AI Governance in Law Firms: Policies, Audits, and Risk Management

Law firms increasingly rely on artificial intelligence tools for legal research, drafting, client intake, document review, and internal operations. These tools can improve efficiency and consistency, but they also introduce new operational, data security, and risk management challenges. Many firms adopt AI informally, without defined policies, oversight structures, or internal review processes, which can expose the firm to avoidable risk.

In this program, Jeff Howell examines how law firms can actively govern AI use through practical, management-focused systems rather than ad hoc decision-making. The course focuses on how firm leadership can design and implement internal AI governance frameworks that establish accountability, standardize AI usage, and create defensible oversight practices. Participants will learn how to set governance leadership roles, draft enforceable AI policies, classify AI tools by risk level, evaluate vendors, conduct internal audits, and maintain ongoing monitoring and training programs.

The program equips attorneys and firm leaders with a structured approach to managing AI adoption as part of day-to-day law firm operations. Rather than treating AI as a one-time technology decision, the course frames governance as an ongoing management responsibility that supports innovation while protecting client interests and firm stability.

Learning Objectives:

1. Identify the core components of an effective AI governance framework for law firms
   
   
2. Explain how to structure leadership oversight and governance responsibility for AI use
   
   
3. Distinguish between high-risk, moderate-risk, and low-risk AI applications in legal practice
   
   
4. Evaluate AI vendors and tools using risk, security, and operational criteria
   
   
5. Describe how to implement internal AI audits and monitoring processes
   
   
6. Apply governance principles to manage operational risk while enabling responsible AI adoption