AI Adoption Style Assessment
Discover your AI adoption approach and learn how to navigate transformation challenges effectively.
Part 1: Context & Current State
1. What best describes your organisation's current AI experience?
2. Which industry best describes your organisation?
3. How many people typically influence AI technology decisions in your organisation?
4. What's your biggest AI adoption challenge right now? (Select up to 3)
5. Rank these factors in order of importance (1 = most important, 4 = least important):
Speed of implementation and competitive advantage
Risk management and regulatory compliance
Innovation potential and user engagement
Employee impact and organisational culture
Part 2: AI Adoption Style Assessment
Rate each statement: 1 = Strongly Disagree, 5 = Strongly Agree
6. When evaluating AI solutions, my first priority is demonstrating clear ROI and competitive advantage.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
7. I believe AI implementation should only proceed after comprehensive risk assessments and compliance reviews.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
8. AI's greatest potential lies in enhancing creativity and enabling more engaging user experiences.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
9. The human impact of AI deployment is more important than speed of implementation.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
10. I prefer to move quickly on promising AI opportunities rather than wait for perfect conditions.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
11. Before adopting AI, I need to see detailed documentation of data quality, model accuracy, and governance frameworks.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
12. AI initiatives should focus on inspiring teams and creating innovative collaborative experiences.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
13. Employee training and change management are the most critical factors in AI adoption success.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
14. AI projects should be measured primarily by their impact on business metrics and operational efficiency.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
15. I would postpone AI deployment if there were any concerns about regulatory compliance or algorithmic transparency.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
16. The most exciting AI applications are those that transform how people interact and collaborate.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
17. AI should augment human capabilities rather than replace jobs, even if automation would be more efficient.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
18. When AI pilots show promise, we should scale rapidly to capture first-mover advantages.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
19. AI explainability and interpretability are non-negotiable requirements for any system we deploy.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
20. I'm drawn to AI use cases that enable personalisation and creative problem-solving.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
21. Ethical considerations and employee trust should guide every AI implementation decision.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
22. AI adoption timelines should be driven by market competition and business urgency.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
23. I prefer phased AI rollouts with extensive testing rather than organisation-wide deployments.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
24. The best AI projects generate excitement and enthusiasm across multiple departments.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree
25. Long-term organisational health is more important than short-term AI performance gains.
1Strongly Disagree
2Disagree
3Neutral
4Agree
5Strongly Agree