Use AI to widen the conversation

An assistant can suggest boundary cases, help summarize a specification, and generate alternative inputs. Treat those ideas as candidates to review, not a finished test strategy.

Give it useful context

Describe the users, the relevant business rules, and the failures you care about. Ask the model to separate stated requirements from assumptions. Then verify both against the actual product.

Validate the generated code

A plausible-looking test can assert the wrong behavior or call an API that does not exist. Read the test, run it, and deliberately make the expected behavior fail to see whether it catches the change.

Keep sensitive data out

Use synthetic inputs and approved environments. Follow your organization’s data handling rules before sending logs, customer records, or credentials to any external tool.

Keep the judgment human

AI can speed up a task. It cannot decide what level of risk your customers should accept. That conversation still belongs to the people responsible for the product.