Artificial intelligence is gaining traction among institutional real estate investors, but fragmented data systems remain a major obstacle to broader adoption, according to a new survey from AI-powered investment software provider Dealpath. The survey of 100 institutional investors found that every respondent has either already adopted or plans to adopt AI, yet 93% reported encountering barriers along the way.
Dealpath said the findings indicate that AI in commercial real estate is “rapidly moving beyond experimentation.” Many firms initially turned to the technology to automate repetitive, document-heavy work, but interest is shifting toward more advanced applications such as underwriting, modeling and deal scoring.
The study’s methodology noted that 80% of surveyed firms manage at least $1 billion in assets, and roughly two-thirds of respondents held executive roles. Among those surveyed, 43% said they use generative tools such as ChatGPT for simple tasks, while 8% are exploring new AI-powered investment use cases. Thirteen percent are piloting custom tools designed to streamline CRE investment processes, and 36% are scaling AI solutions across their organizations.
Strengthening data systems emerged as a top priority, with 98% naming it among their key objectives over the next 24 months. Nearly three-quarters (74%) already have AI governance policies in place, while 36% cited data centralization as a major challenge.
Despite the optimism, most investors face implementation hurdles. According to Dealpath, 43% said their teams lack internal expertise, 42% pointed to regulatory and compliance challenges, 39% struggled with budget constraints and 36% cited decentralized data as a barrier.
Expectations for AI returns varied but shared a common theme of efficiency. Sixty-one percent of respondents hoped to see faster deal evaluation and closing, another 61% sought overall efficiency gains, half expected improved underwriting accuracy and 43% anticipated higher deal velocity — all outcomes that could help firms redirect time and resources toward new revenue opportunities.
As for current use cases, 67% of respondents said they were applying AI to document analysis, 61% used it for portfolio monitoring, 56% for investment memo creation and 49% for extracting information from offering memorandums and flyers.
Dealpath noted that understanding AI’s role in the industry requires viewing it as a broad category encompassing many existing technologies. Software providers have integrated various forms of AI into analytics and automation tools for years, even if not explicitly labeled as such. The distinction between traditional AI and newer generative systems like ChatGPT or Claude can obscure just how much AI technology is already embedded in real estate operations.
According to Dealpath, the essential goal is not to adopt AI for its own sake but to select tools that advance business outcomes. Without that alignment, even the most sophisticated technology risks becoming another layer of complexity rather than a source of strategic advantage.
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