This whitepaper discusses how AI and machine learning (ML) can significantly reduce software testing timelines and costs. By automating tasks like test case generation, test execution, and result analysis, AI and ML streamline the testing process, improving test coverage and defect prediction. Challenges include data quality, system integration, and the need for specialized skills. Despite these hurdles, AI's ability to predict defects, enhance efficiency, and optimize testing makes it a game-changer in software testing, ensuring faster, cost-effective, and higher-quality releases.

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