Runtime AI governance & audit

AI governance is the ability to see which AI systems your organization actually uses, control what data reaches them, and prove both to a regulator on demand. It rests on three technical capabilities applied to every AI tool, approved or not: visibility, control and evidence. A policy states intent; runtime governance is the infrastructure that makes it real, at the moment AI is used.

Regulators and DPOs ask for demonstrated behavior, not policies, and a record reconstructed after the request carries far less weight than one that already existed. These articles define AI governance, explain runtime governance and the audit trail it produces, separate governance from AI security, and compare the platforms that provide it in Europe.