How AI and ML Revolutionize Testing

Intelligent Test Prioritization: AI-driven test automation tools can interpret test requirements, automatically generate test scripts, and adaptively prioritize test cases based on risk factors such as code changes, criticality of features, and historical failure patterns and business priorities. This accelerates time-to-market, reduces testing costs, and improves overall test effectiveness. By intelligently selecting which tests to run first, testing teams can optimize resource utilization and focus their efforts on areas that are more likely to uncover critical defects.

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