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Artificial intelligence is a powerful lever for test teams. In concrete terms, it makes it possible to :

• Increase test coverage AI automatically explores a greater number of scenarios and combinations, far beyond what a human team can cover on its own.
• Go much faster test case generation and execution are accelerated, considerably reducing time-to-production.
• Identify unexpected test cases By analyzing data and behaviors, AI detects unexpected paths and borderline cases that are often overlooked.
• Rely on user flows AI can replay and analyze real user journeys to direct testing efforts where they are most relevant.
• Compare Figma and application screens AI tools are used to automatically compare design mock-ups (Figma, etc.) with real application interfaces, to detect visual discrepancies.
• Analyze a Swagger and generate API test cases By exploiting API documentation (Swagger/OpenAPI), AI can automatically derive functional and non-regression test cases.

One thing is certain: AI will never replace the test analyst. It is a powerful tool at the service of the tester, and remains indispensable for judging the relevance of tests, interpreting results and guaranteeing overall quality. AI helps, it doesn't replace.