Practical guide · AI literacy

AI literacy for employees: what should remain after training

Useful AI training leaves employees with clear data boundaries, a verification routine and known routes for approval and incident reporting.

The goal is not to memorise definitions

Employees do not need a general lecture on the history of artificial intelligence. They need to recognise when AI is appropriate, which data must stay out and when an output needs additional verification.

Teach with company-relevant examples

Examples should use tools and processes from the inventory without real confidential data. Sales, HR and marketing teams face different risks; scenarios make the rule memorable.

  • an allowed case and its verification step
  • a conditional case and the approval owner
  • a non-approved case and a safer alternative
  • a simulated incident and the first reporting step

Check understanding, not only attendance

An attendance register shows that the session happened; it does not show that rules were understood. A short knowledge check and participant questions provide better signals. Policy acknowledgement remains distinct from consent.

Return after 30 days

Collect repeated questions, tool requests and observed errors. Update the guide and examples from operational reality while preserving versions and approvals.

General educational material. It is not legal advice and does not replace legal, DPO, HR or security review appropriate to your organisation.