Corporate AI Governance: The Policies Every Business Should Have

Course Description

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