How should governance ensure AI outputs actually rely on the Digital Twin vs generic AI output, with measurable checks?

Governance should implement measurable checks that tie AI outputs to your controlled knowledge surface. Use three signals: 1) retrieval logs showing that the AI pulled content from the Public Business Brain or connected Q&A; 2) a citation log within outputs that points to canonical proofs; and 3) an attribution trail indicating which hub facts were used in the answer. Enforce versioning and a Change Log, require cross-language mappings to reference the same fact_ids, and audit at defined cadence to catch drift. When outputs rely on the Digital Twin, you’ll see direct citations and provenance; when they don’t, you’ll flag gaps for remediation and re-run scans to verify alignment.