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Online CLE
ON-DEMAND

AI Governance CLE: Moving from Pilot to Practice - Governing Legal AI After the Tool Is Approved

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24 Sep, 2026 | 
12:00pm EDT
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60mins
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Virtual event
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1.0 CLE Ethics Credit

AI governance does not end when a tool is approved. In this free, on-demand ethics CLE, Axiom’s David O’Hara and DraftPilot’s Daniel van Binsbergen examine what happens when AI moves from a closely supervised pilot into everyday legal work, and how legal teams can maintain meaningful oversight as use expands. 

Drawing on the ABA Model Rules, Formal Opinion 512, state bar guidance, and judicial decisions involving AI-generated work, the discussion covers:

  • Verifying AI-generated research, citations, and legal work
  • Setting human review standards based on the risk of each task
  • Supervising AI-assisted and autonomous workflows while preserving attorney judgment
  • Protecting confidential information and assessing AI vendors
  • Documenting decisions, escalation processes, and evidence of reasonable supervision

You’ll also hear practical approaches to approved playbooks, outside counsel guidelines, and controls that help legal departments govern AI use at scale. The program closes with an audience Q&A.

Register to watch the recording on demand and access this free program offering 1.0 ethics CLE credit

 
Is this CLE approved in my state? Check accreditation & summary details →

AI Governance CLE Agenda

Approval Is the Beginning of Governance

  • Moving from supervised AI pilots to enterprise-wide use
  • Why lawyers remain responsible for AI-assisted work
  • The professional responsibility duties that continue after deployment

Competence & the Evolving Rules

  • Model Rule 1.1 and ABA Formal Opinion 512
  • Emerging and diverging state bar guidance
  • Keeping governance current as AI technology and regulation evolve

Verification & Candor

  • Verifying AI-generated legal research, citations, and factual assertions
  • Lessons from recent cases involving fabricated or inaccurate AI output
  • Calibrating human review based on legal risk

Supervision & Autonomous AI

  • Supervisory duties under Model Rules 5.1 and 5.3
  • Preserving independent professional judgment
  • Governing agentic AI and increasingly autonomous legal workflows

Confidentiality, Privilege & Disclosure

  • Protecting confidential and privileged information when using AI
  • Evaluating vendor, retention, and data-use risks
  • Client disclosure and outside counsel considerations

Documentation, Escalation & Defensibility

  • Documenting responsible AI governance and supervision
  • Establishing escalation paths for high-risk AI output
  • Managing audit logs, retention, preservation, and discoverability

Q&A

  • Audience questions and practical takeaways

Speakers

David OHara
David O'Hara
Lawyer
Axiom

David O’Hara is an experienced attorney and legal transformation leader with more than 20 years of experience advising organizations on commercial transactions, legal operations, technology, and emerging areas of legal practice. His career spans in-house leadership, legal consulting, and complex technology-focused engagements, including serving as General Counsel and as a Director in PwC’s Legal Business Solutions practice.

David has extensive experience at the intersection of law and technology, advising on technology transactions, intellectual property, data sharing, autonomous vehicles, and legal technology implementation. He has also led AI-focused legal projects, including training and evaluating AI-powered contract review tools and helping legal teams integrate technology into their workflows and operating models. David earned his J.D. from Wayne State University and his B.A. from the University of Michigan.

 

Daniel vin Binsbergen headshot
Daniel van Binsbergen
CEO & Co-Founder
DraftPilot
Daniel van Binsbergen is a former corporate lawyer and legal technology entrepreneur with more than 20 years of experience spanning private practice, legal services, and legal AI. He is CEO and Co-Founder of DraftPilot, a legal AI platform that helps in-house teams review and redline contracts, create reusable playbooks from historic contracts and guidance, conduct legal research, and analyze large document sets, while keeping lawyers in control of the work and final decisions.
 
Before DraftPilot, Daniel founded and led Lexoo (an ALSP) for more than a decade, working with in-house legal teams on thousands of commercial contracts. Earlier, he was a senior associate at international law firm De Brauw, in Amsterdam and London. Daniel also writes Daniel’s In-house Legal Newsletter. His work focuses on turning AI from a successful pilot into a dependable part of legal practice, with clear standards, proportionate human review, and professional judgment built into the way teams work.

Register On Demand

This is a 60-minute CLE program offering up to 1.0 CLE ethics credit. Check your state's accreditation status and requirements here.

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AI Governance CLE Agenda

Approval Is the Beginning of Governance

  • Moving from supervised AI pilots to enterprise-wide use
  • Why lawyers remain responsible for AI-assisted work
  • The professional responsibility duties that continue after deployment

Competence & the Evolving Rules

  • Model Rule 1.1 and ABA Formal Opinion 512
  • Emerging and diverging state bar guidance
  • Keeping governance current as AI technology and regulation evolve

Verification & Candor

  • Verifying AI-generated legal research, citations, and factual assertions
  • Lessons from recent cases involving fabricated or inaccurate AI output
  • Calibrating human review based on legal risk

Supervision & Autonomous AI

  • Supervisory duties under Model Rules 5.1 and 5.3
  • Preserving independent professional judgment
  • Governing agentic AI and increasingly autonomous legal workflows

Confidentiality, Privilege & Disclosure

  • Protecting confidential and privileged information when using AI
  • Evaluating vendor, retention, and data-use risks
  • Client disclosure and outside counsel considerations

Documentation, Escalation & Defensibility

  • Documenting responsible AI governance and supervision
  • Establishing escalation paths for high-risk AI output
  • Managing audit logs, retention, preservation, and discoverability

Q&A

  • Audience questions and practical takeaways
Register Now

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