AI-generatedGives clinicians an AI decision-support assistant over medical guidelines; doctors review outputs, but documentation and monitoring lag.
- Maturity
- Developing
- Report type
- Sample · illustrative
Overall AI governance maturity is developing with high residual risk — strongest where controls are established and most exposed where foundational gaps remain.
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Target threshold 70
What you report as in place, before evidence adjustment.
Based on response consistency and supporting evidence.
- 53%Documented
- 47%Self-reported
- 0%Missing
What this assessment indicates
Your organization demonstrates its strongest practices in security & operations (66), placing overall maturity at the developing stage with high residual risk. The most material exposure is in monitoring & improvement (6.7). Closing these foundational gaps in inventory, accountability, and production controls will reduce operational, regulatory, and reputational risk as AI adoption expands.
Governance domain performance
Score out of 100 · benchmark 70Established capabilities
- Security & operations (66)
- Transparency & human oversight (63.3)
- Governance & ownership (57.3)
Material governance gaps
- Monitoring & improvement (6.7)
- Inventory & use-case mapping (13.1)
- Data governance (50)
Priority remediation roadmap
Sequenced over the next 90 days, highest-impact gaps first.
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- P1monitoringReview AI output quality and business impact after deployment
- P1monitoringCapture AI incidents, complaints, and failures
- P1inventoryLink each AI use case to an owner and intended purpose
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Assessment basis
What this score is built on.
Responses are checked for consistency and aligned to the selected frameworks.
Framework coverage
Indicative roll-up. Control-by-control mapping is in the full report.
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