University of Illinois Urbana-Champaign

AI Governance and Compliance in Law Specialization

University of Illinois Urbana-Champaign

AI Governance and Compliance in Law Specialization

Gain a Legal Edge in AI Governance.

Classify AI systems, assess vendor risk, evaluate audits, and plan compliant AI deployments.

Brian Trackman

Instructor: Brian Trackman

Get in-depth knowledge of a subject
Beginner level

Recommended experience

4 weeks to complete
at 4 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Beginner level

Recommended experience

4 weeks to complete
at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Classify AI systems by risk tier and map high-risk systems to compliance pathways under frameworks such as the EU AI Act.

  • Analyze gaps in vendor AI integrations and evaluate audit results to judge compliance maturity.

  • Create AI deployment plans that align regulatory requirements with organizational goals, including ongoing monitoring.

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Taught in English
Recently updated!

October 2026

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Specialization - 4 course series

What you'll learn

  • Explain what AI is, how it evolved, and the benefits, risks, and real-world failures that drive the need for AI governance and compliance

  • Identify the goals and core pillars of AI governance, including safety, security, fairness, accountability, transparency, and privacy

  • Apply governance objectives, lifecycle stages, and targets to AI systems, and distinguish a governance mindset from a compliance mindset

Skills you'll gain

Category: Responsible AI
Category: Compliance Management
Category: Governance
Category: Regulatory Compliance
Category: AI literacy
Category: Artificial Intelligence
Category: Ethical Standards And Conduct
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: AI Security
Category: Continuous Monitoring
Category: Accountability
Category: Legal Risk
Category: Governance Risk Management and Compliance
Category: Law, Regulation, and Compliance

What you'll learn

  • Analyze the current state of AI governance, including sources of authority, standards, and the role of social license in sustainable AI.

  • Explain how the EU AI Act classifies AI systems by risk and how its requirements and enforcement shape global compliance.

  • Apply the NIST AI Risk Management Framework's govern, map, measure, and manage functions to identify and reduce AI risk.

Skills you'll gain

Category: Governance
Category: Regulatory Compliance
Category: Technical Standard
Category: Regulation and Legal Compliance
Category: Compliance Management
Category: Artificial Intelligence
Category: Risk Management
Category: Responsible AI
Category: Governance Risk Management and Compliance
Category: Regulatory Requirements
Category: Risk Management Framework
Category: Law, Regulation, and Compliance

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

Category: Governance
Category: Risk Management Framework
Category: Legal Risk
Category: Artificial Intelligence
Category: Law, Regulation, and Compliance
Category: Vendor Management
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Regulatory Requirements
Category: Vendor Contracts
Category: Regulatory Compliance
Category: Auditing
Category: Responsible AI
Category: Compliance Management
Category: Regulation and Legal Compliance
Category: Supplier Risk Management
Category: Governance Risk Management and Compliance
Category: Generative AI
AI Legal Governance: Audit, Accountability, & Tradeoffs

AI Legal Governance: Audit, Accountability, & Tradeoffs

Course 4, 11 hours

What you'll learn

  • Implement AI governance using acceptance criteria, error and risk tolerance, and the NIST AI RMF to address risks like shadow AI.

  • Evaluate AI systems through audits, model drift monitoring, conformity assessments, and audit deliverables that build an audit trail.

  • Analyze how the precautionary and innovation principles shape AI policy, regulation, and organizational decisions across jurisdictions.

Skills you'll gain

Category: Governance
Category: Law, Regulation, and Compliance
Category: Regulation and Legal Compliance
Category: Artificial Intelligence
Category: Compliance Auditing
Category: Compliance Management
Category: Accountability
Category: Accountability Frameworks
Category: Internal Auditing
Category: Agentic systems
Category: Operational Risk
Category: Legal Risk
Category: Governance Risk Management and Compliance
Category: Enterprise Risk Management (ERM)
Category: Regulatory Requirements
Category: Risk Management Framework
Category: Regulatory Compliance
Category: Innovation
Category: Auditing
Category: Responsible AI

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Instructor

Brian Trackman
University of Illinois Urbana-Champaign
4 Courses77 learners

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