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Overview
Your Company Is Already Using AI - Here’s What Legal Needs to Fix
AI isn't waiting for you to catch up. Business teams are adopting AI tools faster than legal can review them, vendors are quietly embedding AI into products the company already uses, and executives are asking, "Are we covered?" For a legal department, this creates a governance gap that's hard to close reactively.
This practical CLE gives a clear and current roadmap for managing the legal risks that come with business AI adoption. Find out which contract clauses and legacy templates need an AI rewrite, uncover shadow AI and hidden vendor risks, strengthen governance and employee-use policies, and protect privilege, trade secrets, and sensitive company data. Then turn AI from a risk to a resource with practical ways to use it for contract review, research, drafting, and routine legal work. Protect the company and get on top of the AI issues already landing on your desk—register today!
- Spot the AI terms hiding in vendor contracts, SaaS agreements, NDAs, and other legacy templates.
- Protect company IP, trade secrets, confidential information, and privilege when employees and vendors use AI.
- Uncover shadow AI, hidden vendor risks, and insurance gaps before they become bigger legal problems.
- Build AI governance and employee-use policies that address the risks companies are facing now.
- Navigate emerging employment, consumer, and state AI requirements.
- Put AI to work in-house with practical prompts for contract review, research, drafting, NDA triage, and more.
Abbreviated Agenda
- Contract Clauses You Need to Review and Rewrite Today
- Find the AI Risk Before It Finds You: Due Diligence and Insurance
- Governance and AI Policies: Urgent Questions and Best Practices
- Protecting Privilege, Trade Secrets, and Company Data
- The Regulatory Minefield: Employment, Consumer, and Emerging AI Rules
- Practical AI for In-House Counsel: With Sample Prompts
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Credit Details
Credits Available
| Credit | Status | Total |
|---|---|---|
| Alaska CLE |
|
4 Total |
| Arkansas CLE |
|
4 Total |
| Arizona CLE |
|
4 Total |
| California CLE |
|
4 Total |
| Colorado CLE |
|
5 Total |
| Connecticut CLE |
|
4 Total |
| Delaware CLE |
|
4 Total |
| Florida CLE |
|
5 Total |
| Georgia CLE |
|
4 Total |
| Hawaii CLE |
|
4 Total |
| Iowa CLE |
|
4 Total |
| Idaho CLE |
|
4 Total |
| Illinois CLE |
|
4 Total |
| Indiana CLE |
|
4 Total |
| Kansas CLE |
|
4.5 Total |
| Kentucky CLE |
|
4 Total |
| Louisiana CLE |
|
4 Total |
| Maine CLE |
|
4 Total |
| Minnesota CLE |
|
4 Total |
| Missouri CLE |
|
4.8 Total |
| Northern Mariana Islands CLE |
|
4 Total |
| Mississippi CLE |
|
4 Total |
| Montana CLE |
|
4 Total |
| North Carolina CLE |
|
4 Total |
| North Dakota CLE |
|
4 Total |
| Nebraska CLE |
|
4 Total |
| New Hampshire CLE |
|
4 Total |
| New Jersey CLE |
|
4.8 Total |
| New Mexico CLE |
|
4 Total |
| Nevada CLE |
|
3 Total |
| New York CLE |
|
4.5 Total |
| Ohio CLE |
|
4 Total |
| Oklahoma CLE |
|
5 Total |
| Oregon CLE |
|
4 Total |
| Pennsylvania CLE |
|
4 Total |
| Rhode Island CLE |
|
4.5 Total |
| South Carolina CLE |
|
4 Total |
| Tennessee CLE |
|
4 Total |
| Texas CLE |
|
4 Total |
| Utah CLE |
|
4 Total |
| Virginia CLE |
|
4 Total |
| Vermont CLE |
|
4 Total |
| Washington CLE |
|
4 Total |
| Wisconsin CLE |
|
4.5 Total |
| West Virginia CLE |
|
4.8 Total |
| Wyoming CLE |
|
4 Total |
| Arizona CPE for Accountants |
|
4.5 Total |
| New York CPE for Accountants |
|
3.5 Total |
| Washington CPE for Accountants |
|
4.5 Total |
| Wisconsin CPE for Accountants |
|
4.8 Total |
| HRCI |
|
4 Total |
| CPE for Accountants/NASBA |
|
4.5 Total |
| SHRM CP/SCP |
|
4 Total |
Select Jurisdiction
CLE
Other
Agenda
-
Contract Clauses You Need to Review and Rewrite Today
- Reviewing and Negotiating AI Vendor Agreements
- Your Old Templates Have an AI Problem: Retrofitting NDAs and More With AI-Specific Carve-Outs
- Who Owns What AI Helped Build? Protecting Company IP and Work Product
- AI Is Hiding in Your SaaS Agreements: Terms You May Be Overlooking
- Indemnity, Liability Caps, and Risk Allocation
-
Find the AI Risk Before It Finds You: Due Diligence and Insurance
- Where AI Is Already Embedded in the Business (Often Without Legal's Knowledge)
- Finding and Managing Shadow AI
- AI Risk Due Diligence in M&A
- Insurance and AI: Reviewing Policies for AI-Related Gaps
- When AI Goes Wrong: Incident Response Planning
-
Governance and AI Policies: Urgent Questions and Best Practices
- AI Oversight at the Board Level – What Boards Are Starting to Ask
- Director and Officer Liability in the Age of AI: Fiduciary Duty Questions and Answers
- AI Governance Policy Design Best Practices
- The Employee-Facing AI Use Policy: What Goes In, What Gets You Sued if It's Missing
-
Protecting Privilege, Trade Secrets, and Company Data
- AI and Attorney-Client Privilege: When Does Tool Use Put Protection at Risk?
