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Article 4 points to AI literacy measures that fit knowledge, experience, training, context of use, and impact. LearnWize helps translate that duty into role-based training and demonstrable evidence.
Evidence chain
LearnWize Article 4
If everyone gets the exact same session, it remains unclear whether training fits a recruiter, policy advisor, product owner, manager, or support employee.
Roles differ in AI use and responsibility.
High-risk or customer-impacting workflows need more depth.
An attendance list does not prove understanding.
Leadership needs a summary that supports decisions.
Document which teams use AI, which tasks are involved, and which knowledge each role needs.
Connect training to the context in which AI is used, including impact on candidates, citizens, customers, or employees.
Let employees practice with realistic work situations, not only generic AI explanations.
Keep participation, scores, certificates, and completion records as evidence that understanding was tested.
Give HR, Legal, Compliance, IT, and leadership a clear view of where the organization stands.
Decide when training needs to be updated because of new tools, policies, roles, or risks.
For ChatGPT, Copilot, Gemini, Claude, or internal AI workflows.
For decisions, advice, screening, analysis, or communication with external impact.
For a concrete dossier instead of scattered training notes.
Map roles, AI use, and missing evidence.
Connect teams to use cases, risks, and learning paths.
Launch LearnWize training by audience.
Test understanding with scenarios and certificates.
Deliver reporting, evidence dossier, and refresh advice.