AI readiness assessment

The five areas it covers

• Strategy and use cases. Whether you know what AI is for, who backs it, and how you will tell if it worked.
• Data. Whether the information an AI project needs exists, is reliable, and can be used.
• People and skills. Whether the people who would use, build, and review AI are willing and able.
• Technology and process. Whether you can connect, test, and run a new tool without interrupting the business.
• Governance and risk. Whether you have rules, accountability, and awareness of legal limits.

What the levels mean

• Just starting (0 to 29). It’s early. Learning, choosing a first use case, and setting basic rules will do more now than building anything.
• Building foundations (30 to 54). You have a start, but a pilot would hit avoidable problems. Work on the gaps below first, then try one small project.
• Ready to pilot (55 to 79). You can run a well-chosen pilot now. Close the gaps below while it runs, so what works can grow.
• Ready to scale (80 to 100). The foundations are in place. Focus on moving proven pilots into everyday work and keeping quality and cost under control.

How to use it

1. Answer 15 statements. Choose how true each one is for your organization today, from “Not at all” to “Fully”. It takes about five minutes.
2. Read your score. You get an overall level and a score for each of the five areas, with a warning if one weak area could hold the rest back.
3. Work the gaps. Take the suggested next steps for your lowest areas, then copy the result to share with your team or leadership.

AI readiness, explained

What is an AI readiness assessment?

A structured check of whether an organization is prepared to use AI well. It looks past the technology to strategy, data, people, processes, and governance, because projects usually get stuck on those, not on the model.

What does AI readiness include?

Five areas: a clear strategy and use cases, usable data, people with the skills and willingness to adopt it, technology and processes that can support a pilot, and governance that sets rules and accountability. This assessment scores each one.

How is the score calculated?

Each of the 15 statements scores from 0 (not at all) to 3 (fully). Each area’s score is its three answers as a share of the maximum, and the overall score is the average of the five areas. Under 30 is just starting, 30 to 54 is building foundations, 55 to 79 is ready to pilot, and 80 or more is ready to scale.

What is a good AI readiness score?

Around 55 or higher means you can run a well-chosen pilot. But the weakest area matters as much as the total: a strong overall score with a very low score for data or governance will still cause trouble, so the result flags that.

What should we do if we score low?

Don’t start by buying or building anything. Fix the lowest-scoring area first. For each one, the result lists practical next steps, such as documenting your data, naming an owner, or writing a short usage policy.

Can this replace a full AI readiness review?

No. It’s a quick self-check based on your own view, so it will miss what you don’t know about. Use it to start a conversation, then test the answers with the people who run your data, systems, and compliance.

I’m Courtney Stephenson, an AI strategy and implementation leader, and I built this tool. Get in touch if you want to go through your results together or work out the next step.