ModelRefs / AI Governance Hub

AI Governance Hub

Policies, audits, compliance automation and risk frameworks for enterprise AI.

Overview

From Shadow AI discovery to EU AI Act compliance. A complete framework for SMBs ready to scale responsibly.

Quick start — choose your priority

  • Need a policy?

    Review governance methodology.

  • Under audit?

    Review trust and evidence standards.

  • New to EU rules?

    Read the 2026 guide.

The Governance Roadmap

A four-stage framework for turning AI risk into a managed, demonstrable position.

  • Stage 1 — The Essentials: Build Your Foundation

    Establish your AI governance baseline with a comprehensive Acceptable Use Policy.

  • Stage 2 — The Crisis: Find Hidden Risks

    Identify Shadow AI tools that bypass your policies and expose your organization to risk.

  • Stage 3 — The Mandatory: Regulatory Compliance

    Navigate the EU AI Act and ensure your AI deployments meet legal requirements.

  • Stage 4 — The Edge: Competitive Advantage

    Turn governance into a sales moat. Win enterprise clients with AI transparency.

Why AI governance matters in 2026

The EU AI Act's main obligations apply from 2026, and its highest penalty tier reaches €35 million or a percentage of worldwide annual turnover, whichever is greater.

  • The risk of inaction

    €35M+ fines under EU AI Act violations. Data breaches from unauthorized AI tools. Lost enterprise contracts requiring compliance. Reputational damage from AI incidents.

  • The competitive advantage

    Win enterprise deals with compliance proof. Build customer trust with transparency. Reduce liability and insurance costs. Future-proof against evolving regulations.

Ready to start your governance journey?

Begin with Stage 1 and work your way through the complete framework, or jump directly to the stage that addresses your most urgent need.

All governance references (1)

Every published governance and regulation reference.

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to AI Governance Hub.