AI document intelligence is worth evaluating when a team repeatedly extracts the same information from documents. Test its performance on your actual document types, including the scans and exceptions that slow reviewers down.
Extraction helps organize information; it does not establish that a document meets a legal, contractual or technical requirement. Keep that decision with the qualified person responsible for review.
Three Workflows to Evaluate
These are illustrative ways to scope a pilot, not reported client results.
Vendor documents. Extract the named insured, policy dates and other required fields from a certificate of insurance into a review queue. Link each field to its source and assign an owner to resolve missing or conflicting information. Schedule reminders from verified dates; keep coverage and contractual decisions with the responsible reviewer.
Construction submittals. Extract the submitted product, specification references and supporting documents into a worksheet for the project engineer. The engineer checks the source material and makes the acceptance decision.
Engagement-letter review. Compare a draft with an approved checklist and flag missing or changed terms. A qualified reviewer resolves differences before the letter is approved.
Map the Process and Its Data Boundary
Map one document type from arrival to final approval. Name the person who receives it, the fields they need, the system where those fields belong and the reviewer who makes the final decision. Confirm which documents the approved tool may receive and who may access results.
Record current review time, corrections, missed findings and backlog. Check model performance alongside scope, training, integration and review design. Any of those can prevent a pilot from working. A related example is AI invoice processing.
Use Confidence Scores Carefully
Place extracted fields in the team's existing review system and keep a link to the source document beside the result. If the tool supplies confidence scores, test how those scores relate to errors in your own sample before choosing a review threshold.
Microsoft's documentation explains that confidence is an estimate, not every field has a score, and critical workflows should include human review. Product behavior varies; a threshold from another team's documents is not automatically suitable for yours.
Route missing fields, conflicting dates, unfamiliar formats and material findings to a named reviewer. A high score does not replace required human approval.
Agree on Acceptance Before Live Work
Use an authorized sample that includes difficult scans, missing information and unusual layouts. Compare extraction with a qualified reviewer's findings. Measure:
- Total review time, including corrections and exception investigation.
- Missed material fields and incorrect extracted values.
- False alerts and the work needed to resolve them.
- Whether reviewers can find the supporting source and follow the escalation rule.
Keep the manual process available while the pilot is evaluated. Give reviewers enough practice to demonstrate extraction checks and exception handling before live use; set training time from readiness, rather than a fixed workshop promise.
The goal is to give reviewers more time for judgment and exceptions. Verify that goal against a fully human-reviewed sample. A faster first draft with more missed findings is not an acceptable improvement.
Assign Responsibility After the Pilot
Decide who reviews errors, who can change the workflow, who tests changes and when automated processing must pause. Include changes to document formats and review requirements in that process.
Set the rollout schedule from pilot evidence, integration work and review needs. Expand only when results meet the criteria agreed by the people accountable for the work. A defensible decision about one workflow is useful even when the next step is to fix the process first.
If your team is evaluating a document workflow, book a consultation or explore AI literacy training. Bring the document type, review checklist and handoff you want to improve.