wave of AI products is increasingly targeting transaction execution, underwriting, and operational workflows, not just productivity tools. In the survey, 33.3% of respondents said they most want AI to automate manual transaction and closing processes, while nearly 25% prioritized better rent and sales comps.
The findings also suggest the competitive edge may shift toward firms with cleaner, more standardized datasets rather than simply the newest AI tools.
What’s next
CRE’s AI adoption curve appears likely to continue climbing, particularly as vendors push deeper into transaction management, underwriting automation, and portfolio operations.
But the report suggests the industry’s next breakthrough won’t come from more chatbots or generic content generation. Instead, adoption may hinge on whether platforms can deliver transparent, verifiable outputs tied to trusted property data.
For now, AI remains firmly in the “co-pilot” phase across most of CRE. The technology is already embedded in day-to-day workflows, but until confidence catches up with adoption, humans will continue making the final call.
