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AI Policies for Business Clients: The Document Every Company Needs and Most Don't Have

Credits Available
Credit Status Total
Alaska CLE Reciprocity 1 Total
Alabama CLE Approved 1 Total
Arkansas CLE Approved 1 Total
Arizona CLE Approved 1 Total
California CLE Approved 1 Total
Colorado CLE Approved 1 Total
Connecticut CLE Approved 1 Total
Delaware CLE Approved 1 Total
Florida CLE Approved 1 Total
Georgia CLE Approved 1 Total
Hawaii CLE Approved 1 Total
Iowa CLE Approved 1 Total
Illinois CLE Approved 1 Total
Indiana CLE Approved 1 Total
Maine CLE Approved 1 Total
Missouri CLE Approved 1.2 Total
Northern Mariana Islands CLE Approved 1 Total
Montana CLE Approved 1 Total
North Carolina CLE Approved 1 Total
New Hampshire CLE Approved 1 Total
New Jersey CLE Approved 1.2 Total
New Mexico CLE Approved 1 Total
Nevada CLE Approved 1 Total
New York CLE Approved 1 Total
Ohio CLE Approved 1 Total
Oklahoma CLE Approved 1 Total
Oregon CLE Approved 1 Total
Pennsylvania CLE Approved 1 Total
Tennessee CLE Approved 1 Total
Texas CLE Approved 1 Total
Virginia CLE Approved 1 Total
Vermont CLE Approved 1 Total
Washington CLE Approved 1 Total
Wisconsin CLE Approved 1 Total
West Virginia CLE Approved 1.2 Total
OnDemand
58 minutes
Andrew Eichen
With Andrew Eichen from ZwillGen PLLC
Recorded April 28, 2026.
Product ID 102363

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$199

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Overview

Your Clients Are Already Using AI. Help Them Do It Safely!

AI tools are already embedded in your business clients' daily operations - drafting, analyzing, deciding. And yet, many companies have no written policy governing any of it. This course gives you the frameworks to assess client exposure, draft AI use policies that hold up, and avoid the pitfalls that make a bad policy worse than none. From red teaming and liability gaps to rollout mechanics and enforcement, you'll leave better prepared to protect your business clients. Register today!

  • Identify hidden AI liabilities before your clients do.
  • Know what every effective AI policy must include.
  • Spot the drafting mistakes that create false protection.
  • Tailor policies across industries, sizes, and risk profiles.
  • Turn a client conversation into a billable, high-value engagement.

Abbreviated Agenda

  1. Assessing Current AI Use/Adoption and Exposure
    1. Current State of AI Law and Liability
    2. Current Legal Exposure Risks Without a Policy - and With a Bad One
    3. Analyzing Your Client's Current Workflows
    4. Red Teaming: AI Agents and MCP Exposure
  2. AI Use Policies: Key Components They Must Have
    1. Expressly Acceptable Uses and Tools and Prohibited Uses
    2. Data Handling and Confidentiality
    3. IP Ownership and Output Rights
    4. Human Oversight Requirements
    5. Vendor Vetting Standards
    6. Incident Response
    7. Training Obligations
  3. Tailoring and Implementation: What Distinguishes a Bad Policy From an Effective One
    1. Adjusting for the Client's Industry, Size, Unique Assets, Customers, Processes, etc.
    2. Integrating With Existing Policies (Employment, IT, IP, etc.)
    3. Rollout Mechanics: Training, Enforcement, Version Control
  4. Practical Drafting Tips and Common Pitfalls

