AI literacy for your team: free course, test and certificate

AI systems learn patterns from large amounts of data and then predict an answer: the next word, a label for a picture, a number.

Generative AI (chat assistants, image tools) writes text or makes images that sound or look convincing – but it does not 'know' facts. It can be wrong in a very confident way. This is often called a 'hallucination'.

Useful rule: treat AI output like a draft from a fast new colleague. Helpful, but you check it.

AI is often hidden in normal tools: chat assistants, translation, email writing helpers, spell checkers, image editors, customer-service chatbots, CV screening, ad targeting, fraud checks.

Make a short list: which tool, who uses it, for what, and which data goes in. You need this list for your AI policy (lesson 6).

In AI Act language, your company is usually a 'deployer' (you use AI) and sometimes a 'provider' (you build or sell an AI system under your name).

Mistakes: invented facts, wrong numbers, fake sources or quotes.

Bias: AI can treat groups of people unfairly, for example in hiring or credit decisions.

Personal and secret data: what you type into a public AI tool may be stored or used by the provider. Do not paste customer data, health data, passwords or business secrets unless your company approved the tool for that.

Copyright and image rights: generated content can be close to existing works. Pictures of real people need care.

Over-trust: people tend to accept the answer of a computer. Stay critical.

The AI Act sorts AI by risk.

Forbidden practices (since 2 February 2025): for example manipulation that causes harm, social scoring, emotion recognition at work or school (with narrow exceptions).

High-risk AI (for example in hiring, education, credit, essential services): strict rules for providers and duties for deployers, such as human oversight and logs.

Transparency (Article 50): people must be told when they chat with an AI, unless it is obvious; deepfakes and some AI-generated text must be labelled.

AI literacy (Article 4): take measures to support the AI skills of your team – like this course.

Other laws still apply too: GDPR, consumer law, copyright, non-discrimination.

Check before you use: facts, numbers, names, links, legal or medical statements.

Keep a human in charge of decisions about people (hiring, prices for a person, complaints).

Use only approved tools for company data and switch off training on your data where possible.

Be open: tell customers when they talk to a chatbot, and label AI images or text where required.

Write good prompts: give context, ask for sources, ask the tool to say when it is unsure.

Report problems: if AI produced something harmful or wrong, tell the responsible person.

A short written policy helps everyone follow the same rules and shows which measures you took. It should say: which AI tools are allowed and for what, which data must never go in, who checks AI output, how you inform customers, who is responsible, and how new staff learn the rules (for example with this course).

Download the template below, fill in the brackets and review it once a year.