How AI-ready is your organisation?
17 questions across 5 dimensions. 15 minutes. A scored baseline, with specific next steps, before you commit any AI budget.
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The Five Dimensions of AI Readiness
How the quiz is scored
Every question is answered on a 1 to 5 scale, so the 17 questions give a total from 17 to 85, placed in one of four readiness tiers. Your result also shows each dimension on its own. A dimension below 60% of its maximum is a gap worth closing before you commit budget; below 40% is a likely deployment blocker.
17 questions worth up to 5 points each
Question counts, the 1 to 5 answer scale and the tier ranges are the quiz's own. A dimension with four questions can move the total by up to 20 points; one with three, by up to 15. Your result also shows each dimension on its own, which matters more than the total when one dimension is far behind.
4 questions
3 questions
3 questions
4 questions
3 questions
Answer these two and your result is benchmarked against organisations like yours as well as against everyone. Nothing else is collected.
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Question 1 of 17: Data Foundation
Data Foundation
Question 1 of 4 in this section
How is your organisation's core business data currently managed?
Data Foundation
Question 2 of 4 in this section
How much relevant historical data does your organisation hold for its core operations?
Data Foundation
Question 3 of 4 in this section
How quickly can your team access the data needed for a specific business decision?
Data Foundation
Question 4 of 4 in this section
Does your organisation have documented data ownership: named individuals responsible for specific datasets?
Process Maturity
Question 1 of 3 in this section
How well-documented are your organisation's core operational processes?
Process Maturity
Question 2 of 3 in this section
Has your organisation identified and prioritised specific AI use cases?
Process Maturity
Question 3 of 3 in this section
How consistently are your business outcomes measured and reported?
Technology & Infrastructure
Question 1 of 3 in this section
How would you describe your organisation's current IT infrastructure?
Technology & Infrastructure
Question 2 of 3 in this section
What is your organisation's level of cloud adoption?
Technology & Infrastructure
Question 3 of 3 in this section
How capable is your organisation at deploying and integrating new software tools?
People, Culture & Leadership
Question 1 of 4 in this section
How does your senior leadership team currently engage with AI?
People, Culture & Leadership
Question 2 of 4 in this section
What best describes your organisation's current AI and data analytical capability?
People, Culture & Leadership
Question 3 of 4 in this section
How does your workforce typically respond to significant technology change?
People, Culture & Leadership
Question 4 of 4 in this section
Does your organisation have a formal AI literacy or upskilling programme?
Governance & Risk
Question 1 of 3 in this section
Does your organisation have a formal AI policy or governance framework?
Governance & Risk
Question 2 of 3 in this section
How mature is your organisation's approach to data privacy and information security?
Governance & Risk
Question 3 of 3 in this section
How does your organisation currently manage the risks associated with AI?
Score by dimension
Each dimension is built from 3-4 questions, each self-rated 1-5. A dimension scoring below 60% of its maximum signals a gap worth addressing before committing budget; below 40% signals a likely deployment blocker.
Five dimensions that determine AI deployment success
Data Foundation
The quality, accessibility, and governance of your data. AI is only as reliable as the data it processes. Poor data quality is the single most common deployment failure.
Process Maturity
Whether your processes are documented, measured, and consistent enough to automate. AI cannot reliably improve a process that varies every time it is performed.
Technology & Infrastructure
Your cloud adoption, integration capability, and infrastructure modernity. Legacy systems drive up AI deployment cost and reduce reliability.
People, Culture & Leadership
Leadership commitment, staff capability, and organisational change readiness. Technical readiness without cultural readiness produces shelfware.
Governance & Risk
Your AI policy, risk management approach, and data privacy maturity. Governance gaps create liability, and slow every subsequent deployment while you retrofit controls.
Ready to turn your score into a plan?
The AI Strategy Consulting engagement benchmarks your readiness against comparable organisations, identifies the highest-return use case for your constraints, and produces a sequenced 90-day roadmap.
Explore AI Strategy Consulting
This is the deeper version of the readiness check, seventeen questions instead of five, because a real diagnosis needs more than a snapshot. I added Technology and People as their own dimensions after watching two businesses with identical data maturity get completely different results, one had a cloud-native stack and a curious team, the other didn't. Fifteen minutes is a small ask for a score that tells you honestly whether you're building on solid ground or setting yourself up to patch problems after launch.
Last updated 29 Sept 2026
More in Where you stand
- AI Readiness Self-AssessmentAre we ready to deploy AI, and where should we focus first?
- AI Acceptable Use Policy BuilderOur staff already use ChatGPT and Copilot. What should our written rules say?
- AI Use Case Prioritisation MatrixOf the use cases on the table, which do we fund first, and how much autonomy can each one have?
- Business Automation MapWhich of our processes already use AI, and where are the gaps worth filling?
- Workforce AI Readiness DiagnosticAre our people ready to adopt AI, as well as our systems?
- Chief AI Officer Personality TestWhat kind of AI leader am I, and where are my blind spots?
