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Lessons from the Inside: C-Suite Perspectives on AI
A critical part of navigating the AI landscape is learning from those who have charged a path forward. This ongoing series provides insights from leaders that have successfully implemented clinical AI in large U.S. health systems.
Sunil Dadlani
EVP, Chief Information & Digital Transformation Officer, Chief Cyber Security Officer at Atlantic Health System
Aligning AI Strategy to Business Goals
Four Phases of an AI Implementation Plan
Changing How Clinicians Work with AI
Evolving AI Regulation and Transparency
Sarah Kramer, MD
Clinical Associate Professor of Internal Medicine
at University of Nevada, Reno School of Medicine
and former CIO
AI as a Co-Pilot
Building a Coalition for AI Adoption
Expanding Clinical AI Across the Enterprise
Educating the Next Generation on AI Adoption
Jeffrey Sturman
Senior Vice President &
Chief Digital Officer at
Memorial Healthcare System
The Utility of Healthcare AI Today
AI and Overcoming Challenges at Memorial Healthcare Network
Lessons Learned and Looking Towards the Future with AI
Debbie Cancilla
EVP, Data Strategy and
Chief Information Officer
at Temple Health
AI’s Impact at Temple Health
The Evolution of AI in Healthcare
Expectations, Learnings and Surprises
The Future of Clinical AI
Go Beyond the Algorithm for a Scalable AI Strategy
AI implementation should not be burdensome, but the steps that happen before, during and after implementation will ultimately determine success. Here are the four components of an enterprise AI strategy:
Choose:
Finding the right technology requires a multidisciplinary, collaborative approach focused on measurable value and clear decision-making.
Integrate:
A platform that will adapt to evolving health system needs while solving orchestration, monitoring and integration challenges.
Adopt:
A collaborative vendor that enables impactful change management through training and metrics for value externalization.
Govern:
Standards for implementation to ensure consistency and quality with a regular review of AI performance, opportunities and gaps.
AI Strategy Resources
AI is not one-size-fits-all, nor is it a linear path that starts with technology selection and ends after implementation. These resources can help health systems at every phase of the journey.
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