METANOWDecide who is accountable
AI governance sets how an organisation selects, develops, deploys and oversees AI. It identifies accountable owners, permitted uses, risk decisions and the evidence needed before a system is released.
Work across the life cycle
Governance includes data provenance, testing, access, monitoring, incident response and retirement. It asks how the system affects people, whether its performance is suitable for the task and when human review is required.
Translate policy into controls
For a document assistant, controls might include approved sources, document permissions, answer evaluation, reviewer corrections and a route for complaints. Record the model and workflow version so a reported issue can be investigated.
Ask for evidence
A policy document alone does not prove that controls operate. Review test results, decision records and monitored outcomes. Frameworks such as the voluntary NIST AI RMF can help structure the work; they do not automatically establish legal compliance or certification.
Sources & further reading
Reviewed 19 October 2026. This is a technology learning session; examples describe possible designs, not a claim that a particular integration is active.