Health system leaders are moving from pilots to practical results with data and AI. As ecosystems mature and generative models evolve, the focus is shifting to trusted data foundations, responsible rollout and measurable outcomes.
Yet many organizations still face fragmented data, unclear governance and adoption challenges. Leaders must balance speed with safety, define where AI should and should not be applied, and align clinicians, IT and operations around shared goals.
In this session, leaders share pragmatic strategies and examples that deliver clinical and operational value while strengthening guardrails.
Learnings include:
- 2026 priorities for data and AI that move beyond pilots to systemwide value
- Proven ways AI can deliver both clinical and operational results with measurable outcomes
- A practical playbook for interoperable, trusted data and AI governance
- Adoption tactics that bridge innovation teams, clinicians and IT
