What is the 2026 First American CRE AI trust gap? The 2026 First American CRE AI trust gap is the finding from a new survey by First American Data and Analytics and DealGround that 66 percent of commercial real estate professionals now use AI on a weekly or daily basis, but only 5 percent trust it enough to influence actual deal decisions. The 255-person survey, released in May 2026, is the first major data set to put numbers on a pattern that CRE technology consultants have observed for two years: AI is everywhere in the workflow, almost nowhere in the actual investment committee vote. For a comprehensive view of which AI tools are being used in CRE, see our pillar guide on the best AI tools for commercial real estate investors.
Key Takeaways
- 66 percent of 255 surveyed CRE professionals use AI weekly or daily; only 5 percent trust AI to influence actual deal decisions, according to the First American Data and Analytics and DealGround survey.
- The most common AI uses are market research and comparable analysis (20 percent), lease abstracting and document review (15.3 percent), and marketing materials (13.7 percent).
- Underwriting and financial modeling came in at 12.2 percent of primary uses, behind document review and marketing.
- Deal sourcing and property valuation remain marginal AI applications in CRE workflows in early 2026.
- The trust gap reflects an accuracy and verification problem, not a capability problem; frontier models like Claude Opus 4.7 and GPT-5.5 can do the work, but firms have not built the verification layer that would justify investment-committee-grade trust.
What the Survey Actually Measured
First American Data and Analytics partnered with DealGround to survey 255 commercial real estate professionals in early 2026 on their AI use, trust, and workflow integration. The headline finding (66 percent regular use, 5 percent decision-grade trust) is the largest data point yet on the production-to-trust gap that has been visible to anyone working in CRE technology.
The survey breaks down primary AI applications in the prior 90 days as:
- Market research and comparable analysis: 20 percent
- Lease abstracting and document review: 15.3 percent
- Marketing materials and presentations: 13.7 percent
- Underwriting and financial modeling: 12.2 percent
- Deal sourcing: marginal
- Property valuation: marginal
Note what is at the top of the list and what is at the bottom. The top of the list is information gathering and writing (low stakes, easy to verify, easy to throw away). The bottom is the activities where a wrong number changes the investment outcome (sourcing the wrong deal, valuing a deal wrong). The trust gap maps directly onto stakes.
Why the Trust Gap Is Rational
The 95 percent of CRE professionals who do not yet trust AI for decisions are not Luddites. They are responding to three realities:
1. Model hallucination remains real
Frontier models still hallucinate on 1.8 to 3.1 percent of CRE financial prompts, depending on the model. On a 1,000-prompt month, that translates to 18 to 31 errors. Most are small (a misread line item). Some are not (an inverted DSCR ratio). Until a firm has built a verification pipeline, the rational posture is to use AI as a draft generator, not a decision maker.
2. No standard verification protocol exists in the industry
Public accounting has GAAP. Engineering has stamped drawings. CRE underwriting has the LP memo, the IC memo, and the broker package, but none of those have a defined AI-verification line item. A firm that wants to trust AI cannot point to an industry standard to anchor that trust.
3. Fiduciary obligations raise the bar
A sponsor that buys a property based on AI-generated underwriting and the underwriting turns out to be wrong faces investor litigation. The downside risk is asymmetric: AI-generated underwriting that is right saves time; AI-generated underwriting that is wrong creates legal exposure. Until that exposure is contractually addressed, the rational fiduciary posture is to keep AI in the draft layer.
What CRE Investors Should Take From the Survey
CRE investors looking for personalized guidance on closing the AI use-to-trust gap can reach out to Avi Hacker, J.D. at The AI Consulting Network.
1. AI use is no longer optional
66 percent regular use means AI is now table stakes for any analyst or broker. A firm whose competitors are using AI to abstract leases 3x faster has lost the productivity edge before the deal hits the screen. For background on the underlying tools, see our ideal AI tech stack for CRE investors.
