The low success rate of AI and ML experiments, typically around 30%, often reflects a narrow focus on production deployment. Effective experimentation prioritizes an AI learning culture, value demonstration, and agile delivery methods. Best practices include setting clear success criteria, regular reviews, centralized documentation, and rewarding knowledge sharing to foster an agile AI learning culture.

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