How to Become an AI Governance Officer?

Raymond Blyd began his legal career in Suriname and the Netherlands, specialising in intellectual property law and legal knowledge system engineering. He has worked across law firms, corporates and a major legal publisher on global legal technology, before founding Legal Complex. He now advises legal tech companies and works with the Dutch Ministry of Defence on AI governance. His focus is practical: enabling organisations to use AI responsibly by embedding governance into technology and creating clear decision-making pathways.

Overview

Blyd described AI governance as identifying AI-related risks and determining how to mitigate them. These risks vary between commercial and public sector organisations, where trust, fairness and credibility are especially critical when AI affects citizens. Governance is therefore not purely technical; it requires shared understanding across legal, compliance, and technical teams of risks, responsibilities and mitigations.

A key challenge is that AI governance is not a one-off exercise, as models, algorithms and data continuously evolve. Organisations must maintain an auditable record of changes, linking governance closely with data governance. At the Ministry of Defence, Blyd integrates governance into developer workflows using tools such as MLflow and GitHub.

For legal professionals, he emphasised combining legal expertise with technical understanding, starting with clear organisational definitions of AI, mapping relevant regulations (including the EU AI Act and cybersecurity rules), and avoiding overly complex policies. Instead, governance should be simplified, explainable, and supported by clear escalation routes so employees can access expert guidance when needed.

Key Takeaways

  • Understand the technology. AI governance professionals need enough technical fluency to understand how AI systems are built and changed.
  • Start with shared definitions. Define what the organisation means by AI and which systems fall under governance.
  • Treat governance as continuous. Systems evolve, so governance must ensure ongoing traceability and auditability.
  • Look beyond regulation. Consider wider requirements, including cybersecurity and sector-specific rules.
  • Build communities and communication channels. Connect existing expertise across the organisation around shared goals.
  • Create pathways, not just policies. Make governance clear and give people direct access to expert support when needed.

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