Implementation Isn't the
Finish Line
AI capabilities are advancing rapidly. Healthcare organizations are deploying foundation models, ambient documentation, and agentic tools faster than ever, sometimes across the entire hype cycle at once. Yet going live is where real work begins, not where it ends. Sustained clinical value depends on more than a successful launch. It requires governance that scales, clinician trust that is earned rather than mandated, and systems someone is still accountable for long after the pilot is over.
Governance has to scale
AI oversight cannot stay on a single committee. As deployments multiply, governance has to grow with them, or it quietly stops working.
Trust is earned, not mandated
Clinicians adopt what they trust. Peer champions and published evidence build trust. Directives do not.
The work starts after go-live
A launched model is a living system. Without monitoring, ownership, and a plan for drift, accuracy erodes while no one is watching.
Explore an exclusive conversation with Dr. Deepti Pandita on why AI succeeds when it accelerates real strategy, earns trust through evidence rather than mandate, and is built to be managed long after it goes live.
What This Session Unpacks
Healthcare organizations are accelerating AI adoption. However, enterprise success depends on governance, interoperability, and operational readiness.
In this session, we’ll explore:
- Why AI should accelerate existing strategy rather than become its own initiative
- How UCI built AI governance that scales, from a single steering committee to five specialized subcommittees
- Why clinician trust is earned through peer champions and published evidence, not mandates
- How conversational AI can narrow the digital divide instead of widening it
- What to ask any AI vendor before you trust their model or their ROI number
- Why the next major opportunity in health tech isn't implementation. It's managing AI safely at scale after launch
Who This Is For
This Mastermind session is designed for healthcare IT leaders, CIOs, CMIOs, and clinical informatics teams responsible for AI governance, adoption, and long-term oversight.
The goal is simple: understand why AI succeeds when it is tied to real strategy, earns trust through evidence, and is designed to be monitored, not just deployed.
The format is intentionally conversational: an honest discussion on AI governance, clinician trust, health equity, and what happens after implementation, featuring practical insights healthcare leaders can apply within their own organizations.
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