When a deeper assessment is useful
- Multiple teams and AI use at scale
- Leadership oversight and accountability
- Third-party tools and integrations
- Tracking maturity over time
A structured, evidence-based view of AI governance maturity
MaturityLens helps organisations assess AI governance and readiness across practical domains, identify evidence gaps, and produce reporting that leadership can use to prioritise improvement.
What you receive
- Maturity score and domain profile
- Evidence gap analysis
- Improvement roadmap
- Board-ready summary report
What evidence-based means
- Policy records and governance decisions
- Use-case inventories and classifications
- Risk registers and controls
- Vendor due diligence records
- Training records and attestations
- Independent assurance disclaimer
Who should be involved
Leadership and governance
Sets direction, oversees AI strategy and accountability.
Risk, compliance and assurance
Manages risk, controls and independent assurance.
Technology, data and security
Builds secure, reliable and responsible AI systems.
Business, people and suppliers
Drives adoption, capability and vendor partnerships.
What the assessment covers
Strategy, accountability and governance
Direction, roles, oversight and decision rights.
Use-case visibility and classification
Inventory, classification and lifecycle visibility.
Policy, risk and controls
Policies, risk management and control effectiveness.
Data, vendors and third parties
Data governance, quality and vendor assurance.
People, agents and oversight
Workforce capability, AI oversight and ethics.
Monitoring, reporting and improvement
KPIs, reporting, incidents and continuous improvement.
How the assessment works
- 1
Scope
Define scope, goals and stakeholders.
- 2
Assess
Complete the structured assessment.
- 3
Review evidence
Provide evidence and supporting documents.
- 4
Analyse
We analyse, score and identify gaps.
- 5
Plan
Agree priorities and improvement roadmap.
- 6
Track improvement
Monitor progress and strengthen maturity.