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AI Governance Fundamentals: Framework, Templates & Sprint
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AI Governance Fundamentals: Framework, Templates & Sprint

About this course

Your organization is already using AI. The question is whether anyone is governing it.78% of employees admit to using AI tools their employer never approved. Over a third are sharing confidential data with those tools. AI incidents are up 56% year over year. And only 34% of organizations have a governance framework.This course is designed to help you start closing that gap.What makes this course different:● Built by someone who has governed AI in regulated industries, not by someone who read about it● Covers the 2026 White House National AI Legislative Framework alongside existing regulations● Practical, not theoretical: includes five ready-to-use templates, not just concepts● Running scenario (Meridian Consulting) that makes every framework concrete and applicable● Hands-on assignments where you build governance artifacts for your own organization● AI-powered role play scenarios where you rehearse real governance conversations● 15 years of regulated finance experience (Citi, JPMorgan, Bloomberg) distilled into a focused courseWhat you will learn:● What AI governance actually is (and the five things it is NOT)● The three pillars: visibility, accountability, and oversight● Seven categories of AI risk with real-world failure examples● How to build an AI inventory and discover shadow AI● How to score risk across seven categories using a practical matrix● How to draft an acceptable use policy your employees can understand and follow● How to assign accountability using a RACI matrix● The EU AI Act phased timeline and what it means for your organization● The three layers of US AI regulation: state laws, federal agency guidance, and the national legislative framework● NIST AI RMF vs ISO/IEC 42001: which framework to adopt and why● Industry-specific requirements for financial services, healthcare, lega

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What you'll learn

  • Understand what AI governance is and the common misconceptions around it
  • Identify and assess AI risks through practical frameworks
  • Draft an acceptable use policy for AI tools
  • Develop a governance framework incorporating visibility, accountability, and oversight
Artificial Intelligence #risk management #data privacy #compliance #accountability #ai governance #ai risk assessment #regulatory frameworks #visibility #oversight #acceptable use policy #governance templates
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