A practical framework for assessing where your AI governance stands today — discovery, policy, monitoring, evidence and accountability — and what to put in place before your next review.
24 pages. Written for CIOs, CMIOs, compliance leads and the committees that own AI oversight.
A working framework for assessing AI governance in a health system: what to inventory, what to write down, what to monitor after go-live, and what evidence to keep. Each section ends with a short checklist you can take into a governance committee.
01
Why AI governance needs a framework
02
Building an AI inventory that reflects reality
03
Finding the AI nobody approved
04
Writing policy people can actually follow
05
Enforcing policy at the point of use
06
Monitoring behaviour after go-live
07
Vendor and model change management
08
Evidence a reviewer will accept
09
Accountability, escalation and sign-off
Written for the people who are accountable when AI goes wrong:
CIOs and CTOs
CMIOs and clinical informatics leads
Compliance and privacy officers
Quality and patient safety leads
Risk, legal and procurement
AI governance committee chairs
