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AI governance basics for working professionals
In this lesson
AI governance basics for working professionals
Explain why organizations establish AI governance policies by tracing their origins to frameworks such as the NIST AI Risk Management Framework's GOVERN function, which requires tr
You'll be able to
- Explain why organizations establish AI governance policies by tracing their origins to frameworks such as the NIST AI Risk Management Framework's GOVERN function, which requires transparent policies and procedures based on organizational risk priorities [^5], and to regulatory drivers including the EU AI Act's risk-based classification system [^1][^3].
- Classify AI systems according to the EU AI Act's high-risk categories, identifying which medical imaging applications, cloud-based services, or large language models fall under heightened regulatory obligations [^3][^4], and articulate how the Act conflates trustworthiness with acceptability of risk in its regulatory approach [^1].
- Apply NIST AI RMF GOVERN principles to workplace scenarios by establishing organizational practices that foster a critical thinking and safety-first mindset in AI system design, development, and deployment [^6], and by implementing transparent risk management processes aligned with organizational priorities [^5].
- Evaluate whether an organization's existing AI policies adequately address cross-sectoral risks common to activities such as acquisition, cloud-based AI services, or large language model deployment, using the NIST AI RMF's guidance on cross-sectoral profiles [^4].
- Create a compliance checklist for a hypothetical AI deployment that integrates both NIST AI RMF governance requirements [^5][^6] and EU AI Act obligations for high-risk systems [^3], demonstrating how sector-specific regulations shape organizational AI rules in practice.