Healthcare AI Stalls Before Deployment — This Is Why

About this video

Sid Dutta joins Chris Hutchins to examine why healthcare AI projects stall before models reach production. Their conversation focuses on the data layer: safe access, privacy-preserving collaboration, runtime governance, and the infrastructure required to use sensitive healthcare data without exposing it.

Topics covered

• Why healthcare AI bottlenecks form at the data layer rather than the model
• What privacy-preserving AI and runtime data protection mean in practice
• How shadow AI and fragmented governance increase institutional risk
• What leaders should build before attempting cross-institution AI collaboration

This conversation discusses data governance, privacy, and cybersecurity for educational purposes and is not legal or compliance advice.