EU AI Act Article 4: What the AI Literacy Requirement Actually Demands

Article 4 of the EU AI Act requires providers and deployers of AI systems to support the AI literacy of their staff and commissioned third parties. This obligation applies regardless of whether a system is classified as high-risk or minimal risk. Anyone using AI in their company must ensure that users understand the opportunities, risks, and limitations of the technology. The legislator does not demand a rigid certificate, but rather measures that are appropriate to the technical prior knowledge of the users and the specific application scenario.

Who is affected by Article 4 since February 2025

Every company that provides or operates AI systems on the Union market has been subject to this obligation since February 2, 2025. This applies not only to internal employees but explicitly also to external staff and freelancers who handle AI systems on behalf of the company. The legal text makes no exceptions for small and medium-sized enterprises here. The context is decisive: someone using a system for automated document processing needs a different level of competence than someone making AI-supported personnel decisions. The regulatory supervisory authority for enforcing this obligation by national market surveillance authorities takes effect from August 2, 2026.

The real penalties for lacking AI literacy

The law does not provide for direct fines for an isolated violation of Article 4. Circulating claims about penalties of up to 15 million euros or 3 percent of annual turnover specifically for lacking AI literacy are false and cannot be substantiated by Article 99 on sanctions. However, this does not mean the all-clear. The danger lies in the indirect risk: if there is a violation of other provisions of the regulation, such as human oversight, authorities will examine AI literacy. If training or guardrails are missing here, this is considered an indication of gross negligence, which leads to massive problems in liability lawsuits.

How the Digital Omnibus changed the legal text

Since July 27, 2026, companies no longer have to guarantee a specific level of competence, but only support its development. The Digital Omnibus Regulation softened the wording of Article 4. The strict obligation to ensure a sufficient level became the obligation to take measures to support AI literacy. The European Commission provides a non-binding repository with examples of training and awareness measures for this purpose. However, merely copying these examples does not guarantee legal compliance.

How to technically anchor AI literacy in systems

Training alone is not enough if the systems themselves operate as a black box and users cannot comprehend decisions. In the practice of applied AI systems, governance is therefore built directly into the tools. In concrete terms, this means: answers and data points must be provided with a source reference so that humans can verify the origin of an information. When processing documents or analyzing business data, orchestrators decide in multiple stages what passes through automatically and what is submitted for manual review. Through tiered autonomy (Level 0 to 4) and the "approval-first" principle, it is ensured that critical actions such as price changes or orders do not fire without human approval. In this way, the required human oversight is systemically enforced and logged.

What managing directors must check now

The review begins with the question of who in the company actually uses AI systems and whether this use is controlled in a traceable manner. It is not enough to store a PDF with guidelines on the intranet. Companies must document which systems are in use, who operates them, and how the staff is empowered to do so. Since sensitive data must remain within a defined framework, the technical infrastructure is also relevant, such as the use of models via EU endpoints. Those who take the requirements of Article 4 seriously do not rely on the gut feeling of their employees, but implement systems that inherently provide transparency, source references, and approval processes.