AI Readiness Assessment | How Prepared Is Your Business?

Data Quality & Availability

How ready is your data for AI applications?

1. How would you describe the quality of your organisation's data?

Poor - lots of errors, inconsistencies, and gaps Fair - some issues but generally usable Good - reliable and well-maintained Excellent - clean, validated, and enriched

2. How accessible is your data across the organisation?

Siloed - each department has its own data Partially shared - some cross-department access Mostly accessible - centralised with good access Fully accessible - unified data platform

3. Do you have historical data for training AI models?

Minimal - less than 6 months of data Moderate - 6 months to 2 years Good - 2 to 5 years of historical data Extensive - 5+ years of rich historical data

4. How is your data currently stored and managed?

Manual - spreadsheets and local files Basic databases - some structure but limited Cloud-based - modern databases with APIs Data warehouse/lake - advanced analytics-ready

Technology Infrastructure

How ready are your systems for AI integration?

5. What is the current state of your IT infrastructure?

Legacy - mostly on-premise, older systems Hybrid - mix of cloud and on-premise Cloud-first - most systems in the cloud Cloud-native - modern, scalable architecture

6. How would you describe your integration capabilities?

Limited - manual data transfers, few APIs Basic - some integrations, manual monitoring Good - API-based integrations with monitoring Advanced - iPaaS, event-driven, real-time

7. Do you have compute resources for AI/ML workloads?

None - no dedicated AI/ML resources Basic - standard cloud instances Good - GPU instances available, managed ML services Advanced - dedicated ML infrastructure, auto-scaling

8. How mature are your security and governance practices?

Basic - minimal controls, reactive approach Developing - some policies, basic compliance Established - comprehensive policies, regular audits Advanced - AI-specific governance, privacy by design

Team Skills & Culture

How ready is your team for AI adoption?

9. What is your team's current AI/ML knowledge level?

None - no AI/ML experience Basic - awareness but limited hands-on experience Intermediate - some team members with AI skills Advanced - dedicated AI/ML team or strong expertise

10. How open is your organisation to adopting new technologies?

Resistant - prefers established methods, slow to change Cautious - willing but needs strong evidence Open - actively explores new technologies Innovative - early adopters, tech-forward culture

11. What is your organisation's approach to data-driven decision making?

Intuition-based - decisions mostly on experience Emerging - starting to use data in decisions Data-informed - regular use of analytics Data-driven - decisions always backed by data

12. What change management capabilities do you have?

Minimal - change often meets resistance Basic - some processes, inconsistent application Structured - formal change management process Mature - dedicated team, proven frameworks, high success

Process Maturity

How documented and optimised are your workflows?

13. How well documented are your business processes?

Tribal knowledge - processes in people's heads Partially documented - key processes mapped Well documented - most processes standardized Fully documented - living process library with regular updates

14. Do you currently use any automation tools?

None - everything is manual Basic - some simple automations (email rules, macros) Moderate - RPA or workflow automation tools Advanced - intelligent automation with AI/ML

15. How do you measure process performance?

We don't - no formal process metrics Basic - occasional manual tracking Regular - dashboards and KPI tracking Continuous - real-time process intelligence and analytics

16. How does your organisation handle process improvement?

Reactive - only when problems arise Periodic - annual reviews and projects Continuous - dedicated improvement programs Optimised - Lean/Six Sigma culture, innovation encouraged

Strategic Alignment

How aligned is AI with your business goals?

17. Does your organisation have a clear AI strategy?

No - AI hasn't been discussed strategically Exploring - initial discussions about AI potential Defined - AI strategy exists with clear objectives Integrated - AI is core to business strategy with executive sponsorship

18. What executive support exists for AI initiatives?

None - no executive awareness or interest Aware - executives know about AI but not actively involved Supportive - executive sponsor for AI initiatives Champion - C-level executive actively driving AI

19. Have you identified specific AI use cases for your business?

No - haven't explored potential applications Few - 1-2 potential use cases identified Several - prioritised list of use cases with business cases Many - comprehensive AI roadmap with active pilots

20. What budget is allocated for AI initiatives?

None - no dedicated AI budget Exploratory - small budget for research/pilots Allocated - dedicated budget for AI projects Strategic - multi-year AI investment plan

Your AI Readiness Report

Based on your responses across 5 key areas

0

Overall Readiness Score

Not Ready

Readiness Level

Beginning Journey

Readiness by Category

1

Data Quality 0%

2

Technology 0%

3

People & Culture 0%

4

Process Maturity 0%

5

Strategy 0%

Key Recommendations

Suggested Next Steps

Get Your Full Report

Discuss your results with an AI expert

Book Free Workshop