What is AI governance consulting?

AI governance consulting helps an organisation define how AI is inventoried, approved, owned, risk-assessed, secured, monitored and reviewed in day-to-day operations.

Is AI governance only for high-risk AI?

No. Proportionate governance should cover the full AI portfolio while applying deeper controls to higher-consequence systems.

AI Governance Consulting Europe

What this service is for

For organisations moving from scattered AI experiments to a repeatable operating model — without creating unnecessary bureaucracy around every low-impact use case.

VisibilityKnow what AI exists, why it is used and who owns it.

ControlApply deeper review where data, autonomy or consequence is higher.

EvidenceMake decisions traceable through reusable records, not one-off documents.

Typical governance workstream

Workstream	Output	Purpose
AI inventory	System/use-case register	Visibility across approved AI, embedded AI, pilots and material Shadow AI.
Roles & ownership	RACI / decision rights	Separate business, technical, security, privacy and approval responsibilities.
Risk tiers	Proportionate classification model	Route low-impact use quickly while escalating consequential use.
Policy & acceptable use	Short operational rules	Make safe behaviour clear to employees and managers.
Supplier governance	Vendor review baseline	Cover data use, retention, subprocessors, security, change and exit.
Human oversight	Review and escalation design	Define when humans verify, intervene, approve or stop a workflow.
Evidence model	Decision and review records	Support AI Act, ISO 42001, ISO 27001 and internal assurance work.

Designed around the EU context

The governance model is informed by the EU AI Act, ISO/IEC 42001, ISO/IEC 27001 and NIST AI RMF. These sources are used as complementary lenses rather than treated as interchangeable. Legal applicability is assessed separately from internal risk management.

A practical starting package

Current-state AI inventory and gap scan.
Role and decision-rights map.
Risk-tier model with escalation criteria.
Minimum acceptable-use policy.
AI supplier review baseline.
Human-oversight and incident route.
90-day implementation roadmap with owners.

Good fit

This approach is particularly useful for European SMEs, knowledge-intensive teams, education and public/social-service organisations that need structure but do not want a governance programme designed only for large multinationals.

Related resources

Reference framework sources

Build the operating model around your actual AI use

Describe the use cases, organisational context and current governance. SundAI can help identify the smallest useful control model and the highest-priority gaps.

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AI governance that works outside the policy document