AI inventory and ownership
Start with an inventory of AI systems, purposes, vendors, data, roles, owner and review rhythm. Without an inventory, governance becomes scattered decision-making.
AI governance and compliance
AI governance and compliance in the Netherlands
A practical roadmap for bringing the EU AI Act, GDPR, AI literacy, risk classification, DPIA, FRIA, vendor assurance and evidence into one working governance model.
Governance model
What belongs in an AI governance framework?
Most organisations do not need a thick manual as a first step. They need a working model that shows which AI systems exist, which risks matter, who decides and what evidence is available.
Risk classification
Determine whether each system is prohibited, high-risk, subject to transparency duties, GPAI-related or low risk. Article 6 and Annex III are central.
Policy, controls and decision-making
Define who may use AI, which review is needed, when legal, privacy and security join, and which controls must be demonstrable.
DPIA, FRIA and vendor evidence
Privacy impact, fundamental rights impact and vendor evidence should come together in one file. This becomes relevant quickly in HR, government, education, finance and essential services.
AI literacy and training records
Article 4 requires an appropriate level of AI literacy. Connect training to roles, systems, risks, completion logs, certificates and management reporting.
Monitoring, transparency and change control
Governance does not stop at deployment. Track logging, incidents, model changes, transparency duties and periodic reviews.
Roadmap
From scattered AI questions to demonstrable control
Use this route as content navigation through Responsible AI Platform. The order helps move from legal text to classification, evidence and execution.
1. Understand the obligations
Start with the legal structure, your role in the value chain and the deadlines coming toward your organisation.
2. Classify systems
Make visible which systems may be high-risk, which fall under Article 50 and where a GPAI relationship exists.
3. Build the evidence file
Use templates and tools to connect policy, inventory, risk analysis, DPIA/FRIA and training evidence.
4. Test readiness and priority
Determine where your organisation stands and which actions come first for leadership, compliance, privacy, HR, procurement and product teams.
Sectors
Where governance becomes concrete quickly
AI governance stays too abstract if you do not look at real processes. These sector routes help place risks, roles and evidence per context.
Practical next steps
From guidance to implementation and training evidence
Responsible AI Platform explains and structures. If you want to move further, Embed AI and LearnWize support the two most common needs: implementing governance and making AI literacy demonstrable.
Embed AI
AI governance and compliance consultant
For organisations moving from analysis to implementation: scope, roadmap, AI inventory, policy, controls and management decisions.
View consultant pageEmbed AI
AI Act readiness sprint
For a compact gap analysis around the EU AI Act, GDPR, AI literacy, vendors and priorities.
View readiness routeEmbed AI
AI governance consultant
For setting up a working governance model with roles, review structure, intake process and evidence rhythm.
View governance routeLearnWize
AI Literacy Readiness Assessment
Use the assessment to reveal role gaps, Article 4 risk and training priority.
Start the assessmentLearnWize
Article 4 AI Act training
Role-specific AI literacy for teams that use, procure, build, review or control AI.
View trainingLearnWize
AI literacy evidence pack
For certificates, progress records, role matrix and management reporting around Article 4.
View evidence routeExpertise
Further reading around Zahed Ashkara as AI governance expert
This page is part of a broader knowledge network around the EU AI Act, governance, compliance, AI literacy and responsible AI use.
FAQ
Frequently asked questions about AI governance and compliance
Short answers for organisations that want to make AI governance practical.
What is AI governance and compliance?
AI governance and compliance combines policy, roles, risk classification, privacy, security, training, vendor assurance, monitoring and evidence so an organisation can use AI responsibly and demonstrably.
Where should AI governance start?
Start with an AI inventory and role mapping. Then classify systems under the EU AI Act, assess GDPR/DPIA/FRIA impact, set up policy and controls, and connect training to roles.
How does AI literacy relate to governance?
AI literacy is a governance control. People who use, procure, review or build AI need sufficient understanding of risk, limitations, human oversight, privacy and organisational policy.
Is an AI policy enough?
No. A policy helps, but supervisors and clients also look for inventory, ownership, risk assessment, DPIA/FRIA, training records, vendor evidence, monitoring and decisions.
When do you need external support?
External support is most useful when multiple teams use AI, vendors bring AI into processes, Annex III domains are involved, Article 4 evidence is missing or leadership needs priorities quickly.
Sources
Official sources and primary documents
This route links to official texts, Commission information and Dutch supervisory information where possible. Always check the current legal text and supervisory information for definitive qualification.