AI-generatedRuns a public customer-support chatbot built on a third-party AI model, with a public developer API and still-light governance.
- Maturity
- Emerging
- Report type
- Sample · illustrative
Overall AI governance maturity is emerging with critical 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.
- 40%Documented
- 60%Self-reported
- 0%Missing
What this assessment indicates
Your organization demonstrates its strongest practices in governance & ownership (54.8), placing overall maturity at the emerging stage with critical residual risk. The most material exposure is in monitoring & improvement (5). 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
- Governance & ownership (54.8)
- Data governance (30)
- Security & operations (25.8)
Material governance gaps
- Monitoring & improvement (5)
- Inventory & use-case mapping (7.5)
- Vendor & third-party (9.2)
Priority remediation roadmap
Sequenced over the next 90 days, highest-impact gaps first.
- P0securityAdd misuse/abuse controls to public AI endpoints
- P0securityAddress prompt-injection risk in design reviews
- P0dataScope retrieval permissions by user or role
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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.
How your domains map to the frameworks
Indicative, domain-level mapping — the control-by-control crosswalk lives in the dedicated assessments and the full report.
| Domain | EU AI Act | ISO/IEC 42001 | NIST AI RMF |
|---|---|---|---|
| Governance & ownership | Art. 9, 17 (risk & quality mgmt) | Clause 5–6, A.2–A.3 | GOVERN |
| Inventory & use-case mapping | Art. 11, 49 (docs, registration) | Clause 4, A.4 | MAP 1.6 (inventory) |
| Data governance | Art. 10 (data governance) | A.7 | MAP / MEASURE (data) |
| Security & operations | Art. 15 (robustness, cybersecurity) | A.6 / security | MEASURE 2.7 |
| Vendor & third-party | Art. 25 (value chain) | A.10 | GOVERN 6 (supply chain) |
| Transparency & human oversight | Art. 13, 14, 50 (transparency, oversight) | A.8–A.9 | Accountable & Transparent |
| Monitoring & improvement | Arts. 72–73 (post-market, incidents) | Clause 9–10 | MANAGE 4 (monitoring) |
Go deeper — recommended next assessments
This governance check is broad and cross-framework. For a control-level result, continue with a dedicated assessment — start with ISO/IEC 42001, where your indicative coverage looks weakest.
Build the ISO/IEC 42001 management-system view across all nine AIMS domains and certification prep.
Start assessmentProfile your system across NIST AI RMF — Govern, Map, Measure and Manage — with the GenAI profile.
Start assessmentGo deep on EU AI Act applicability, operator role, risk classification and conformity duties.
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