EUAIACTUS.COM

Operational AI governance

Build an AI governance system that can support EU AI Act compliance.

AI governance turns legal requirements into ownership, controls, evidence and repeatable decisions across product, engineering, procurement, HR, legal, compliance and risk teams.

A service provided by Lexara Advisory LLC.

Governance architecture

Six capabilities every serious program needs

AI system inventory

A maintained register of systems, models, vendors, intended purposes, owners, users, affected persons, jurisdictions and deployment status.

Role & scope decisions

Evidence of territorial-scope, provider/deployer/value-chain role and applicable obligation determinations per system.

Risk classification

Prohibited-practice screening, Article 50, GPAI, high-risk pathways and relevant data-protection/sectoral overlays.

Control ownership

Named accountable owners for transparency, documentation, human oversight, testing, incident management, procurement and monitoring.

Evidence architecture

A traceable record showing what was assessed, what control exists, who approved it, when it was reviewed and which source/version was used.

Change governance

Triggers for reclassification and control review when models, intended purpose, data, vendor, geography or regulatory requirements change.

EU AI Act first

Do not replace legal analysis with a governance framework.

NIST AI RMF and ISO/IEC 42001 can help structure governance. They are not substitutes for the EU AI Act and do not automatically demonstrate compliance with a specific Article or obligation. The mapping must be explicit.

EU AI Act

Binding regulatory requirements, actor roles, risk categories, application dates and enforcement.

NIST AI RMF

A voluntary risk-management framework that can help organise governance, mapping, measurement and management activities.

ISO/IEC 42001

An AI management-system standard that can support organisational governance processes and continuous improvement.

Control crosswalk

Use frameworks to reuse evidence and operating processes only where the mapping to the legal requirement is defensible.

2026 priorities

Governance work that cannot wait for 2027

  • Prohibited-practice screening and escalation.
  • Article 50 transparency controls for applicable systems.
  • GPAI provider/downstream role analysis.
  • AI literacy measures under amended Article 4.
  • High-risk system inventory and classification readiness.
  • Vendor/model documentation requirements.
  • Regulatory-change monitoring and legal-review triggers.

Deliverable

A governance program should make decisions reproducible.

A regulator, auditor, customer or internal committee should be able to understand which systems were reviewed, what rule applied, what evidence supported the decision and who owns the next action.

Build the operating model around your real AI systems.