Industry Leaders Advise UC Law SF on the Future of AI in Law and Legal Education
January 21, 2026 | Technology & Innovation
Sixteen leaders from law and technology - many UC Law San Francisco alumni - have joined a new advisory board focused on how AI is changing legal practice and legal education. The Advisory Board on the Technological Transformation of Legal Practice & Education met for the first time in December. Their role: advise on curriculum, professional skills training, and the responsible use of AI in teaching and academic operations.
It's a straightforward goal with immediate impact: keep legal education aligned with how top firms, in-house teams, and legal tech companies are working today - and where they're headed next.
Why this matters for practicing lawyers
- AI is now part of research, drafting, discovery, due diligence, and knowledge management. Graduates must be fluent in these workflows from day one.
- Clients expect informed guidance on AI policy, risk, IP, data privacy, and procurement. In-house teams need lawyers who can set credible guardrails and move projects forward.
- Firms must train lawyers to use AI responsibly, document quality controls, and align billing models with AI-enabled work.
- Competence includes tech literacy. Bar guidance such as the ABA Model Rule 1.1 (Comment 8) sets that expectation.
What the advisory board will do
- Recommend courses, clinics, and simulations that reflect real AI use in litigation, transactions, compliance, and policy work.
- Define core competencies: prompt strategy, verification and critique, confidentiality and privilege with AI, data governance, and vendor evaluation.
- Guide responsible use of AI in teaching and assessment, aligned with frameworks like the NIST AI Risk Management Framework.
- Connect students with tools, datasets, externships, and mentors from leading firms and legal departments.
UC Law SF's technology programs (context)
UC Law SF has invested in technology and law for more than a decade. The new board links that academic work directly to current practice and emerging standards.
- AI & Law Innovation Institute
- Center for Innovation
- LexLab
- Startup Legal Garage
- Technology Law & Lawyering concentration
Advisory Board Members
- Ashley Pantuliano '11, Deputy General Counsel, OpenAI
- Alexandra Stathopoulos, Partner, Orrick, Herrington & Sutcliffe LLP
- David Wang, Chief Innovation Officer, Cooley LLP
- Iain Cunningham '04, Vice President and Deputy General Counsel, NVIDIA
- Jo Levy, Partner, The Norton Law Firm
- Kerry McLean '93, Executive Vice President, General Counsel and Corporate Secretary, Intuit
- Lee B. Shepard '06, Partner, Morrison & Foerster LLP
- Lindsay Llewellyn '08, Chief Legal & Business Officer, Lyft
- Luis Villa, Vice President, Legal, Sonar
- Naveen Pai, Chief Knowledge Officer, Gunderson Dettmer
- Paul Sieminski, Chief Legal Officer, Liquid AI
- Scott Morgan '97, former Senior Vice President and Chief Legal Officer, Splunk
- Shannon Yavorsky, Partner, Orrick, Herrington & Sutcliffe LLP
- Shashi Deb '94, Adjunct Professor and Board Director, UC Law SF
- Shelley McKinley, Chief Legal Officer, GitHub
- Svetlana Matt '12, Director, Public Policy, DISH Network
Strategic Plan on Generative AI
The board will advise on UC Law SF's Strategic Plan on Generative AI. The focus is clear: update curriculum, align learning outcomes with evolving professional skills, and integrate AI tools into teaching and assessment where it makes sense.
"The board brings together leaders who are grappling with these issues every day in practice," said Drew Amerson, director of LexLab, UC Law SF's center for technology law and lawyering. "Their insight helps ensure that UC Law SF continues to lead in artificial intelligence and other emerging technologies that are reshaping the legal profession."
What legal teams can do now
- Run a quick inventory of AI use cases across research, drafting, review, KM, eDiscovery, and client service. Prioritize two pilots with clear success metrics.
- Set policy: acceptable tools, data handling, privilege, human review, and documentation. Keep it short and update quarterly.
- Train for outcomes: verification techniques, prompt strategy that reduces hallucinations, and matter-specific checklists.
- Vendor diligence: model sources, data retention, SOC 2/ISO posture, red-teaming, indemnities, and audit logs.
- Align pricing and staffing to AI-enabled work. Be transparent with clients about review standards and savings.
If you're building a skills plan for your team, explore curated AI courses by job function for fast, practical upskilling.
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