From Promise to Practice: Driving System-Wide Efficiency with Clinical AI
As health systems face increasing pressure to improve operational performance, reduce burnout, and deliver high-quality care, many are turning to AI as a potential solution. But adopting AI at an enterprise level comes with challenges from selecting the right solutions, to ensuring seamless implementation, adoption and long-term governance.
This session will explore how AI can be scaled responsibly across departments to drive efficiency without compromising care. You’ll hear from experts as they unpack real-world experiences, implementation strategies and governance frameworks that make AI both effective and sustainable. Through this dynamic discussion, you’ll gain an enterprise-level view into what it takes to move from AI experimentation to long-term transformation.
By the end of this session, participants will be able to:
- Identify key criteria health systems and vendors use to evaluate and select scalable AI solutions across clinical and operational areas.
- Understand common implementation challenges and best practices for embedding AI into existing workflows and systems.
- Explore strategies for fostering strong adoption among clinicians and staff to ensure AI tools are used effectively and responsibly.
- Examine governance structures that support risk-informed, sustainable AI usage across health systems.
- Assess the collaborative roles of vendors, providers, and governing bodies in maintaining AI performance and trust over time.
Speakers:
- Moderator: Lawrence W. Vernaglia, Partner and Health Care Lawyer, Foley & Lardner LLP
- Ashley Weber, VP, Ochsner IS Ancillary Services, Ochsner Health
- Brenton W. Hill, JD, MHA, Head of Operations and General Counsel, CHAI
- Demetri Giannikopoulos, Chief Transformation Officer, Aidoc
