AI Literacy

AI literacy is more than knowing what AI is. Article 3(56) covers the skills, knowledge and understanding that help providers, deployers and affected persons use AI in an informed way and understand opportunities, risks and potential harm. Article 4 of the EU AI Act has applied since 2 February 2025. Since 27 July 2026, providers and deployers must take measures to support the development of AI literacy. Those measures should reflect technical knowledge, experience, education, the context of use and affected persons. The law does not require a specific individual level, standard course or certificate.

An AI-literate professional masters four core competencies: 1) UNDERSTAND - Fundamental understanding of how AI works: difference between AI/ML/generative AI, how training data affects output, what AI can and cannot do, basics of LLMs. 2) EVALUATE - Critical assessment: recognizing hallucinations and errors, identifying bias, assessing reliability, understanding risks and limitations. 3) APPLY - Responsible deployment: effective prompting, privacy-conscious use, compliance with regulations, making ethical considerations. 4) COMMUNICATE - Effectively convey: making AI use transparent, explaining to colleagues, informing stakeholders, documenting AI decisions.

The EU AI Act distinguishes levels by role. MANAGEMENT & BOARD (strategic level): understanding AI governance, risks and strategic implications - CEO, CTO, directors, AI Ethics Board. AI USERS (operational level): working with AI tools daily, assessing output, responsible use - customer service, marketing, HR, legal. COMPLIANCE & RISK (control level): overseeing AI use, monitoring risks, ensuring compliance - compliance officers, risk managers, DPOs, internal audit. DEVELOPERS & IT (technical level): deep knowledge of AI systems and technical compliance requirements - data scientists, ML engineers, developers, IT architects.

The Dutch Data Protection Authority recommends a multi-year action plan in 4 steps. STEP 1 - INVENTORY (Week 1-2): Map AI systems including purpose, degree of autonomy and impact. Document who works with them and current knowledge level. STEP 2 - SET GOALS (Week 3-4): Define measurable goals per risk domain. Assign responsibilities. Present to board for commitment. STEP 3 - IMPLEMENT (Month 2): Start role-specific training. Publish AI use register internally. Write culture/vision document. STEP 4 - EVALUATE (Month 3+): Discuss results in management team, analyze residual risk, adjust goals. Include in management reporting. AI literacy is not a one-time event but an ongoing organizational capability.

AI literacy is more than a compliance checkbox. LEGAL GOVERNANCE: show how you apply Article 4 in a risk-based way per role, system and context. RISK MANAGEMENT: prevent data breaches, bias incidents and reputation damage through employees who understand AI risks. MORE EFFECTIVE AI ADOPTION: teams that understand AI get more value and make fewer mistakes. INNOVATION CAPACITY: AI-literate employees see opportunities others miss and can meaningfully apply AI. EMPLOYEE SATISFACTION: investing in AI skills gives confidence and perspective in a changing work environment. COMPETITIVE ADVANTAGE: AI-literate teams move faster and more responsibly than competitors.

The Digital Omnibus on AI was adopted as Regulation (EU) 2026/1744 and applies since 27 July 2026. Article 4 remains an obligation for providers and deployers, but its wording changed. Organisations must take measures to support the development of AI literacy. They do not have to guarantee a specific individual level. Training can be appropriate, but the law does not prescribe a standard training or certificate.