MetincTrust
Sample AI Governance Readiness Report
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Aisha RahmanAI-generated
Healthcare

Gives 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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Sample
Executive summary
AI Trust Readiness Score
46/ 100
MaturityDevelopingRiskHigh

Target threshold 70

Self-reported maturity
64/ 100
1
2
3
4
5
Defined

What you report as in place, before evidence adjustment.

Confidence score
68High
LowHigh

Based on response consistency and supporting evidence.

Evidence coverage
100%Extensive
  • 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.

Strongest capability
Security & operations
Primary exposure
Monitoring & improvement
Immediate focus
Review AI output quality and business impact after deployment

Governance domain performance

Score out of 100 · benchmark 70
Security & operations
66
Transparency & human oversight
63.3
Governance & ownership
57.3
Vendor & third-party
53.1
Data governance
50
Inventory & use-case mapping
13.1
Monitoring & improvement
6.7
0–24 Critical25–49 At risk50–74 Moderate75–100 Strong

Established 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.

0–30 days

No actions in this window.

31–60 days
  • P1monitoring
    Review AI output quality and business impact after deployment
  • P1monitoring
    Capture AI incidents, complaints, and failures
  • P1inventory
    Link each AI use case to an owner and intended purpose
61–90 days

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Assessment basis

What this score is built on.

37
Controls assessed
19
Evidence items supported
7
Domains evaluated
2
Critical gaps identified

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.

NIST AI RMF
40%Developing
ISO/IEC 42001
41%Developing
EU AI Act
51%Developing
Full report · 40 pages

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