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AI Readiness Mini-360
Construct Mapping Template (Research Backbone Framework)
Dimension
Core Construct
Established Research Domain
Key Theorists / Models
Why It Matters for AI Scaling
Current Questions Covering This
Strategic Clarity
Strategic Alignment
Strategic Management & Execution Alignment
Kaplan & Norton (Strategy-Focused Org), Hambrick & Fredrickson
AI initiatives fail without shared direction
Q1, Q2
Governance & Structure
Decision Rights Clarity
Organizational Design & Governance
Galbraith STAR Model, RAPID Framework
AI scaling requires clear ownership
Q3, Q4
Leadership Behaviour
Leadership Signaling & Modeling
Transformational Leadership
Bass & Avolio
Leaders shape adoption culture
Q5, Q6
Culture & Trust
Psychological Safety
Team Learning & Trust Theory
Amy Edmondson; Mayer, Davis & Schoorman
AI experimentation requires safe failure
Q7, Q8
Learning & Capability
Organizational Learning
Learning Organization Theory
Peter Senge
AI scaling depends on learning loops
Q9, Q10
There are no rows in this table
Section 2 – Question-Level Mapping
Table 6
Question
Dimension
Underlying Construct
Research Anchor
Is It Sufficiently Sharp?
Missing Elements?
Q1
Strategic Clarity
Strategic Direction Alignment
Kaplan & Norton
Needs sharpening?
Risk appetite?
Q2
Governance
Decision Authority Clarity
RAPID Model
Clear enough?
Escalation logic?
Q3
Culture
Psychological Safety
Edmondson
Good
Add risk framing?
There are no rows in this table
Section 3 – Measurement Rigour Plan
Area
Current Design
Research-Backed Expectation
Action Needed
Scale Type
1–5 Likert
Standard psychometric scale
OK
Gap Threshold
0.7 variance
Needs empirical basis
Validate via pilot
Reliability
Not tested
Cronbach’s alpha per dimension
Pilot test required
Factor Structure
Assumed
Exploratory factor check
Phase 2
There are no rows in this table
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