Many health systems are deploying AI tools, but UC San Diego Health is emerging as a leading example of AI as an operating model, where it has embedded across clinical care, operations, and patient experience rather than deployed as isolated tools.
This session breaks down how UCSD Health structures and governs a growing portfolio of AI initiatives, applying distinct frameworks to predictive AI, generative AI and operational automation.
Learn how the organization used ambient documentation as an entry point to expand AI into adjacent workflows — from patient communication to population-level intelligence and real-time operational decision-making.
The conversation moves from strategy to execution, covering governance models that enable scale and evaluation practices built into every deployment.
Key learnings:
- Why predictive AI, generative AI and operational automation require different governance and adoption frameworks
- How UCSD Health manages a constant influx of AI initiatives through structured intake
- How a single high-adoption use case — ambient documentation — can unlock broader workflow transformation
- What it means to treat AI as an ongoing discipline with continuous evaluation
