How to Avoid The Pitfalls of Rapid AI Change

The problem we're solving:

There’s a lot of excitement and interest about AI, but not everyone knows where to start. Some agencies won't let staff install AI tools, while others have teams vibe coding their own solutions. And the market is full of vendors selling solutions before anyone's confirmed there's a real problem to solve. 

This session helps you cut through the noise and focus on where AI can actually move the needle for your agency. You’ll learn to identify your highest-impact use cases and to honestly assess what an AI tool could do for your agency. The result is investing in AI where it counts, not where the loudest vendor points. 

What you'll learn:

• The plain English difference between basic types of AI (chatbots, agents) with real government examples

• A practical rubric for evaluating where AI makes sense in your agency’s work, where it doesn’t, and which AI use cases are worth pursuing

• The readiness factors that determine whether your agency can support a given use case: process, data, governance, and people

• What good AI implementation actually looks like, through a live demo from a vetted builder
  

Agenda at a glance:

• The pressure every leader feels right now

• Why the AI market feels impossible to navigate

• AI without the jargon

• What makes a good AI business case (live rubric walkthrough)

• Readiness: what has to be true before you build anything

• What AI can Actually Do For Government

• Live Q&A

Speakers:

Ryan Hunter has worked with dozens of cities and counties nationwide to streamline procurement, make permitting easier, slash time-to-hire, and otherwise transform public services. Before co-founding PPI, Ryan directed San Francisco’s first citywide program in process improvement. Under Ryan’s leadership, the Lean Program trained over 700 staff, coached dozens of leaders to independently plan and implement major improvement projects, produced hundreds of rapid improvements, and facilitated transformation in areas as diverse as park maintenance, benefits administration, and hiring. During San Francisco’s COVID-19 response, Ryan used his process improvement expertise to stabilize the City’s COVID testing infrastructure, improve time-to-result, and efficiently allocate a limited supply of test kits. Ryan holds a Master’s degree in Sociology from Stanford University and a Master’s in Public Policy from UC Berkeley’s Goldman School. He is a Lean Black Belt, Certified Six Sigma Black Belt, Agile Scrum Master, and a Project Management Professional (PMP). He makes a mean mai tai.

Christine Tsang is co-founder and CEO of Caldera PBC, a public benefit corporation building AI infrastructure for state and local government. She is a Fellow at Princeton's Center for Information Technology Policy and was previously the founding Executive Director of Stanford RegLab, which has partnered with over 50 federal, state, and local agencies to design and deploy AI systems, including the IRS, US DOL, California, Colorado, San Francisco, and San Diego. This award-winning work has been featured in the New York Times, Politico, Bloomberg Law, NPR, CBS News, SF Chronicle, and more. She writes on effective public sector AI and has testified in front of the California legislature on new and emerging technology expertise and capacity. Prior to that, Christine was a Fulbright Scholar in China, worked in venture philanthropy and served on the leadership team of multiple venture-backed startups. She holds a B.A from Yale College and J.D. from Yale Law School.