How would you design an AI-driven test strategy that uses machine learning across the entire testing lifecycle, from test planning through execution to analysis? What infrastructure and data foundations are required?

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An AI-driven test strategy applies machine learning at every stage of the testing lifecycle to create a system that continuously learns and improves its testing effectiveness.

How would you design an AI-driven test strategy that uses machine learning across the entire testing lifecycle, from test planning through execution to analysis? What infrastructure and data foundations are required?

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