AIR APAC/AI readiness check

AIR APAC · Free · About fifteen minutes · Nothing is sent or stored

AI readiness check for your organisation

Thirty questions across six areas. Your result appears on this page when you finish, with the two areas to start with.

Before you start

How to answer

Answer on what you can see today, not on plans.
If you are unsure between two answers, choose the lower one.
The check is most useful when two or three leaders answer it separately and then compare. Where your answers differ is often as useful as the score.

Your answers stay in your browser. Nothing is sent to AIR APAC, nothing is stored, and the page sets no cookies. This is a preliminary self-check for discussion inside your organisation. It is not an assessment or a certification, and it is separate from the AI Readiness Index: it does not change any Index result.

The questions

Thirty questions, six areas

0 of 30 answered

Area 1 of 6

Leadership and vision

1. Does your organisation have a documented AI strategy aligned to business objectives?No AI strategy existsInformal discussions, but nothing documentedA strategy document exists but is rarely usedDocumented strategy with clear priorities, communicated to leadershipIntegrated AI strategy with regular review cycles and board visibility

2. Has your organisation allocated budget for AI initiatives with defined success metrics?No budget allocatedAd hoc spending when specific needs ariseBudget exists but success metrics are unclearDefined budget with some success metrics establishedMulti-year budget with clear KPIs reviewed quarterly

3. How would you rate the AI literacy of your senior leadership team?Little to no understanding; AI is seen as "IT's problem"Aware of AI but not personally engagedBasic understanding; can discuss AI but delegate all decisionsSolid understanding; actively involved in AI strategy discussionsDeep understanding; personally using AI tools and role-modelling adoption

4. Are your senior leaders personally using AI tools in their work?No usage: executives have not tried AI toolsOccasional experimentation: tried once or twiceRegular personal use: at least weeklyIntegrated into daily workRole-modelling and publicly advocating AI adoption

5. Is there a named executive sponsor accountable for AI adoption outcomes?No sponsor identifiedInformal sponsor without clear accountabilityNamed sponsor without specific KPIsNamed sponsor with defined KPIs and regular reportingNamed sponsor with board-level accountability and resources

Area 2 of 6

Data readiness

6. If you needed to access customer data for an AI project, how long would it take?Weeks or months: data locked in silosDays: requires multiple approvals and manual extraction1-2 days: process exists but is cumbersomeHours: accessible through defined processesNear real-time: available through APIs or data platform

7. What percentage of your critical business data would you consider clean and reliable?Less than 20%20-40%40-60%60-80%Above 80%

8. Are data governance policies in place and actively followed?No governance policies existPolicies exist on paper but not followedPolicies exist and are followed in some areasComprehensive policies with designated data ownersMature governance with regular audits and enforcement

9. Does your technical infrastructure support AI workloads?No cloud infrastructure; legacy systems onlyLimited cloud adoption; fragmented infrastructureCloud infrastructure exists but not optimised for AIModern infrastructure with some AI-ready capabilitiesAI-ready infrastructure with appropriate compute and storage

10. Can your existing systems integrate with AI tools?No integration capability; systems isolatedManual integration onlySome APIs exist but integration is challengingMost systems have APIs; integration manageableModern integration layer; AI tools connect easily

Area 3 of 6

Skills and capability

11. What percentage of employees have the baseline skills to use AI effectively?Less than 10%10-25%25-50%50-75%Above 75%

12. Can your people evaluate and judge AI outputs, not just use AI tools?No: people accept AI outputs without evaluationRarely: some awareness that outputs should be checkedSometimes: evaluation happens inconsistentlyUsually: most users critically evaluate outputsAlways: evaluation is standard practice with clear criteria

13. Is AI training designed for behaviour change, not just awareness?No training existsAwareness training only (presentations, overviews)Skills training exists, but it is genericRole-specific training with practical applicationComprehensive training with follow-up coaching and measurement

14. Are there clear AI use cases tied to specific job functions?No defined use casesGeneral use cases but not role-specificSome role-specific use cases documentedClear use cases for most roles with guidanceComprehensive use case library with success metrics

