Clinical AI Governance: What Clinicians Must Know in 2026

About this episode

The episode discusses the importance of governance in the adoption of AI tools in healthcare, focusing on what clinicians need to know for safe implementation.

AI in healthcare is accelerating fast—but adoption without governance is risk. In this conversation, oncology and health policy leaders break down how clinicians and health systems should evaluate emerging AI tools: what FDA clearance vs approval really means, why “not FDA-approved” doesn’t automatically mean unsafe, and how laboratory-developed tests (LDTs) are already embedded in everyday care. We also explore real-world evidence, model drift, and why implementation—not innovation—is the true bottleneck for safe scale. If you’re assessing AI in imaging, diagnostics, clinical decision support, or workflow automation, this is your framework for asking smarter questions and protecting patients.

People in this episode

Host: Tensor Black

Topics covered

• AI in healthcare
• clinical decision support
• governance
• FDA approval
• real-world evidence
• model drift
• implementation challenges

Keywords

• AI governance
• healthcare
• FDA clearance
• clinical decision support
• model drift
• patient safety
• workflow automation

Mentioned in this episode

Organizations: FDA, health systems, laboratory-developed tests (LDTs), AI

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