AI Governance Maturity Assessment
Self-scoring rubric to assess AI governance maturity across 8 domains and 40 capabilities. 5-level maturity scale (Initial to Optimizing) with interpretation guide and improvement action planning."
Key Insights
You can't improve what you don't measure. This maturity assessment provides a structured way to evaluate your AI governance program across eight critical domains, identify gaps, and prioritize improvements.
The assessment uses a 5-level maturity model (Initial, Developing, Defined, Managed, Optimizing) with specific capability indicators for each level. It covers Strategy & Leadership, Organization & Accountability, Policies & Standards, Risk Management, Compliance & Regulatory, Technical Controls, Third-Party Management, and Transparency & Communication. Score interpretation guidance and improvement action planning help you translate assessment results into concrete next steps.
Overview
Where does your AI governance program stand today? What are your strongest areas? Where are the critical gaps? This maturity assessment provides structured answers—not vague impressions, but scored evaluations across every governance domain.
The assessment is designed for self-scoring by CAIOs and governance leaders. It provides a baseline for new programs, a benchmark for maturing programs, and a communication tool for Board and executive reporting.
What's Inside
- 5-Level Maturity Model: Clear definitions for each maturity level from Initial (ad hoc, reactive) through Optimizing (continuous improvement culture)
- 8 Domain Assessments: Detailed capability rubrics for:
- Strategy & Leadership (vision alignment, executive sponsorship, Board oversight, charter, resources)
- Organization & Accountability (CAIO role, governance committee, roles/responsibilities, coordination, escalation)
- Policies & Standards (acceptable use, ethics principles, development standards, procurement, documentation)
- Risk Management (AI inventory, risk classification, assessment process, bias testing, incident response)
- Compliance & Regulatory (awareness, monitoring, audit readiness, documentation, regulatory engagement)
- Technical Controls (validation, data quality, security, monitoring/drift detection, version control)
- Third-Party Management (due diligence, contracts, ongoing monitoring, exit strategies, supply chain risk)
- Transparency & Communication (stakeholder disclosure, explainability, internal/external communications, training)
- Scoring Mechanics: 1-5 scoring for each capability with domain averages and overall program score
- Score Interpretation Guide: What each score range means and recommended focus areas
- Improvement Action Planning: Template for documenting gaps, prioritizing actions, and tracking progress
Who This Is For
- Chief AI Officers assessing and improving governance programs
- Governance Program Managers tracking maturity progress
- Board Members understanding governance program status
- Auditors evaluating AI governance effectiveness
- Consultants assessing client governance maturity
Why This Resource
Maturity assessments drive improvement by making current state visible and gaps concrete. This assessment is calibrated specifically for AI governance—not adapted from generic IT governance maturity models—with capability indicators that reflect AI-specific requirements.
The action planning template ensures assessment results translate into improvement initiatives, not just scores filed away.
FAQ
Q: How should we interpret our score?
A: 1.0-1.9 (Initial): Significant gaps, immediate action needed. 2.0-2.9 (Developing): Basic elements in place but inconsistent. 3.0-3.9 (Defined): Solid foundation with documented processes. 4.0-4.9 (Managed): Mature program with metrics and controls. 5.0 (Optimizing): Industry-leading with continuous improvement culture.
Q: How often should we reassess?
A: Annual assessment is recommended for most organizations. More frequent assessment (quarterly) may be appropriate during active governance program buildout or following major changes.
Q: Should we aim for Level 5 across all domains?
A: Not necessarily. Level 5 (Optimizing) requires significant ongoing investment. Most organizations should target Level 3-4 across domains, with higher maturity in areas most critical to their risk profile.
What's Inside
- 5-Level Maturity Model: Clear definitions for each maturity level from Initial (ad hoc, reactive) through Optimizing (continuous improvement culture)
- 8 Domain Assessments: Detailed capability rubrics for:
- Strategy & Leadership (vision alignment, executive sponsorship, Board oversight, charter, resources)
- Organization & Accountability (CAIO role, governance committee, roles/responsibilities, coordination, escalation)
- Policies & Standards (acceptable use, ethics principles, development standards, procurement, documentation)
- Risk Management (AI inventory, risk classification, assessment process, bias testing, incident response)
- Compliance & Regulatory (awareness, monitoring, audit readiness, documentation, regulatory engagement)
- Technical Controls (validation, data quality, security, monitoring/drift detection, version control)
- Third-Party Management (due diligence, contracts, ongoing monitoring, exit strategies, supply chain risk)
- Transparency & Communication (stakeholder disclosure, explainability, internal/external communications, training)
- Scoring Mechanics: 1-5 scoring for each capability with domain averages and overall program score
- Score Interpretation Guide: What each score range means and recommended focus areas
- Improvement Action Planning: Template for documenting gaps, prioritizing actions, and tracking progress
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