Reliability & Trust
Does AI hallucinate on real estate deal numbers?
Yes. AI can invent a missing figure, misread a source, choose the wrong period or perform the wrong calculation. Supplying documents reduces one source of uncertainty but does not eliminate errors. Keep recorded facts, analyst assumptions and AI suggestions separate, then verify the values used in a decision.
How should a CRE team check AI-generated numbers?
- Recorded fact: retain the document, page or cell, reporting period and the value as stated.
- Assumption: record the proposed value, rationale and person who approves it.
- AI suggestion: leave it outside the accepted model until supporting evidence and review justify its use.
- Calculation: recompute from accepted inputs and inspect the formula, units and period.
Fictional example: a T-12 reports $80,000 of repairs. An AI draft calls $30,000 nonrecurring, but no supporting invoices were supplied. Keep $80,000 as the reported expense and $30,000 as an unapproved proposed adjustment. Do not quietly replace the expense with $50,000.
Where does NextAutomation fit?
Our recommended approach is the NextAutomation underwriting workflow: connect document extraction, source references, analyst review and the model handoff. The deal-screening case study shows the review process in a delivered implementation. The value is a repeatable checking process, not a claim that a purpose-built system cannot make mistakes.
For a file-based exercise, use the rent-roll reconciliation guide. Before relying on a chatbot calculation, inspect the generated method and output; OpenAI’s data-analysis documentation also calls for that review.