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AI Consulting 101

AI Readiness Assessment: The 25-Question Checklist for Mid-Market Leaders

By Harry Peppitt 4 min read Updated

Most companies that fail at AI implementation weren’t unlucky. They started before they were ready.

This AI readiness assessment covers five categories: Strategy, People, Process, Technology, and Data. 25 questions total. Score yourself honestly, and you’ll get a clear picture of where you stand and what needs to happen before AI investment makes sense.

This is the same framework we use in the first phase of every AI Advisory engagement.

How to Use This Assessment

Scoring: Rate each statement on a scale of 1 to 5.

  • 1: Not true at all
  • 2: Slightly true, but significant gaps
  • 3: Partially true, in some areas or teams
  • 4: Mostly true, with some exceptions
  • 5: Consistently true across the organisation

Total possible score: 125 points

ScoreBandWhat It Means
0–49Not ReadyFoundational work needed before any AI investment
50–74Early StageCore prerequisites in place; targeted pilots possible with support
75–99ReadyStrong foundation; structured AI investment likely to generate returns
100–125AdvancedMature foundation; ready for ambitious AI initiatives

Category 1: Strategy (25 points possible)

1. We have a clear, documented AI strategy endorsed by executive leadership. Score: ___

2. We can name three to five specific business problems where AI could create measurable value within 12 months. Score: ___

3. We have allocated budget for AI initiatives in the current financial year. Score: ___

4. We have identified an internal owner or champion responsible for AI initiatives. Score: ___

5. Our board and senior leadership have a realistic understanding of what AI can and cannot do. Score: ___

Category 1 Total: ___ / 25

Category 2: People (25 points possible)

6. We have at least one internal person with hands-on experience deploying AI or automation tools. Score: ___

7. Our senior leadership actively supports process change and is willing to adjust workflows to enable AI adoption. Score: ___

8. Our frontline teams understand that AI is being explored, and the communication has been framed positively. Score: ___

9. We have capacity to dedicate at least one internal person to an AI implementation project for 2 to 4 hours per week. Score: ___

10. Our team has the technical literacy to engage with AI tools and interpret AI-generated outputs critically. Score: ___

Category 2 Total: ___ / 25

Category 3: Process (25 points possible)

11. Our core business processes are documented and consistently followed across teams. Score: ___

12. We can identify our top three most time-consuming manual processes and describe them step by step. Score: ___

13. We have a clear process for evaluating and approving new tools or technology implementations. Score: ___

14. When we change a process, the change tends to stick rather than reverting to the old way within a few weeks. Score: ___

15. We measure and track performance of our key processes with defined KPIs. Score: ___

Category 3 Total: ___ / 25

Category 4: Technology (25 points possible)

16. Our core business systems are modern enough to have APIs or data export capabilities. Score: ___

17. We use cloud-based software for most of our operations, rather than primarily on-premises systems. Score: ___

18. We have a consistent approach to software vendor evaluation and avoid proliferating tools without IT awareness. Score: ___

19. Our IT or technical team is willing and able to support AI integrations. Score: ___

20. We have a documented approach to data security and understand what data can and cannot be shared with external AI tools. Score: ___

Category 4 Total: ___ / 25

Category 5: Data (25 points possible)

21. We have a single source of truth for our key business data, and our teams agree on which system is authoritative. Score: ___

22. Our most important business data is structured and stored in systems, not trapped in emails or unstructured documents. Score: ___

23. We maintain consistent data entry standards, and our records are reasonably clean and complete. Score: ___

24. We can pull historical data covering at least 12 to 24 months for our core business processes. Score: ___

25. We have someone responsible for data quality, and there is a process for identifying and correcting data errors. Score: ___

Category 5 Total: ___ / 25

Your Total Score: ___ / 125

What Your Score Means

Not Ready (0-49)

Significant foundational work is needed before AI investment is likely to generate returns. For most companies in this band, the highest-impact starting point is data infrastructure: getting to a reliable single source of truth for core business data.

Early Stage (50-74)

Some foundational elements are in place, and targeted pilots are possible with appropriate support. Identify your lowest-scoring categories and prioritise them. Run one small, well-scoped pilot in an area where your readiness scores are strongest.

Ready (75-99)

Strong foundations are in place. Develop a prioritised AI roadmap based on your specific use cases. Start with the highest-ROI, lowest-risk applications.

Advanced (100-125)

You have a mature foundation and are ready for ambitious AI initiatives. Focus on ROI prioritisation and organisational capacity. Pick two or three high-impact programs and commit resources to see them through.

Category Score Patterns to Watch For

High Strategy, Low Data: You have leadership commitment but the data foundations aren’t there. Get data foundations in place before committing to AI implementations.

High Technology, Low Process: You have good technical infrastructure, but processes aren’t well-defined enough for AI to improve them. Define processes before automating them.

High Everything, Low People: Strong foundations but limited internal capability to absorb change. Invest in change management and training alongside implementation.

Next Steps

Our AI Assessment call is a 30-minute session where we work through your specific scores, identify the two or three highest-leverage actions, and give you a concrete view of what an AI roadmap would look like for your business. No commitment, no sales pitch.