
AI Readiness Assessment Report
Generated December 10, 2025
sample@example.com
About this assessment: This report provides indicative insights based on your self-reported answers. It is intended to identify AI areas for further investigation, not a comprehensive security, capability, or compliance audit. Results should be validated through deeper organisational analysis before any significant investment or strategic decisions are made.
Your Overall Results
4.0
2.5
2.0
Detailed analysis of each dimension and tailored suggestions follow below.
D1 - AI Exposure (Usage): 4.0
HighActive Engagement. Your responses indicate widespread AI adoption across your organisation. This active engagement creates momentum for innovation, though it also suggests that ensuring secure, supported workflows warrants attention.
AI Exposure (Usage) Distribution vs Benchmark (mean = 3.8)
D2 - Organizational AI Capability (Skill): 2.5
ModerateDeveloping Capability. Your responses suggest inconsistent capability levels. You may have pockets of expertise alongside gaps in training or infrastructure. Targeted investment could help close specific gaps.
Organizational AI Capability (Skill) Distribution vs Benchmark (mean = 2.8)
D3 - AI Governance (Control): 2.0
ModerateDeveloping Governance. Your responses suggest governance structures exist but may have enforcement gaps. Strengthening implementation could improve confidence in AI risk management.
AI Governance (Control) Distribution vs Benchmark (mean = 3.0)
Quadrant Results
Your scores place you in the 'Blind Risk Zone'
Your responses indicate areas where both capability and governance may benefit from attention. Establishing foundations in both areas would support more confident AI adoption.
AI Readiness Risk Map
Tailored Suggestions
Blind Risk Zone: Foundation Priority
Active AI exposure (D1 at 4.0) without strong foundations in either Capability (D2 at 2.5) or Governance (D3 at 2.0) requires attention to establish basic structures.
Strategic Focus
With AI usage already active, focus on establishing basic structures quickly. Prioritise minimum viable governance first to manage immediate risk, then build capability aligned with your emerging framework.
Consider prioritising:
- Establish basic usage guidelines immediately
- Define accountability structures for AI decisions
- Begin building capability aligned with governance
- Assess current AI usage to understand risk exposure
Further Guidance: Four-Step Development Process
A structured approach can help organisations develop their AI maturity thoughtfully:
Step 1: Understand Current Position
Develop a deeper understanding of your organisation's specific context and priorities.
- Explore root causes: Investigate what's driving dimension scores
- Assess readiness: Understand cultural factors and existing friction points
- Identify priorities: Determine which areas would benefit most from attention
- Define boundaries: Clarify scope for initial focus areas
Step 2: Identify Opportunities
Focus on identifying high-value, manageable opportunities for AI adoption.
- Map value: Identify use cases that offer clear benefit with manageable complexity
- Define requirements: Establish minimum controls needed for chosen use cases
- Set indicators: Define metrics for both value delivered and risk managed
Step 3: Build Capability and Controls
Develop integrated capability and governance appropriate to your chosen opportunities.
- Practical governance: Design controls as enablers rather than barriers
- Targeted training: Build skills focused on compliant, effective AI use
- Stakeholder engagement: Ensure appropriate buy-in before proceeding
Step 4: Pilot, Learn, and Expand
Test approaches in controlled environments and scale what works.
- Controlled pilots: Test within defined boundaries
- Monitor outcomes: Track against established indicators
- Iterate thoughtfully: Adjust based on real experience
- Document learnings: Create reusable patterns for future expansion

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