Do We Really Need a Certified AI Management System for Effective AI Governance?
I recently completed an interesting online course on Certified AI Management Systems on the LinkedIn Learning platform — and it sparked a question I’ve heard more and more often lately:
Is a certified AI Management System necessary for effective AI governance?
And honestly… that might be the wrong question. A better one could be:
👉 Are we fit as an organisation for purpose?
Because before going all-in with yet another management system, it’s worth taking a step back and asking what your organisation actually needs to manage AI responsibly, safely, and effectively.
From my perspective, there are three topics that matter most when setting up and introducing AI management in a company — regardless of whether certification is on the roadmap or not.
1) Provide Understandable Guardrails
AI governance doesn’t work if it only lives in legal documents and compliance slide decks.
Employees need clear, understandable guardrails they can apply in real daily work.
That means:
✅ Defining an AI Governance Policy
✅ Creating practical guidelines on how to use AI tools responsibly
✅ Helping teams avoid “shadow AI” by making the rules usable, not scary 🫣
Good governance should feel like enablement, not just restriction.
2) Know and Deal With the Risks
Governance without risk awareness is basically guesswork.
A key step is to build an inventory of AI use cases already happening in your daily business:
📌 Where is AI being used today?
📌 Who is using it?
📌 For what purpose?
📌 With which data?
📌 What tools and vendors are involved?
Once you have that, you can assess risks — ideally aligned with frameworks like the EU AI Act risk classification.
Especially important:
🚨 Identify whether you have high-risk use cases
🛠️ Prioritise mitigation and controls for those cases
📉 Reduce risk before scaling adoption
In short: Don’t manage AI blindly — manage what you actually use.
3) Enable Employees Through Learning
AI governance isn’t just about systems — it’s about people.
If employees don’t understand AI well enough to use it responsibly, no certification will save you. 😅
What helps:
🎓 Offer AI learning paths
🧠 Encourage continuous self-learning
🌱 Motivate people to experiment safely and improve over time
The goal isn’t to turn everyone into an AI engineer — but to build AI literacy across the organisation.
🧩 So… Do You Need Certification?
Maybe. Eventually.
A certified AI Management System can be a powerful structure — especially when organisations need:
📋 Standardisation
🔍 Audit readiness
🏢 Scalable governance across business units
🌍 External credibility and trust
But certification should be a result of maturity, not a shortcut to maturity.
✅ Final Thought
Before investing heavily into certification and formal systems, I’d recommend focusing on:
🧱 Guardrails (policy + guidelines)
⚠️ Risk inventory + assessment (EU AI Act thinking helps)
🚀 Enablement through learning
Get those right — and you’ll be much closer to real AI governance than any certificate alone can provide.