A practical first use of AI in a real estate transaction is a bounded extraction test, not autonomous contract drafting or client advice. Choose a task whose proposed answer can be checked directly against a source document.
Authorize the task and build an independent reference
Choose a few factual fields, such as party names and a stated date. Specify the document types and exclude interpretation, valuation and legal conclusions. Use redacted, synthetic or otherwise authorized test material; do not upload live client records before permitted use and access controls are established.
Have the appropriate reviewer record the correct values and source passages independently of the AI output. Include blank fields, amendments, poor scans and similar names. Mark genuinely ambiguous answers as unresolved rather than manufacturing a single correct value.
Count omissions as well as wrong answers
Ask for proposed values with source locations and an explicit unknown state. Compare each against the reference. Track wrong values, omissions and unsupported answers separately. Check whether reviewers catch the mistakes; a convincing explanation can make a wrong answer harder to detect.
Hypothetical example: Suppose a fictional pilot tests 20 approved documents with five fields each: 100 field opportunities. It finds four wrong values, six omissions and 90 correct values. Reporting only 96% accuracy after excluding omissions would mislead. The team records all categories and investigates whether the amendment cases account for the errors. These figures are invented to illustrate measurement.
The live-use gate and reasons to stop
Keep outputs as suggestions until a designated reviewer accepts them. Stop on unauthorized data exposure or an unapproved external action. Re-test after material model, prompt or form changes, and retain a manual path for every task in scope.
A test sample cannot establish performance on every form or future model version. Extraction is not contract interpretation. A human approval requirement reduces automation risk but does not guarantee a reviewer will detect every error.
- Narrow task and authorized data agreed.
- Reference answers created before comparison.
- Omissions and unsupported values counted.
- Reviewer acceptance required for live fields.
- Stop conditions and re-test triggers documented.