White Paper

AI in Testing: What Works and What Doesn't?

AI in Testing: What Works and What Doesn't?

Pages 8 Pages

This whitepaper explores how AI is transforming software testing by increasing speed, coverage, accuracy, and cost-efficiency. It highlights key benefits such as predictive analytics, intelligent automation, and improved user experience. However, challenges include technical complexity, false positives, and over-testing. Best practices stress human oversight, data privacy, and continuous model updates. ACCELQ’s no-code platform leverages AI for test generation, self-healing, and advanced analytics. Looking ahead, features like Copilot 360 aim to embed generative AI across all test automation stages.

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