Related Topics

Product ID 102363

Credit Details

Credits Available
Credit Status Total
Alaska CLE Reciprocity 1 Total
Alabama CLE Approved 1 Total
Arkansas CLE Approved 1 Total
Arizona CLE Approved 1 Total
California CLE Approved 1 Total
Colorado CLE Approved 1 Total
Connecticut CLE Approved 1 Total
Delaware CLE Approved 1 Total
Florida CLE Approved 1 Total
Georgia CLE Approved 1 Total
Hawaii CLE Approved 1 Total
Iowa CLE Approved 1 Total
Illinois CLE Approved 1 Total
Indiana CLE Approved 1 Total
Maine CLE Approved 1 Total
Missouri CLE Approved 1.2 Total
Northern Mariana Islands CLE Approved 1 Total
Montana CLE Approved 1 Total
North Carolina CLE Approved 1 Total
New Hampshire CLE Approved 1 Total
New Jersey CLE Approved 1.2 Total
New Mexico CLE Approved 1 Total
Nevada CLE Approved 1 Total
New York CLE Approved 1 Total
Ohio CLE Approved 1 Total
Oklahoma CLE Approved 1 Total
Oregon CLE Approved 1 Total
Pennsylvania CLE Approved 1 Total
Tennessee CLE Approved 1 Total
Texas CLE Approved 1 Total
Virginia CLE Approved 1 Total
Vermont CLE Approved 1 Total
Washington CLE Approved 1 Total
Wisconsin CLE Approved 1 Total
West Virginia CLE Approved 1.2 Total
Select Jurisdiction
CLE

Agenda

All times are shown in

  1. AI Policies for Business Clients: The Document Every Company Needs and Most Don't Have

    1. Assessing Current AI Use/Adoption and Exposure
      1. Current State of AI Law and Liability
      2. Current Legal Exposure Risks Without a Policy - and With a Bad One
      3. Analyzing Your Client's Current Workflows
      4. Red Teaming: AI Agents and MCP Exposure
    2. AI Use Policies: Key Components They Must Have
      1. Expressly Acceptable Uses and Tools and Prohibited Uses
      2. Data Handling and Confidentiality
      3. IP Ownership and Output Rights
      4. Human Oversight Requirements
      5. Vendor Vetting Standards
      6. Incident Response
      7. Training Obligations
    3. Tailoring and Implementation: What Distinguishes a Bad Policy From an Effective One
      1. Adjusting for the Client's Industry, Size, Unique Assets, Customers, Processes, etc.
      2. Integrating With Existing Policies (Employment, IT, IP, etc.)
      3. Rollout Mechanics: Training, Enforcement, Version Control
    4. Practical Drafting Tips and Common Pitfalls

Who Should Attend

This legal course is designed for attorneys. CTOs, directors, and paralegals will also benefit.

Speakers

Andrew Eichen
Andrew
Eichen
ZwillGen PLLC
Speaker bio
Andrew Eichen

Andrew Eichen

ZwillGen PLLC
Andrew Eichen

is an attorney at ZwillGen PLLC. He helps clients navigate the regulatory and strategic challenges of artificial intelligence. With a background in law, finance, and public policy, he advises clients on responsible AI deployment and compliance under emerging frameworks including the EU AI Act, Colorado AI Act, and NYC Local Law 144. He designs practical governance programs that help companies operationalize regulatory compliance and minimize deployment risk. His experience includes drafting internal policies aligned with the NIST AI Risk Management Framework, developing vendor assessment frameworks, and building AI-specific incident response plans. Andrew also advises clients on system-specific risks and AI-related contract terms for SaaS and enterprise applications. Prior to joining ZwillGen, he was an associate at Venable LLP, where he advised financial institutions and fintech companies on banking regulations and payment processing. He earned his J.D. degree, magna cum laude, from the University of Pennsylvania Law School, where he was inducted into the Order of the Coif and received the graduating prizes for Excellence in Business Law, Best Paper in Law and Economics, and Outstanding Trial Advocacy Abilities. During law school, he focused his studies on technology law, serving as a research assistant to Professor Christopher S. Yoo, a leading authority on internet law, and as a senior editor of the Journal of Law and Innovation. He also holds a Master of Public Policy from Georgetown University's McCourt School of Public Policy, where he was named a McCourt Scholar, the school's most prestigious merit scholarship. His AI-focused coursework included studies with Professor Paul Ohm, and his research on AI in higher education earned the award for Most Outstanding Thesis. He earned his Bachelor of Science in Business Administration, magna cum laude, from Washington University's Olin Business School, with double majors in finance and entrepreneurship.

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