Getting Started with AI: Free and Entry-Level Training
If you have been told your organisation needs AI literacy and you are not sure what that means, this page is the short version. It covers what is worth learning first, what can wait, and where to start without committing to anything.
What AI literacy actually means
The term comes from Article 4 of the EU AI Act, but the underlying idea is not a legal one. The European Commission and the OECD have converged on a similar description: the combination of knowledge, skills and judgement that lets someone use AI systems appropriately, understand what they produce, and recognise where they should not be relied on.
Note what is absent from that. It does not mean knowing how a model works internally. It does not require a technical background. It is closer to the competence you would expect of someone using any other unfamiliar professional tool.
What to learn first
In roughly this order, because each one makes the next more useful:
- What these tools are doing. Enough to understand why they produce confident wrong answers, which is the single most useful thing a new user can grasp.
- How to ask well. Most disappointing output is a badly framed request. This is learnable in an afternoon and pays back immediately.
- Where the limits are. Which tasks these tools are genuinely good at, and which they should not be near.
- What not to put in. Confidential, personal and commercially sensitive material, and why the distinction matters.
- How to check output. Verification habits that fit the work rather than a general instruction to be careful.
What can wait: model architectures, the finer points of the risk classification system, and anything about building AI systems, unless that is what your organisation does.
Matching training to roles
Article 4 asks for measures that take account of technical knowledge, experience, education and the context of use. That is a strong hint that one session for everyone is the wrong shape.
Three broad groups usually emerge. People who use AI occasionally for drafting and summarising need the fundamentals and the confidentiality rules. People whose decisions are informed by AI output need those plus real depth on limits and verification. People selecting or configuring tools need the governance layer as well, covered in our guide on provider and deployer roles.
Starting without committing
There is a reasonable case for starting free. It tells you where your team actually is before you spend anything, and it gives people a low-stakes way to try the tools rather than reading about them.
The AI Essentials course covers the fundamentals above in a structured form, and there is a free AI course for teams that want to start at no cost. Irish learners can browse the full listing at BH Courses Ireland.
After the basics
Once the fundamentals are in place, the useful next step depends on the work. For compliance, that is the Article 4 obligation, covered in our guide to AI literacy. For customer-facing teams, the transparency rules that took effect in August 2026 are covered in using AI in marketing.