1. Map the work staff do today
List the input, interpretation, checks and final action. Identify repeated reading and copying, along with the exceptions that need judgment.
From repeated handling to a reviewed process
Test the correction path as carefully as the successful draft.
A first scope should explain which step AI assists and who remains responsible for the result.
2. Agree on permitted examples and success
Choose synthetic or appropriately protected samples and define what a correct result means. Keep examples for evaluation separate from those used to develop the approach.
3. Try a bounded assisted step
Compare the proposed AI step with ordinary rules or the existing method. Record wrong and missing fields as well as successful examples.
4. Build the staff review and system handoff
Make correction, rejection and approval usable. Validate the approved data and check what happens if saving or sending fails. Use controlled substitutes for live external actions.
5. Pilot and review
Release to an agreed group with a named owner. Review corrections, exceptions, cost and processing time before expanding the volume or permitted actions.