AI governance framework — from policy document to live portfolio control

An AI governance framework defines how an enterprise classifies, controls and supervises its AI systems. AI-Koutsi turns the framework into a working portfolio model: every use case carries its risk tier, control set, monitoring rules and decision rights — generated automatically from the readiness assessment.

The four layers of a working AI governance framework

Strategy and principles, risk classification, control and monitoring library, and decision rights. AI-Koutsi ships canonical libraries for each layer and links them to your AI portfolio so the framework is enforced, not just documented.

Tied to the AI portfolio, not stored separately

Every prioritized use case is auto-classified and tied to its controls and monitoring rules. Governance scope changes when the portfolio changes — no parallel maintenance cycle.

Aligned with EU AI Act, NIST AI RMF and ISO 42001

The canonical control library maps EU AI Act articles, NIST AI RMF functions and ISO 42001 clauses. One classification covers all three external frameworks.

Frequently asked questions

What should an AI governance framework include?
A working AI governance framework includes principles, a risk classification scheme aligned with the EU AI Act, a control and monitoring library, decision rights and an evidence model. AI-Koutsi ships all four and ties them to your AI use case portfolio.
Who owns the AI governance framework?
Typically the CDO, Head of AI or a dedicated AI governance lead, in partnership with risk, legal and security. AI-Koutsi supports role-based access so each owner sees only the parts of the framework they manage.