CEN/CENELEC CWA 18398:2025
The vocabulary this network runs on
KROG evaluates competence against a published European standard rather than a private rubric. These pages are that standard, rendered directly from the same data files the matching engine reads. Nothing here is a summary written by hand.
37 role profiles
Grouped into the standard's 5 families. Each role states its competences with required levels, its EQF level, the AI Act actor contexts it operates in, and its skill areas.
41 e-CF competences
Areas A–E, and for each competence the levels it actually defines — the rule that decides whether a requirement can be written at all. 2 are scoped out of this CWA.
The matrix
Annex I: roles across, competences down, the required level in the cell. The clearest single artefact the standard has.
37 educational profiles
Specifications, not offers: the standard specifies a programme per role. KROG does not deliver these. 23 further standard-based courses are specified alongside them.
The five levels
e-1 to e-5 by autonomy, context complexity and accountability — and the evidence floor each level implies before a claim may be shown as verified.
Skill areas
47 areas classify what a role works on, independently of the competences it must hold.
- Data Analytics
- Data Modelling
- Data Engineering
- Data Quality & Governance
- Data Privacy Engineering
- Synthetic Data Generation
- Machine Learning
- Deep Learning
- Natural Language Processing
- Generative AI
- Computer Vision
- AI Platforms & Frameworks
- AI Infrastructure
- AI Tooling & Ecosystem
- AI System Architecture & Enterprise Integration
- AI Automation
- AI Solution Architecture
- MLOps & AI Lifecycle Management
- Model Evaluation & Validation
- Testing AI-based systems
- AI Performance Monitoring
- Model Optimisation & Efficiency
- Explainability & Interpretability (XAI)
- AI Security
- Safe, Responsible & Sustainable AI
- Human-Model Interaction Design
- Prompt Engineering
- AI Strategy
- AI Market & Technology Intelligence
- AI Business Application & Impact
- AI Value Measurement & ROI
- AI Economics & Cost Management
- AI Product Management
- Project & Program Management of AI Initiatives
- Operating Model Design for AI
- Vendor & Partner Management for AI
- Change Management for AI
- AI Adoption & Enablement
- AI Governance
- Model Risk Management (MRM)
- Third-Party & Supply Chain AI Risk
- AI Ethics
- AI Risk, Assurance & Audit
- AI Incident Management & Response
- AI Policy & Regulation
- AI Compliance & Regulatory Readiness
- Regulatory Reporting & Documentation