CRE firms love AI but few are using it in production

A new Teammate AI field report found strong enthusiasm for artificial intelligence across 17 midsized commercial real estate firms, but only five had moved beyond chatbots and copilots into production workflows. The findings suggest CRE leaders see clear automation upside in underwriting, reporting and operations, yet most firms still lack ownership, governance and measurable ROI.

Why it matters: - Commercial real estate firms are talking about AI, but most are not yet using it to change day-to-day work. - The gap matters because the biggest opportunities sit in repetitive, high-friction workflows that affect underwriting, reporting, leasing, property management and investor communication. - The report suggests competitive advantage may go to firms that operationalize AI first, not the firms that discuss it most.

What happened: - Teammate AI released AI in CRE: The Peer Intelligence Report, a field report on how 17 midsized commercial real estate firms are approaching AI. - Respondents rated AI an average priority of 8.5 out of 10 over the next 12 months. - Only 30% of the firms reported production use beyond general-purpose chatbots and copilots. - The report includes five anonymized firm stories showing different adoption patterns across owner-operators, investment managers and larger platforms.

The details: - One lean owner-operator had already deployed multiple live workflows using mostly off-the-shelf tools. - A smaller investment manager connected underwriting, document review, investment committee preparation and reporting. - Another firm had broad employee experimentation but no formal initiative, governance model or firm-level ROI measurement. - A larger integrated platform remained mostly at the chatbot and copilot stage. - Ryan said smaller firms can move quickly when they focus on a specific workflow and that operating ownership and focus drive adoption more than budget. - Of the 17 firms surveyed, 15 were interested in finance or reporting automation. - Fourteen firms identified opportunities in property management, asset management, leasing or internal operations. - Thirteen firms prioritized some form of deal-execution automation. - Common targets included recurring financial reporting, data reconciliation, budget-to-actual analysis, portfolio performance reporting, lease-obligation tracking, invoice processing, work-order triage, investor communications and administrative workflow coordination. - Leadership posture was strongly associated with whether a firm launched an AI initiative. - Ten of the 13 firms whose leaders described AI as strategic or actively encouraged adoption launched an initiative. - Launching an initiative did not guarantee results, and just over half of the firms with an initiative reported clear or strong returns in at least limited areas. - The report found acquisitions, underwriting and due diligence among the strongest areas of interest. - Thirteen firms identified at least one of those transaction stages as an automation priority, and nine firms selected two or more stages. - Executives flagged potential automation in extracting data from offering memoranda, rent rolls, leases, T12s and data rooms. - Other opportunities included normalizing deal information, populating approved underwriting inputs, flagging missing or inconsistent material information, supporting market research and comparable-property analysis, drafting investment memoranda, assembling investment committee materials and tracking due-diligence handoffs. - The report also notes reviewing legal and compliance documentation as part of the workflow opportunity set. - Ryan said one major opportunity is connecting the full deal workflow from OM, rent roll and T12 intake through underwriting, diligence and investment committee review while keeping assumptions, exceptions and investment judgment with humans. - The report includes detailed findings, charts, workflow examples, anonymized firm profiles and an executive action framework. - Teammate AI said the report is meant to help organizations identify, design and operationalize AI and automation opportunities. - The company also said its work focuses on turning emerging technology into practical, controlled workflows that improve capacity, decision-making and operating performance. - The report is available at Read the report. - Teammate AI’s social post is available at LinkedIn post.

Between the lines: - The findings point to a familiar enterprise pattern: enthusiasm arrives fast, but workflow redesign, governance and measurement lag behind. - The most important barrier does not appear to be awareness of AI use cases; it is execution discipline. - The results also suggest smaller firms may have an adoption edge when decision-making is tighter and workflows are easier to change.

What's next: - The report points CRE leaders toward a practical next step: pick one workflow, assign ownership, connect the needed systems and measure whether throughput, errors or bottlenecks improve. - Firms that can move from pilots to repeatable operational use may capture the earliest gains in deal execution and back-office automation. - Teammate AI is positioning the report as a framework for firms that want to move from experimentation to controlled deployment.