Collective Privacy and AI Governance for Small Healthcare Providers

Across Canada, many small and mid-sized institutions are facing growing privacy and artificial intelligence governance obligations without the resources or in-house expertise to meet them effectively. This session explores scalable, collaborative approaches to privacy and AI compliance, from collective privacy impact assessments and shared AI assessments to communities of practice that pool subject-matter expertise across Ontario-based institutions with common needs. Drawing from real-world case studies in the primary health and community health sectors, as well as emerging consumer e-health and multi-partner initiatives, this presentation will demonstrate how institutions managing vast amounts of sensitive personal data can pragmatically achieve privacy and AI governance outcomes that are both practical and sustainable.

What you will learn:

• How collective or “pooled” PIAs and AI assessments can improve quality and reduce costs.

• Practical methodologies for implementing scalable privacy and AI governance across small healthcare institutions.

• Lessons learned from pilot projects and communities of practice supporting resource-limited institutions.