Individual Readiness Report
AIRA / 03-CATOverall AI Readiness Score
0/100
AIRA Level
AI Empowered
- Knowledge78
- Readiness72
- Scenarios64
Recommended PathwayAI for Office Management
Strong knowledge base, weaker applied judgement on live tasks
Measure AI readiness.
Build real adoption.
AIRA helps organisations understand whether their people are genuinely prepared to adopt AI — across capability, confidence, governance and practical application.
Built for workforce transformation, capability development and responsible AI adoption.
Designed for enterprise workforce transformation
- Government
- Financial Services
- GLC
- Enterprise
- Education
- Digital Economy
The gap
AI adoption is not a technology problem alone.
Many organisations invest in AI tools and training without understanding whether employees have the awareness, confidence, practical skills or governance knowledge required to use AI effectively. The result is spend without measurable behaviour change — and risk that surfaces only after it has already been taken.
Tool Access Without Adoption
Employees may have access to AI tools but still avoid using them or use them incorrectly.
Training Without Diagnosis
Generic training programmes fail when they do not address actual capability gaps.
Innovation Without Governance
Uncontrolled adoption creates privacy, security, compliance and decision-making risks.
Three categories
A complete view of AI readiness
AIRA scores three weighted categories that together determine whether AI adoption succeeds in real working environments.
- 01
AI Knowledge & Awareness
Understanding of AI and generative AI, responsible use, prompt engineering, governance, ethics and privacy.
15 multiple-choice itemsWeight35% - 02
AI Readiness, Confidence & Adoption Mindset
Readiness, confidence, adoption mindset, willingness to learn, trust and critical thinking.
15 rating-scale itemsWeight35% - 03
AI Workplace Scenarios
Applied judgement when using AI in everyday workplace situations.
15 situational itemsWeight30%
Methodology
From assessment to action
A four-stage framework that turns individual responses into a defensible development plan — for the person and for the organisation.
Stage 01 — Assess
Employees complete a structured, role-aware AI readiness assessment.
45 assessment items
Stage 02 — Diagnose
AIRA identifies capability strengths, behavioural barriers and governance risks.
Three weighted categories
Stage 03 — Segment
Participants are grouped into meaningful readiness profiles and maturity levels.
Five AIRA levels
Stage 04 — Develop
Each participant receives a recommended learning pathway and practical action plan.
30-day action plan
The assessment
Situational questions, not trivia
Participants respond to realistic workplace scenarios across all three categories. Every item maps to a measurable behaviour rather than a definition.
MDEC AIRAAI Readiness AssessmentResponses are confidential
Question 18 of 45
Approximately 18 minutes remaining
AI Readiness, Confidence & Adoption Mindset
Maturity
Five levels of AI readiness
Scores resolve into an AIRA level that leaders can act on. Levels describe observable behaviour in the workplace, which makes them meaningful for training design and for reporting progress over time.
- LEVEL 1
AI Aware
Limited AI knowledge and little to no practical use.
0–20 - LEVEL 2
AI Ready
Understands AI fundamentals and ready to adopt AI tools.
21–40 - LEVEL 3
AI Enabled
Uses AI regularly to improve individual productivity.
41–60 - LEVEL 4Sample
AI Empowered
Integrates AI into workflows, collaboration and decision-making.
61–80 - LEVEL 5
AI Leader
Champions AI adoption, innovation, governance and best practices.
81–100
Individual outcomes
More than a score
Every participant receives a complete readiness report: where they are strong, where they are exposed, what to learn next and what to do in the next thirty days.
Overall readiness score
0/100
AI Empowered
- AI Knowledge & Awareness
- 78
- AI Readiness, Confidence & Adoption Mindset
- 72
- AI Workplace Scenarios
- 64
Key strengths
AI Knowledge & Awareness
Strong grasp of where AI creates value
Prompt engineering
Gives AI tools clear, structured instructions
Adoption mindset
Open to adapting existing workflows
Development priorities
AI Workplace Scenarios
Applying judgement on live work tasks
Human oversight
Verifying AI output before it is reused
Data handling
Classifying information before prompting
Governance risk flags
- ElevatedConfidential information handling
- ModerateOutput verification before reuse
- LowApproved tool awareness
Recommended training pathway
AI for Office Management
Priority development area: applied judgement in live workplace scenarios
Suggested workplace use cases
- Drafting and refining internal reports
- Summarising long policy and regulatory documents
- Preparing meeting briefs and follow-up actions
- Structuring first-draft analysis for review
30-day development actions
- Days 1–10Complete the Responsible AI foundations module and the organisational data classification briefing.
- Days 11–20Apply a confidentiality check before every generative AI prompt and log three real workplace examples.
- Days 21–30Rebuild one recurring reporting task with AI assistance and review output accuracy with your team lead.
For organisations
Turn individual assessments into organisational intelligence
Individual reports stay confidential. Aggregated, they give transformation leaders a defensible picture of where the workforce actually stands.
- Workforce readiness distribution
- Capability gaps by department
- Governance risk exposure
- Training demand
- Adoption barriers
- High-potential AI leaders
- Progress over time
Organisational Readiness Overview
Total participants
0
Average readiness score
0/100
Level 4 — AI Empowered
Governance risk indicator
Moderate
34% show gaps in information handling
AI Empowered or above
0%
Level 4 and Level 5
Readiness distribution
- AI Aware
- 8%
- AI Ready
- 22%
- AI Enabled
- 30%
- AI Empowered
- 28%
- AI Leader
- 12%
Department comparison
- Technology
- 79
- Corporate Services
- 71
- Human Capital
- 68
- Finance
- 64
- Operations
- 59
Organisation average 68 · lowest quartile flagged for priority intervention
Recommended programme allocation
AI for Office Management
52%
Aware and Ready cohorts
AI Data Analytics
21%
Analytical functions scoring 65%+ in Knowledge and Scenarios
AI Driven Sales & Customer Engagement
18%
Customer-facing functions scoring 60%+ in Scenarios
AI Executive Leadership
9%
Senior Manager and above scoring 60%+ overall
Where AIRA is applied
Built for the decisions leaders actually have to make
Each application answers a question a transformation, HR or learning team is already being asked to answer.
Workforce Capability Assessment
Replace assumptions with an evidence base. Leaders see exactly which parts of the workforce can already work with AI and which cannot.
Training Needs Analysis
Direct learning budget at measured gaps instead of broad-brush programmes, and justify the allocation with category-level evidence.
AI Adoption Baseline
Establish a defensible starting point before tools are rolled out, so later progress can be attributed rather than assumed.
Responsible AI Awareness
Surface where employees would mishandle confidential information or accept unverified output, before an incident makes it visible.
Transformation Progress Tracking
Re-assess on a cycle to show movement across maturity levels and report workforce readiness alongside other transformation measures.
Platform
Enterprise deployment capability
AIRA is designed to run across large, multi-department organisations without losing participant confidentiality or analytical depth.
- Role-based assessments
- Custom organisational categories
- Department-level analytics
- Training pathway mapping
- Benchmarking
- Multilingual assessment support
- Secure participant management
- Exportable executive reports
- Longitudinal progress tracking
- Governance and risk indicators
Capability set reflects the AIRA assessment framework. Deployment scope is confirmed per organisation.
Before scaling AI, understand your readiness.
Establish a clear baseline, identify capability gaps and build a workforce development plan grounded in evidence.
Individual assessment takes approximately 30 minutes.