AI Literacy Assessment

A practical, workplace-focused AI literacy assessment that measures how people understand, use, verify and govern AI tools in real work situations.

6 dimensions 30 min Verifiable certificate

Leaderboard

Top performers

P

Pandu Atini

95 / 100

2
A

Alex

96 / 100

1
N

Nenad

95 / 100

3

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This assessment measures practical AI literacy across six dimensions: Know & Understand, Use & Apply, Detect AI, Evaluate & Create, Ethics & Risk, and AI Impact Awareness. Each dimension starts with a short self-rating, followed by scored workplace scenarios. This lets the report show both actual capability and self-awareness gaps. The questions focus on everyday professional judgement: how AI tools can fail, how to use them effectively, when to verify outputs, how to handle privacy and bias risks, and who remains accountable for AI-assisted work. The result helps organisations target training and evidence proportionate AI literacy measures. It is not a certification and does not replace legal, compliance or technical review.

What it measures

Know & Understand

Whether the learner has a practical mental model of how AI systems produce outputs, where they can fail, and what common claims like accuracy or confidence really mean.

Use & Apply

Whether the learner can use AI tools intentionally: choosing suitable tasks, writing useful prompts, maintaining tool quality, and knowing when human verification is needed.

Detect AI

Whether the learner can recognise AI-generated, AI-manipulated or AI-assisted content in professional settings, and respond through verification rather than surface impressions.

Evaluate & Create

Whether the learner can critically review AI outputs before using them, separate supported facts from generated assumptions, and treat AI as a starting point rather than final authority.

Ethics & Risk

Whether the learner responds appropriately to privacy, bias, explainability, intellectual-property and escalation risks, especially under time pressure.

AI Impact Awareness

Whether the learner understands accountability, downstream effects on people, human oversight, and the need to monitor AI systems after deployment.