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After 34 years of digital transformation experience, I've seen a predictable pattern: Industrial AI projects fail when companies skip foundational work. Like Rome's layered architecture, successful AI requires three levels - integrated PLM/ERP/MES systems as bedrock, Industrial Data Fabric as infrastructure, and AI as the visible achievement on top. Companies with mature system integration succeed with AI, while those jumping straight to algorithms fail predictably. With 75% of AI projects failing due to data infrastructure issues, the lesson is clear: assess your foundation maturity first, then build AI systematically.

After 34 years of ERP implementations, I spent four months studying AI frameworks and discovered a fundamental truth: AI must be nurtured like a young employee, not deployed like software. Sol Rashidi's research shows 70% of AI success comes from culture and team dynamics, not technology. Unlike ERP's "deploy and celebrate" model, AI requires continuous guidance and adaptation. This changes everything about assessment, implementation, and success metrics. Manufacturing and supply chain leaders need new methodologies that treat AI as a living extension of organizational values.