AI Geletterdheid

AI literacy is more than just knowing what AI is. According to Article 3(56) of the EU AI Act, it includes: "skills, knowledge and understanding that allow providers, deployers and affected persons to make an informed deployment of AI systems and to gain awareness about the opportunities and risks of AI." Article 4 asks organizations to ensure "a sufficient level of AI literacy" for staff working with AI. This has applied since February 2, 2025 and remains in force. The Digital Omnibus (not yet law) softens the direct duty towards promoting and encouraging, but the value of literacy stays: it empowers people and reduces risk in everyday AI use.

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 original Digital Omnibus on AI proposal sought to amend Article 4: less emphasis on a direct organisational obligation and more emphasis on encouragement by the Commission and Member States. The EDPB and EDPS advised keeping the direct obligation for organisations. On 7 May 2026, the Council and European Parliament reached a provisional political agreement on the AI Act amendments, but the official agreement communication does not spell out Article 4 as a settled amendment. The practical line is therefore clear: do not claim AI literacy has disappeared. Until a formal amendment applies, the current AI Act remains in force, and training remains necessary for responsible use, risk management and demonstrable governance.