Article 4: AI literacy

Article 4 is a horizontal competence obligation: if you are a provider or deployer of an AI system, you must organise so that your staff and other people who operate or use AI on your behalf reach an appropriate level of AI literacy—as far as reasonably achievable (“to their best extent” in the English consolidated text).

The duty is contextual: you must account for people’s technical knowledge, experience, education, training, the context of use, and who is affected by the system.

Article 4 does not replace classification, data governance, logging, or transparency duties—it feeds proportionate implementation of those duties by ensuring people understand what the system does, when it fails, and where law draws red lines.

The term AI literacy is defined in Article 3 (point (56) in the consolidated numbering): skills, knowledge, and understanding enabling providers, deployers, and affected persons to deploy AI informedly, with awareness of opportunities, risks, and harm.

Article 4 operationalises that concept for providers and deployers through organisational measures. When you document compliance, cross-reference your training programme to both Article 4 and the Article 3(56) definition text on EUR-Lex.

• Article 1 — Subject matter: literacy supports trustworthy deployment called for in the Regulation’s aims.
• Article 2 — Scope: Article 4 applies where provider/deployer obligations already bite.
• Article 3 — Definitions: AI literacy (point (56)) and actor labels (provider, deployer).
• Article 5 — Training should cover red lines staff must not cross in sales or operations.
• Article 6 + Annex III — High-risk systems need documentation and oversight; literacy makes those controls real.
• Article 13 / Article 14 — Literacy underpins transparency to users and human oversight in practice.
• Article 113 — Application dates determine when Article 4 must be met for your pathway.

• Role-based curricula for engineering, product, legal, support, and leadership—mapped to Article 4 factors.
• Vendor playbook when outsourcers “operate” your AI: contractual literacy duties and audit rights.
• Affected-person lens: training for teams deploying AI in sensitive contexts (workers, patients, students, benefits claimants).
• Join with risk management: link literacy records to risk assessments and incident reviews.
• Refresh triggers: new model version, new geography, or post-incident lessons learned.
• Evidence: dated attendance, assessments, and policy acknowledgements stored like other compliance artefacts.

Editorial note: The following paragraph reproduces Article 4 as commonly cited from the English consolidated text of Regulation (EU) 2024/1689 on EUR-Lex. Always re-open EUR-Lex for the definitive wording and any later amendments before compliance decisions.

Providers and deployers of AI systems shall take measures to ensure, to their best extent, a sufficient level of AI literacy of their staff and other persons dealing with the operation and use of AI systems on their behalf, taking into account their technical knowledge, experience, education and training and the context the AI systems are to be used in, and considering the persons or groups of persons on whom the AI systems are to be used.

The recitals in the same consolidated AI Act on EUR-Lex often explain why competence-building obligations sit in Chapter I. Use the official preamble on EUR-Lex—do not rely on unofficial recital lists without checking sequence and wording against the authentic text.