Many organizations say they need AI skills.
What they actually need is AI literacy.

The Centralink analysis makes an important point.
AI literacy is not about coding, models, or prompts. It is about judgment. Employees need to know when to use AI, when not to, and how to check its output.

This is where many companies struggle.

People already use AI at work. Quietly. Often without rules. Often without support. Not because they are careless, but because they want to be faster and better at their jobs.

The risk is clear:

• Wrong outputs are trusted too quickly

• Sensitive data is shared without thinking

• Decisions are influenced by tools that people do not fully understand

AI literacy means something practical:

• Knowing what AI is good at and what it is bad at

• Understanding bias, limits, and errors

• Reviewing AI output before acting on it

• Using AI as support, not authority

This article is right about one thing.
AI literacy must be built into daily work. Short courses alone will not work. People learn when managers talk about AI openly, when examples come from real tasks, and when mistakes are treated as learning moments.

If organizations ignore AI literacy:

• Risk grows quietly

• Trust drops

• AI value stays low

If they invest in it properly:

• Confidence grows

• Adoption improves

• People and AI work better together

At Centralink, we help organizations build practical AI literacy for managers and teams, focused on real work, not theory.

Do your people know how to work with AI, or are they guessing?

Reach us via info@centralink.nl