15. Is there ongoing support for AI adoption after initial training?No support after trainingAd hoc support when issues ariseHelp-desk support availableDedicated support with regular check-insEmbedded coaches and peer support networks

Area 4 of 6

Process maturity

16. What percentage of core business processes are documented in detail?Less than 20%: processes are held in people's heads20-40%: some documentation but incomplete40-60%: key processes documented60-80%: most processes documented and maintainedAbove 80%: comprehensive and regularly updated

17. Are processes consistent across the organisation?No standardisation; every team differentLimited standardisation; significant variationSome standardisation in key areasHigh standardisation with documented exceptionsConsistent processes with continuous improvement

18. Have you designed clear handoff points between humans and AI?No consideration of human-AI handoffsHandoffs happen ad hoc without designSome handoffs designed for specific workflowsMost workflows have designed handoff pointsComprehensive handoff design with escalation paths

19. Is it clear where AI adds value versus where humans are essential?No analysis of where AI or people should do the workGeneral awareness but no specific guidanceSome workflows have defined boundariesMost workflows have clear role definitionsComprehensive role mapping with regular review

20. Are metrics and incentives aligned with AI-enabled workflows?No consideration of AI in performance metricsSome awareness that metrics need updatingSome metrics updated for AI-enabled workMost metrics reflect AI-enabled workflowsPerformance system redesigned for AI-enabled work

Area 5 of 6

Governance and ethics

21. Does a formal AI use policy exist and is it known by employees?No policy existsInformal guidelines onlyPolicy exists but awareness is lowPolicy exists and communicated regularlyComprehensive policy with training and enforcement

22. Is there a framework for evaluating and approving AI tools?No framework; tools adopted ad hocInformal review for major purchases onlyFramework exists but inconsistently appliedClear framework with defined criteriaMature vendor management with regular review

23. Is there a clear process for handling AI failures or errors?No process; handle issues as they ariseAd hoc response to individual incidentsBasic incident response definedComprehensive risk framework with escalationMature risk management with regular testing

24. Is there clear accountability for AI-related decisions and outcomes?No clear accountability; "AI made the decision"Accountability unclear; shared across manySome accountability for major decisionsClear accountability for most AI use casesNamed roles for who decides and who is consulted, with board oversight

25. Are ethical considerations formally part of AI decision-making?Ethics not consideredInformal awareness of ethical issuesEthics discussed but not systematicEthical framework with review processEthics embedded in governance with regular audits

Area 6 of 6

Culture and change capacity

26. Is there psychological safety to experiment with AI and fail?No: failure is career riskLimited: experiments quietly toleratedModerate: some experimentation encouragedHigh: experimentation expected and celebratedVery high: people try, fail early, and the lessons are recorded

27. How does the workforce perceive AI?Fearful: seen as threat to jobsSceptical: seen as overhypedNeutral: mixed or uncertain attitudesPositive: seen as helpful toolEnthusiastic: seen as opportunity for growth

28. In the past two years, how many major change initiatives achieved their stated objectives?None: change initiatives typically failFew: less than 25% achieve objectivesSome: about half achieve objectivesMost: more than 75% achieve objectivesNearly all: strong change execution capability

29. Are employees actually using AI tools in their daily work?No adoption: tools purchased but unusedMinimal: less than 20% using regularlyModerate: 20-50% using regularlyStrong: 50-75% using regularlyWidespread: above 75% using regularly

30. Is the organisation currently able to absorb major change?Overwhelmed: multiple major changes underwayStretched: significant change fatigueModerate: some change capacity availableGood: can absorb additional changeStrong: change capacity deliberately managed

0 of 30 answered

Your result

Your organisation, by area

Your overall score: out of 5. Each area is the average of its five answers, from 1 to 5.

Where to start

A preliminary self-check, not an assessment. Scores are your own answers, not a comparison with other organisations.

Email the result to myself

Next: a free programme on deciding well when AI gives you the answer · the AI Readiness Index 2026