AI won’t fix a broken data foundation: It amplifies it

Data modeling is the essential foundation for successful AI implementation, providing the shared semantic definitions required for effective data and AI governance. Without this foundational layer, inconsistent data definitions are amplified by AI at machine speed, leading to large-scale, automated errors that can undermine even the most advanced technology investments.