Insights
Governance, in practice
Working notes on the problems health systems actually hit once AI is live.
Predictive AI vs. GenAI governance: same word, different rules
Can you govern a sepsis model and an LLM the same way? The differences matter more than most frameworks acknowledge.
The “Day 2” Problem: Why 90% of AI Governance Focuses on Pre-Deployment Vetting When Real Insights Live in Ongoing Monitoring
AI governance doesn’t end at deployment. Real risk and impact emerge in production, where oversight is often weakest.
Secret Cyborgs: The Hidden Risk Your AI Governance Policy Is Missing
“Secret cyborgs” expose a growing gap between formal governance and how AI is actually used on the ground.
The Rise of the Departmental AI Lead: What AI Governance Can Learn from Epic’s Physician Builder Model
AI governance is decentralizing from committees to departments, where real oversight happens.
Your AI is 99% accurate. So what? Why accuracy alone isn’t enough
“99% accuracy” means little if the model doesn’t drive real-world action and impact.
48 Hospital and Health System Chief AI Officers to Know
From clinical decision support to enterprise automation, AI is reshaping healthcare. Meet the executives shaping the future of responsible AI in hospitals across the US.
Navigating AI Liability in Healthcare: Key Considerations for Health System Leaders
When AI harms, who’s to blame? As AI enters clinical care, liability is shifting. Here’s what health leaders need to know.
Navigating HIPAA's New Proposed AI Rule: Key Implications for Health Systems
Sam Khan explores the newly proposed HIPAA AI rule and its impact on healthcare AI compliance.
The Expanding Role of Chief AI Officers in Healthcare: A Comprehensive Overview for 2025
Explore the 2025 list of top Chief AI Officers shaping AI strategy, governance, and innovation in healthcare.