AI Legal Compliance: Rules, Standards, and Third-Party Risk

AI Legal Compliance: Rules, Standards, and Third-Party Risk

This course is part of AI Governance and Compliance in Law Specialization

Instructor: Brian Trackman

What you'll learn

Apply the NIST AI Risk Management Framework and playbook to build an AI governance program, including AI inventories and use case profiles
Compare holistic and targeted AI regulation, including California, Colorado, and Illinois laws, to plan a multi-state compliance strategy
Assess third-party AI risk and use contract provisions such as indemnity to allocate risk without replacing your own oversight

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

11 assignments

Taught in English

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This course is part of the AI Governance and Compliance in Law Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 2 modules in this course

This course helps professionals turn AI governance principles into practical programs and compliance strategies. You will learn how the NIST AI Risk Management Framework and its playbook translate legal requirements into concrete tasks, including AI inventories and use case profiles. You will also explore how California, Colorado, and Illinois regulate AI, and how holistic and targeted regulatory models affect compliance planning. Finally, you will learn how to manage third-party AI risk, drawing on real-world case studies and contract provisions such as indemnity.

You will learn how the NIST AI Risk Management Framework helps organizations turn legal requirements into governance and compliance processes through use case profiles, the generative AI profile, and audit crosswalks. You will also learn how U.S. states such as California, Colorado, Texas, Utah, and Illinois regulate AI, including the differences between holistic and targeted approaches and the open question of federal preemption. Finally, you will learn how organizations can build a baseline governance architecture that supports both broad and sector-specific AI obligations.

What's included

6 videos1 reading5 assignments

6 videosTotal 49 minutes

Targeted AI Governance Frameworks11 minutes
State Regulation: the California Effect13 minutes
State Regulation: Colorado, Texas, and Utah10 minutes
State Regulation: Illinois and General Notes10 minutes
Summary Comparison: Holistic v Targeted AI Governance Frameworks4 minutes
A Message on Your Professional Development Paths1 minute

1 readingTotal 10 minutes

Pathways to Expand Your Legal Credentials10 minutes

5 assignmentsTotal 150 minutes

Knowledge Check: Target AI Governance Frameworks30 minutes
Knowledge Check: State Regulation: the California Effect30 minutes
Knowledge Check: State Regulation: Colorado, Texas, and Utah30 minutes
Knowledge Check: State Regulation: Illinois and General Notes30 minutes
Knowledge Check: Summary Comparison: Holistic v Targeted AI Governance Frameworks30 minutes

You will learn how to turn high-level AI governance principles into a working program using the NIST AI Risk Management Framework and its playbook, including how to build an AI system inventory. You will also learn how third-party AI tools, models, and data create risk, as illustrated by cases involving Apple, McDonald's, Workday, and Rite Aid, and how contract provisions such as indemnity help allocate risk without replacing your own governance and oversight.