McKinsey found 88% of organizations now use AI in at least one business function, and 51% have seen at least one negative consequence from AI use (often inaccuracy). KPMG highlights a governance gap: only 34% report having an organizational policy or guidance for using generative AI tools. In the Netherlands, EY reports 42% of employees fear job loss due to AI, and only 24% are satisfied with employer AI training. That is a trust problem, not a tech problem.

AI policies fail, mostly because they are vague, too strict, or impossible to find. A policy that works is practical and visible. It should give people confidence to use AI safely, not scare them into silence.

A strong AI policy usually includes:

• Approved tools (no personal accounts for work)

• Clear use cases and red lines (especially around HR, legal, and finance)

• A simple privacy rule: never paste confidential data or personal data into AI tools

• Human review of AI output before sending or publishing

• Training, support, and regular updates, because AI changes weekly

Research on generative AI governance supports the same direction: clear guardrails plus accountability and human oversight reduce risk and improve adoption.

If you want a usable AI policy template and rollout plan for your team in the Netherlands, Centralink can help.