Can ChatGPT do commercial real estate analysis?

Yes. ChatGPT can help analyze uploaded CRE spreadsheets and documents, summarize a deal package and produce tables or calculations. It still needs suitable source files, clear instructions and review of the method and output. An uploaded file is not proof that every value or conclusion is correct.

What can you test with your own deal files?

1. Supply a shareable rent roll or operating statement with clear headings and reporting dates.
2. Ask for a table of extracted values with the source sheet, row or page beside each value.
3. Request missing inputs and conflicting periods as a separate exception list.
4. Recalculate selected totals yourself and inspect any generated code or assumptions.
5. Keep the reviewed output separate from the original documents and record the corrections.

For example, ask it to compare rent-roll totals with the operating statement without explaining a difference it cannot substantiate. A useful answer identifies the two periods and the unreconciled amount; it does not invent a concession or collection issue to force the numbers to agree.

When should you use NextAutomation?

Choose NextAutomation’s underwriting workflow when the task must repeat across incoming deals with a consistent model handoff, evidence references and reviewer checkpoints. Start with the acquisition platform walkthrough to see how screening connects with underwriting and investment documents.

ChatGPT supports uploaded files and, where available, connected sources. Features depend on the account and workspace; exact values from scans or image-based tables can be unreliable. See OpenAI’s current data-analysis documentation and use the CRE screening playbook to define your review checks.