Globally, 87% of AI projects fail due to predictable issues like undefined business outcomes, inadequate data audits, and poor governance. To succeed, projects must clearly define their goals, thoroughly audit data quality, integrate compliance from the start, ensure proper team structure, and begin with focused pilots rather than expansive platforms. These measures increase the likelihood of reaching production to 13%.
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