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Corporate AI Governance: The Policies Every Business Should Have (On-Demand)

Original Course Date: August 14, 2026

AI tools have increasingly become a part of everyday business operations, often faster than the policies meant to govern them. As a result, many companies have significant AI deployments, frequently with no rules in place to govern how AI systems are procured, built, or used. More and more businesses need a real governance framework for AI, and many are turning to lawyers to build it.

This course walks through the documents that make up a corporate AI governance program and how to assemble them into a working framework. The session will explain the purpose of each document, what they cover, as well as how to customize them depending on a company’s size, industry, and operations. Participants will walk away with a practical framework for advising any business that needs to put AI governance in place.

Principles

  • The legal risks businesses face when they use AI without governance in place
  • The core documents of a corporate AI governance program and what each one does
  • Setting the rules through an AI policy, internal standards, and an employee acceptable use policy
  • How to screen AI vendors, plan for AI incidents, and assess the risk of each AI system
  • Guidance for tailoring a program to a client’s size and industry
  • Key drafting mistakes to avoid when developing an AI governance program

Syllabus

  1. The Importance of AI Governance
    • What an AI governance program is and what purpose it serves
    • The risks of deploying AI without governance structures in place
    • Relevant legal and industry standards
  2. The Core Documents: Policy, Standards, and Acceptable Use
    • The AI governance policy: principles, roles, and core rules
    • Standards: procedures for managing AI across its lifecycle
    • The acceptable use policy: approved tools, data handling, output review, and prohibited uses
  3. Managing Vendor, Incident, and Classification Risk
    • Vendor screening questionnaires and the contract terms they drive
    • Incident response for AI-specific failures
    • Risk assessment and classifying AI systems
  4. Customizing an AI Governance Framework
    • How a company’s size, industry, and existing policies impact AI governance
  5. Common Pitfalls and First Steps
    • Common drafting mistakes
    • Where to start in developing an AI governance framework