What the model cannot know
Knowledge cutoffs, no access to internal systems, and the fact that a confident answer is not a checked answer.
Read the guide →This is the obligation most organisations are quietly failing without knowing it, and also the easiest one to satisfy.
Article 4 originally required organisations to ensure a sufficient level of AI literacy among staff and others using AI on their behalf. The wording changed on 27 July 2026. The duty is now to take measures to support the development of AI literacy, and the text states explicitly that nobody has to guarantee any particular level of ability in any individual.
That difference is real. This is an obligation of effort. You have to do something sensible and be able to show that you did. You do not have to prove that every employee reached a measured standard.
The duty covers staff, and in addition other people operating AI on the organisation's behalf, which can reach contractors and service providers. The breadth here rests on Commission guidance as reported by several legal practices rather than on text we verified directly, so confirm it against the primary source if it becomes decisive for you.
This is not an official template. It is a reasonable reading of an effort-based obligation, arranged so it is easy to evidence.
Write down which AI tools are actually in use, in which roles, for which tasks. Shadow use through personal accounts belongs on the list too.
The marketing team needs something different from the engineers. A short internal session on what the tool is good at, how it fails, and what must never be pasted in covers most of the risk.
What is allowed, what must never go in, who to ask, and how published content gets marked.
Date, participants, topics. Documentation is not itself required here, but it is the simplest way to show the duty was taken seriously.
A new tool, a new model generation or a new use case are the natural triggers. Once a year is a reasonable baseline.
The regulation says nothing about curriculum. Based on what actually goes wrong in practice, these topics return the most value.
Knowledge cutoffs, no access to internal systems, and the fact that a confident answer is not a checked answer.
Read the guide →Personal data, passwords, keys, trade secrets and client material in tools with no agreement behind them.
Read the guide →Source requirements, separating findings from inference, and a routine simple enough to actually run.
Read the guide →Chatbots, images and published text. The duties start applying on 2 August 2026.
Read the guide →Why a web page or an email can hijack an AI tool that has been given access to something.
Read the guide →Emotion inference on staff and students is prohibited, however well the tool appears to work.
Read the guide →