Global AI Governance Maturity Self-Assessment

Assess the Readiness of Your AI Governance—Global Framework

Assess Your Global AI Governance Maturity. Is your organization ready for responsible, sustainable, and certifiable AI deployment—across borders and regulatory landscapes?
The AIGN Global AI Governance Self-Assessment provides a fast, confidential, and actionable benchmark—aligned with leading international standards. Map your current state, receive instant maturity scores and tailored recommendations, and unlock your roadmap to trustworthy AI.

No registration. No data transfer. 100% privacy by design.

About the AIGN Global AI Governance Framework. The AIGN Global AI Governance Framework is designed to help organizations of any size and sector implement responsible, effective, and future-proof AI governance. Built on international best practices—including the EU AI Act, ISO/IEC 42001, OECD AI Principles, and the NIST AI Risk Management Framework—it provides a comprehensive structure for managing AI risks, driving ethical innovation, and achieving regulatory alignment across borders.

Is your organization truly prepared for responsible and effective AI deployment on a global scale?

The AIGN Global AI Governance Maturity Self-Assessment enables you to evaluate and benchmark your current capabilities against the world’s leading standards for trustworthy AI.

Why Use the AIGN Global Self-Assessment?

Comprehensive Coverage: Assess your AI governance maturity across all key domains—from leadership and strategy to ethics, risk management, and compliance.
Immediate Feedback: Receive a clear maturity score and actionable recommendations within minutes.
Aligned with International Standards: Built on the EU AI Act, ISO/IEC 42001, OECD AI Principles, and the NIST AI Risk Management Framework.
Privacy by Design: All data remains on your device—no registration, no data transfer.
Actionable Roadmap: Identify concrete priorities and next steps to strengthen your AI governance and risk management.

How It Works

For each question, simply select the score that best reflects your current practice—from 1 (“no evidence”) to 5 (“excellence by design”).
Be honest: your real starting point is the foundation for effective progress.

Ready to get started? Begin your self-assessment now and unlock your roadmap to responsible AI governance.

AIGN AI Governance Global Maturity Self-Assessment

AIGN
AI Governance Maturity Self-Assessment Based on the AIGN Global Framework

Assess your organization’s AI governance maturity in 8 dimensions.
Benchmark yourself with the AIGN Global Framework — the international gold standard for responsible, sustainable, and certifiable AI.
All data stays on your device. No results are stored or sent.

1. Strategy & Leadership

1. Is there a documented AI governance strategy, embedded in overall leadership vision?Strategy is not ad-hoc or isolated, but guides AI use across the organization.

2. Is top management or board ownership for AI governance visible and continuous?Senior leaders drive accountability, not just compliance.

3. Are roles & responsibilities for AI (RACI) formally assigned and reviewed at least annually?Clear escalation, override and ethics contact points are established.

2. Trust & Capability Indicators

4. Is transparency and explainability „by design“ embedded in all AI systems?Not just technical docs, but actionable explanations for all key users and stakeholders.

5. Are fairness & bias mitigation measures active, tested and externally reviewed?Go beyond checklists: peer review, stakeholder consultation, and continuous monitoring.

6. Is accountability for AI outputs clearly defined, traceable and contestable?Audit trails, appeals, and redress mechanisms are available for users and staff.

3. Governance Structures

7. Are oversight, escalation and audit mechanisms robust and stress-tested?Red teaming or stress-test scenarios are conducted at least annually.

8. Is there an up-to-date responsibility (RACI) matrix for the full AI lifecycle?Includes training data, deployment, post-market monitoring, incident response.

9. Are external stakeholders, affected groups or independent experts involved in governance?Participation and feedback are systematically documented and acted upon.

4. Risk & Impact Management

10. Are AI-specific risk assessments, red lines and impact mappings routine and reviewed?Heatmaps, consequence analysis and risk registers are active and up-to-date.

11. Are unacceptable outcomes (red lines) and mitigation plans clearly defined per AI use case?Includes scenario planning, fallback strategies and documentation for all critical systems.

12. Are risk heatmaps and incident trends discussed at management level?Not just compliance, but proactive risk foresight, reviewed by leadership.

5. Data & Model Governance

13. Is data provenance (origin, rights, consent) fully documented and regularly audited?Copyright, input quality and lineage logs are integrated in audits.

14. Are data quality, bias and representativeness checked and reported for all key datasets?Include diverse stakeholders in input audits and bias checks.

15. Is there full versioning and documentation for all models and datasets?Changelogs, update logs and governance events are tracked in a revision-secure way.

6. Compliance & Audit

16. Are all AI systems compliant with relevant regulations (EU AI Act, GDPR, ISO/IEC 42001, etc)?Includes non-EU global standards and sector rules where relevant.

17. Are internal or external AI governance audits conducted at least annually?Audit results lead to documented improvement actions.

18. Are audit trails and documentation maintained in a revision-secure and transparent way?Documentation is not just compliance, but empowers continuous learning and improvement.

7. Sustainability & Societal Impact

19. Is energy/resource efficiency considered and benchmarked in all AI design & deployment?Carbon tracking, green compute and optimization plans are documented and monitored.

20. Are long-term maintainability and updatability managed for all AI systems?Systemic longevity, retrainability and sunset criteria are part of the governance plan.

21. Are societal, ethical and inclusion impacts considered in all major AI projects?Stakeholder inclusion, diversity impact and benefit mapping are performed and reported.

8. Incident Response & Continuous Improvement

22. Are incident detection, response and escalation processes documented and tested?Red teaming, escalation playbooks and incident logs are reviewed and updated regularly.

23. Are lessons learned from incidents, audits and reviews systematically integrated?Continuous improvement is visible in updated policies, controls and training.

24. Are regular updates, training and governance reviews embedded in routines?Maturity is not static — annual or continuous reviews drive trusted AI for the long term.

Assessment logic based on the AIGN Global Framework for Responsible AI Governance – www.aign.global

Ready to Raise Your AI Governance to the Next Level?

Take the next step with the AIGN Global AI Governance Framework.
As an official licensee, you gain exclusive access not only to our internationally aligned framework—but also to a complete suite of practical tools, validated templates, and expert guidance tailored to your needs.

We don’t just deliver a framework. We empower you to succeed.
From first assessment to full implementation, our consulting team is by your side—ensuring your organization achieves true, certifiable AI governance maturity.

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Don’t navigate the complexities of AI governance alone.
Contact us today to schedule your personal consultation and discover how the AIGN Global AI Governance Framework—complete with official tools and templates—can future-proof your organization.

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