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Cognitive Project Management in AI · PMI
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- CPMAI stresses that AI projects fail for AI-specific reasons: applying traditional waterfall software practices to data-centric work, underestimating the quantity and quality of data needed, vendor hype and product mismatches, overpromising, and the gap between a model that works in the lab and one that works in production. CPMAI's iterative, data-centric phases are designed to counter these failure modes.