Copilot-Assisted Test Scenario Design
Used AI-assisted exploration to broaden test-scenario thinking for a process-heavy workflow, while keeping relevance, structure, and final validation under human review.
Context
A process-heavy reconciliation workflow required coverage across data conditions, formatting differences, and exception paths. The challenge was not simply to produce more test cases, but to explore possible scenarios without losing the practical structure needed for review and execution.
Approach
I used Copilot as an exploration aid to surface possible scenarios and questions, then reviewed, filtered, and organized the useful output into a practical test-plan and walkthrough structure. The workflow treated AI output as draft input, not as an authoritative testing decision.
Principle
The value came from combining faster scenario exploration with reviewer judgment. Relevance, completeness, and correctness remained human responsibilities, helping keep the resulting test material aligned with the actual workflow rather than with generic AI-generated assumptions.