The Trust Engine: Balancing AI Innovation with Patient Data Integrity

The Trust Engine: Balancing AI Innovation with Patient Data Integrity

Monday, March 9, 2026 3:05 PM to 3:35 PM · 30 min. (US/Pacific)
Level 3 | San Polo 3501A
Healthcare Cybersecurity Forum

Information

As healthcare moves from AI pilots to enterprise-wide deployment, the conversation has evolved into a "Patient Safety" conversation. For clinical and operational leaders, the challenge is ensuring that the AI tools integrated into every bedside and back-office function are ethical, secure, and reliable.

This session explores the intersection of cybersecurity and clinical excellence. We will discuss the rise of "Shadow AI" in the wards, the risks of "Agentic AI" (AI that takes actions on behalf of staff), and the emerging 2026 regulatory landscape. Attendees will gain a cross-functional blueprint for building an "AI Trust Engine"—a strategy that protects sensitive PHI while empowering clinicians with the automated tools they need to reduce burnout. We will move past the technical jargon to focus on how unified data visibility protects the integrity of the medical record and, ultimately, the safety of the patient.

Level
Intermediate
Format
Expert Insight
Learning Objective #1
Connect Security to Patient Safety: Understand how data "poisoning" or unauthorized AI access directly impacts clinical decision-making and patient outcomes.
Learning Objective #2
Manage the "Shadow AI" Ripple Effect: Identify how unauthorized AI tools (used by well-meaning staff to save time) create hidden vulnerabilities
Learning Objective #3
Navigate the 2026 Regulatory Environment: Prepare for the latest AI-specific requirements from the ONC, FDA, and international bodies regarding data transparency and "explainability."
Learning Objective #4
Build a Cross-Functional AI Governance Team: Learn how to bridge the gap between IT, Clinical, and Legal departments to create a unified policy for AI-driven data handling
Session #
HCF-9

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