SOURCING EXCELLENCE
AI & TECHNOLOGY
AI readiness discussions often begin with a cleanup project.
Fix the supplier master. Standardize descriptions. Repair classifications. Then deploy the technology.
The problem is the implied finish line.
The business keeps changing, so the data keeps changing. New suppliers appear. Categories move. Acquisitions introduce new definitions. Workarounds accumulate.
Data quality is not the project before AI. It is part of the work of running AI well.
That means ownership, standards, monitoring and continuous correction. A perfect snapshot at go-live is less useful than an organization capable of noticing and correcting drift.