AI Governance in Healthcare: A Practical Guide to Safer and Compliant AI
AI is quickly becoming part of healthcare, from clinical documentation and triage to diagnostics support, patient communication, scheduling, and operations. It can save time, reduce workload, and improve care. But in healthcare, getting AI wrong has real consequences: patient safety risks, privacy breaches, biased outcomes, regulatory exposure, and loss of trust from clinicians and patients.
AI governance doesn't have to mean heavy bureaucracy or a large compliance team. It means putting clear, practical rules in place for how your organization selects, uses, and monitors AI, with human oversight built in where it matters most.
In this webinar, we'll explore what AI governance means in healthcare, which risks leaders should pay attention to, and how to set up simple, workable guardrails so AI stays safe, accountable, and compliant. The session is designed for healthcare leaders, managers, and decision-makers, with no technical knowledge required.
1. What AI Governance Means in Healthcare
Understand what AI governance is, why it matters for healthcare organizations of every size, and how it differs from technical AI development or formal regulatory approval.
2. The Risks of Using AI Without Clear Guardrails
Explore common risks, including exposing patient data, relying on inaccurate or biased AI outputs, unclear accountability for AI-assisted decisions, and staff using unapproved AI tools.
3. Keeping Humans in the Loop
Learn where human oversight is essential — from clinical decisions to patient-facing communication — and how to design review steps that keep clinicians and staff in control without slowing everything down.
4. Building a Practical AI Governance Framework
Learn how to establish simple, actionable guidelines for your organization, including:
Defining which AI tools can be used and for what purposes.
Setting clear rules for handling patient and confidential data.
Deciding when human review is required.
Assigning responsibility for AI use and addressing issues when they arise.
Reviewing AI tools and practices as regulations and needs evolve.
5. Managing Third-Party AI Tools and Vendors
How to evaluate AI vendors, what to ask about data handling, model behavior, and safety, and how to control "shadow AI" across your teams.
6. Your First Steps: From Awareness to Action
Identify the first actions your organization can take to improve AI governance without unnecessary bureaucracy.
7. Live Q&A
Bring your questions and real-world scenarios.
Who should attend
Hospital, clinic, and health-system leaders.
CIOs, CMIOs, and digital health teams.
Healthcare startups and health-tech companies.
Healthcare SMEs and service providers.
Compliance, quality, and patient-safety teams.