Technique 2.113 AI Change-Readiness
Introduction
This technique is designed to help leaders, change practitioners and teams assess where they are on the AI maturity curve and what to do next.
It is assessing human, cultural and organisational readiness for AI-enabled Change that is intentionally human-centred, emotionally aware and change-focused; however, it is not a technology audit.
Assessment Dimensions
- Leadership & Direction
- Culture & Psychological Safety
- Capability & Learning
- Ways of Working & Roles
- Governance, Ethics & Trust
- Emotional Readiness & Identity
How to Use
Rank each statement on a scale from 1–5:
1 = Strongly disagree
2 = Disagree
3 = Neutral/mixed
4 = Agree
5 = Strongly agree
Scoring Statements
1. Leadership & Direction
| Statement | Score (1–5) |
|---|---|
| 1.1 Leaders share a clear and realistic narrative about why AI matters here | |
| 1.2 Leaders openly discuss both benefits and risks of AI | |
| 1.3 There is clarity on how AI aligns with strategy and purpose | |
| 1.4 Leaders role-model responsible AI use | |
| 1.5 Decision rights related to AI are clear |
Domain score (out of 25): ___
Red Flags
- Leaders delegating AI entirely to IT
- Vision articulation without behavioural modelling
2. Culture & Psychological Safety
| Statement | Score (1–5) |
|---|---|
| 2.1 People feel safe to ask “naïve” questions about AI | |
| 2.2 Experimentation with AI is encouraged and protected | |
| 2.3 Mistakes in AI pilots are treated as learning | |
| 2.4 Concerns about AI are openly discussed | |
| 2.5 Cross-functional collaboration is supported |
Domain score (out of 25): ___
Red Flags
- Fear-based silence
- Shadow AI use
3. Capability & Learning
| Statement | Score (1–5) |
|---|---|
| 3.1 Employees understand what AI can and cannot do | |
| 3.2 AI literacy is available for all roles | |
| 3.3 Reskilling pathways are visible and accessible | |
| 3.4 Learning is embedded in day-to-day work | |
| 3.5 Managers are equipped to support AI-related skill shifts |
Domain score (out of 25): ___
Red Flags
- Training only for specialists
- “Learn on your own time” expectations
4. Ways of Working & Roles
| Statement | Score (1–5) |
|---|---|
| 4.1 AI is being integrated into real workflows (not just pilots) | |
| 4.2 Role impacts of AI have been openly discussed | |
| 4.3 Job redesign is happening alongside AI adoption | |
| 4.4 Humans remain accountable for decisions | |
| 4.5 Workload impacts are monitored and managed |
Domain score (out of 25): ___
Red Flags
- Tool deployment without role clarity
- Increased pace without workload redesign
5. Governance, Ethics & Trust
| Statement | Score (1–5) |
|---|---|
| 5.1 Ethical principles for AI use are clearly articulated | |
| 5.2 Bias, transparency and accountability are addressed | |
| 5.3 Employees know where and how to raise concerns | |
| 5.4 Data quality and privacy are actively managed | |
| 5.5 Governance supports innovation rather than blocking it |
Domain score (out of 25): ___
Red Flags
- Ethics as an afterthought
- Governance that arrives too late or ‘too heavy’
6. Emotional Readiness & Identity
| Statement | Score (1–5) |
|---|---|
| 6.1 Leaders acknowledge fears about job impact | |
| 6.2 People can discuss identity and role changes safely | |
| 6.3 AI is framed as augmenting human value | |
| 6.4 Loss, uncertainty, and ambiguity are recognised | |
| 6.5 Change conversations go beyond productivity metrics |
Domain score (out of 25): ___
Red Flags
- Dismissal of emotional responses
- Over-reliance on efficiency narratives
Interpreting Your Results
General
- Patterns matter more than scores
- Mismatch across sections signals change risk
- Use results to prioritise change actions, not just AI investment
Overall Readiness Profile
| Total Score | Readiness Interpretation |
|---|---|
| 30–72 | Low readiness – focus on sense-making and trust |
| 73–102 | Emerging readiness – invest in capability and safety |
| 103–126 | Strong readiness – scale responsibly |
| 127–150 | High readiness – enable continuous transformation |
Priority Change Actions (By Readiness Gaps)
If Leadership scores are low
- Create a shared AI change narrative
- Run leadership sense-making sessions
If Capability scores are low
- Introduce tiered AI literacy
- Build learning into workflows
If Emotions score is low
- Facilitate identity and impact conversations
- Train managers in emotional regulation
If Governance scores are low
- Co-design ethical guardrails
- Clarify accountability early
NB Key Insight
AI change readiness is a measure of human readiness for uncertainty.
Technology can be purchased quickly.
Trust, identity and capability cannot.
(main source: Ajay Agrawal, et al, 2018)