- Confidentiality and Trade Secret Leakage From AI Tool Use
- The Company's AI Use Is Discoverable: Preservation, Discovery, and Litigation Risks and Obligations
-
The Regulatory Minefield: Employment, Consumer, and Emerging AI Rules
- Employment AI: Bias, Discrimination, and Disparate-Impact Risk
- Consumer Transparency and Disclosure Requirements
- California's Automated Decisionmaking Rules: What Companies Need to Know
- Federal vs. State AI Regulation: The Preemption Fight and What Businesses Do Now
-
Practical AI for In-House Counsel: With Sample Prompts
- Using AI for Contract Review and First-Pass Redlining
- AI-Assisted Research and Memo Drafting
- Streamlining Routine Work: NDA Triage, Policy Drafting, and More
- Turning Company Policies, Templates, and Playbooks Into Reusable AI Workflows
Who Should Attend
This course is designed primarily for in-house counsel and general counsel. Corporate and business attorneys, compliance and risk professionals, privacy and data governance professionals, legal operations professionals, HR directors and managers, and business leaders and executives may also benefit.
Speakers
Speaker bio
Jordan Wilcox
is the responsible AI governance and risk leader at Ascensus. He is an artificial intelligence (AI), privacy, and technology attorney with extensive experience in AI and machine learning (ML). He is responsible for developing, implementing, and operationalizing Ascensus’ Responsible AI framework and practices. This includes assessing AI systems for risk, documenting AI systems, responding to Client questions/requests on AI, negotiating AI contractual terms, and ensuring AI systems comply with applicable requirements. Prior to joining Ascensus, Mr. Wilcox worked as managing attorney, global head of data, analytics, and responsible AI at Dun & Bradstreet (D&B). In this role, he supported bringing multiple Generative AI products to market, including a joint product launch with IBM. Mr. Wilcox was also responsible for reviewing governance requirements for ML models used in credit, risk, and business scores. Before D&B, he managed a risk and audit team within Amazon’s Alexa Data Services, a global data labelling organization responsible for labeling and annotating data for machine learning. Mr. Wilcox developed and implemented controls for rapid protype data labelling, and privacy by design measures. He worked across different data types and modalities, including biometric and health data. Residing outside of Boston, Massachusetts, Mr. Wilcox earned his Bachelor of Arts degree from Stonehill College, with a major in political science and his J.D. degree from University of New Hampshire School of Law.
Speaker bio
Sean D. Brian
is of corporate counsel at Traeger, Inc., where he manages commercial litigation, negotiate and draft complex agreements with national retailers and international distributors, and assist with regulatory compliance efforts across consumer product safety, environmental regulations, and advertising law. Working on AI-enhanced contract review tools to drive department efficiency and manage contractual risk profile. Previously, as a Deputy County Attorney in Weber and Carbon counties, he has prosecuted serious felonies including homicides and financial crimes, served in specialty Drug and Mental Health courts, and acted as liaison and trainer for the Weber County Sheriff’s UAV Team. He was an adjunct professor of Criminal Law and Courts. He earned his B.S. degree from the University of Utah and his J.D. degree from the University of Utah S.J Quinney College of Law.
Speaker bio
Krystle Nova
is Senior Corporate Counsel at TTEC, specializing in Employment Law Strategy and People-Tech Compliance/ AI Governance. She helps leaders and teams move fast, stay compliant, and scale responsibly turning complex issues into clear, documented, auditable decisions. Ms. Nova specializes in Employment Law: Multi-state counseling; EEOC responses & mediations; wage & hour (FLSA); pay equity/transparency; ADA/leave; NLRB joint-employer; investigations; policy modernization; eDiscovery (legal holds/ECA/TAR). She also practices AI Ethics & Compliance: AI use-case intake, risk tiering, approvals/exceptions, and incident response. Ms. Nova supports M&A employment workstreams (integration, WARN/change comms), DOL audit readiness, and licensing/credentialing workflows. She earned her B.A. degree from Cornell University and her J.D. degree from Benjamin N Cardozo School of Law.
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