Your data engineering lead green-lights another middleware connector because the vendor showed clean field mappings between the ERP and the new analytics warehouse.
Within six weeks the inventory forecasting model begins surfacing recommendations based on quantity fields that now carry different units after a quiet ERP patch.
No alert fires because the integration layer logs success on every record count match, not on semantic agreement.
The platform licence covers the connector but leaves contract testing and drift monitoring as unfunded internal work that never makes the sprint list.
Downstream AI teams discover the mismatch only when forecast accuracy drops and finance starts questioning why replenishment orders no longer align with actual stock movements.
Fixing it now requires a full re-mapping pass plus regression checks across every consuming model, work that should have been caught at the first schema change.
The pattern repeats whenever procurement buys connectivity without requiring machine-readable contracts and automated verification at each boundary.