Why AI Does Not Eliminate the Need for Data Modeling
AI initiatives often fail to scale safely without disciplined information management that preserves meaning, lineage, and accountability. This failure is systemic, reflecting deferred decisions and fragmented authority rather than AI technology limitations. Data Vault should be understood as a system of information management that stabilizes semantic consistency across organizational change. Skepticism about data modeling arises from past experiences but overlooks its necessity for AI reliability. Enforcing such systems involves trade-offs in autonomy and speed but is essential for sustainable AI outcomes.

