In 2025, McKinsey reports that more than 60 percent of AI programs fail to scale because governance is weak or missing [1].
Deloitte shows that AI risk and compliance costs rise by over 30 percent when roles and controls are unclear [2].
PwC adds that boards now see AI governance as a top three executive risk, not a tech issue anymore [3].

So what is AI governance really?

Recent academic work gives a clear answer.
AI governance is not policies on paper.
It is a system of rules, practices, and processes that align AI with strategy, goals, and values.

Research highlights four agendas that matter most today [4]:

• Technical: explainability and model strength
• Stakeholder: trust, skills, and human impact
• Regulatory: moving from soft rules to real enforcement
• Process: audits, monitoring, and clear ownership

>Here is the hard truth.
Technology is not the main blocker.Culture and senior leadership commitment decide success or failure.
Without ownership at board level, AI becomes risky, slow, and expensive.

For Dutch organizations, this is urgent.
The EU AI Act is coming. Fines, audits, and reporting duties will follow.
Those who act now gain trust and speed.
Those who wait will pay later.

At Centralink, we help leaders design practical AI governance that fits their strategy and culture. No theory. No box ticking.

If AI is already in your organization, governance cannot wait.

What is your biggest concern today? Risk, compliance, or trust?

Reach out via info@centralink.nl

References 
[1] McKinsey & Company. (2025). The state of AI governance.
[2] Deloitte. (2025). Global AI risk and governance outlook.
[3] PwC. (2025). AI governance and board responsibility report.
[4] Birkstedt, T., Minkkinen, M., Tandon, A., & Mäntymäki, M. (2024). AI governance themes and future agendas. Journal of Business Research.