Managing test cases in Jira often starts simple — but as teams scale, gaps begin to appear. Traceability becomes harder to maintain, test execution visibility is limited, and reporting lacks the depth needed for confident release decisions.

AI is only as effective as the data and processes beneath it — structured test cases, consistent execution history, and clear defect signals.

This checklist helps QA and engineering teams evaluate their current test case management practices, identify gaps in Jira-based workflows, and assess whether their testing process is ready to support AI-driven capabilities. Use it to identify gaps, improve process maturity, and define what your next test management platform should deliver.