Governance

Competence

Development of AI-related skills including ethical reflection.

How the laws define this

Both instruments establish that competence fundamental to artificial intelligence relies on combining knowledge and skills to achieve intended, effective results. Where they diverge is in their target scope, specific applications, and ethical dimensions. In the North Rhine-Westphalia AI Strategy Paper 2.0 (KI-Strategiepapier NRW 2.0), competence is tailored to university staff and students using generative AI in higher education, explicitly incorporating ethically reflective action along with support measures like training, consulting, networking, and curricular adjustments to foster responsible use. Conversely, ISO/IEC 42006:2025 narrows its focus strictly to the specialized expertise of auditors who evaluate AI management systems, defining competence as the practical ability to apply skills and knowledge to deliver thorough and credible audit evaluations. Thus, while one framework addresses broader educational and ethical application for users, the other treats competence as a technical prerequisite for professional auditing and management system certification.

Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.

How jurisdictions differ

What is distinctive in each definition, binding law in force first.

JurisdictionInstrumentStatusWhat is distinctive
ISOISO/IEC 42006:2025 — Information technology — Artificial intelligence — Requirements for bodies providing audit and certification of artificial intelligence management systemsIn ForceFocuses on auditors' ability to apply knowledge and skills for assessing AI management systems, unlike the broader educational context in the other.
North Rhine-Westphalia, GermanyNorth Rhine-Westphalia AI Strategy 2.0In ForceLimits competence to university staff and students' skills, knowledge, and ethical reflection for responsible generative AI use in higher education.

What it triggers

  • North Rhine-Westphalia AI Strategy 2.0 calls for competence through training, consulting, networking, and curricular measures in higher education.source

Definitions (2)

The combination of skills, knowledge, and ethically reflective action among university staff and students regarding AI; encompasses training, consulting, networking, and curricular measures to ensure responsible and effective use of generative AI in higher education.

Competence refers to the ability to apply knowledge and skills to achieve intended results, particularly for auditors assessing AI management systems. It ensures that auditors possess the specialized expertise required for thorough and credible evaluations of AI systems.

Not to be confused with

AI competencies

AI competencies refer to a general set of knowledge, skills, and ethics for working with AI, while competence here is contextualized to specific professional or educational roles.

Talent

Talent emphasizes the human resources and skills base for AI development, whereas competence focuses on applied abilities and ethical reflection in auditing or education.

professionalisation

Professionalisation involves developing a recognised assurance profession, differing from competence as the specific abilities required within such roles.

Questions and answers

How does the North Rhine-Westphalia AI Strategy address competence?

It combines skills, knowledge, and ethical reflection for university staff and students. Measures include training, consulting, networking, and curricular integration for responsible generative AI use.

How do these definitions of competence differ?

The ISO definition targets auditors' expertise in AI management system assessments. The strategy definition applies to higher education contexts with ethical and practical training.