2. Building the verification layer is the competitive frontier
The first firms to close the 61 percentage point gap between "I use it" and "I trust it" will compound a real advantage. The verification layer is not glamorous: it is prompt standardization, formula enforcement, independent re-derivation, and citation-per-number. Firms that build it will close deals faster and with more confidence than firms still treating AI as a side tool.
3. The use mix will shift as trust grows
Today's top use cases (market research, lease abstracting, marketing copy) are low stakes. As trust grows, AI use will migrate toward higher-stakes workflows: underwriting, valuation, and eventually deal sourcing. The 12.2 percent underwriting figure in the survey will probably double in 18 months as Claude Opus 4.7, GPT-5.5, and Gemini 3.1 Pro mature their financial-data accuracy.
4. Vendor selection matters less than verification process
The survey did not differentiate between ChatGPT users, Claude users, and Gemini users. The trust gap is roughly the same regardless of vendor because the problem is workflow, not model. A firm with a strong verification process will trust any frontier model more than a firm with no process trusts the best frontier model.
How This Connects to Broader 2026 Trends
The First American and DealGround findings sit alongside complementary signals from earlier in 2026:
- The 2026 CoreNet Global and Colliers report found that AI is the number one driver of CRE change, with 51 percent of corporate real estate professionals naming it as the single largest force reshaping their work. See our coverage of that report on CoreNet and Colliers AI findings.
- Allwork research estimates AI productivity gains could increase US demand for office, industrial, and retail real estate by 12 percent over the next decade, adding roughly 330 million square feet.
- CBRE's 2026 Tech Gateway Office Markets report identified 17 markets where AI growth is accelerating leasing, with the largest tech-leasing gains in Manhattan, Toronto, and Boston.
The shared pattern across all of these data sets is that AI is reshaping CRE faster than CRE is building the governance to handle it. The 5 percent decision trust number is the cleanest expression of that lag.
What CRE Firms Should Do This Quarter
For sponsors, brokers, and asset managers reading this in Q2 2026, three concrete steps move the needle:
- Map your current AI use against the survey's categories. If your firm's mix is heavy on marketing and light on underwriting, you have unrealized productivity in the underwriting workflow.
- Build the verification protocol. Pick three core metrics (NOI, cap rate, DSCR) and write a standard AI prompt with citation-per-number and independent re-derivation. Use this for every deal screen.
- Standardize on enterprise AI tier. Consumer accounts with confidential data are a known governance gap. Move to ChatGPT Enterprise, Claude for Work, or Gemini Enterprise with SSO, DPA, and audit logs.
For CRE firms ready to close the trust gap with a structured verification rollout, The AI Consulting Network specializes in exactly this transition. For research grounding the broader market context, the First American Data and Analytics CRE technology research provides the underlying survey context referenced throughout this article.
Frequently Asked Questions
Q: What percentage of CRE professionals use AI in 2026?
A: According to the 2026 First American Data and Analytics and DealGround survey of 255 CRE professionals, 66 percent use AI on a weekly or daily basis. However, only 5 percent trust AI enough to influence actual deal decisions.
Q: What is the most common AI use case in commercial real estate?
A: Market research and comparable analysis is the most common primary use case at 20 percent, followed by lease abstracting and document review at 15.3 percent and marketing materials at 13.7 percent. Underwriting and financial modeling sits at 12.2 percent of primary uses.
Q: Why do CRE professionals not trust AI for deal decisions?
A: Three reasons: frontier models still hallucinate on 1.8 to 3.1 percent of financial prompts, no industry-standard AI verification protocol exists for CRE, and fiduciary obligations create asymmetric downside risk if AI-generated analysis turns out to be wrong.
Q: Will CRE AI trust grow in 2026 and 2027?
A: Yes, likely faster in firms that build verification protocols around their AI use than in firms that wait for vendor accuracy to improve. The technology already supports decision-grade output for many CRE workflows; the gap is in process, not capability.
Q: What is the difference between using AI and trusting AI in CRE?
A: Use is running an AI tool to draft, summarize, or analyze. Trust is letting the AI output influence a real investment decision without independent verification. The First American and DealGround survey shows the use number (66 percent) is more than 13x the trust number (5 percent).