Know where
you stand.Know what’s next.
A practical assessment of your AI foundations. Answer 10 questions and get a clear score, tailored priorities and a downloadable report.
AI readiness is more than buying a licence.
Good AI adoption starts with a real business problem, clear ownership, usable information and sensible controls. Our assessment looks at the foundations that make AI practical, secure and measurable.
Business & ownership
Defined problems, accountable owners and a clear reason to invest.
Data & platforms
Visibility of existing tools, usable business data and approved AI access.
Security & governance
Identity controls, data-handling rules and proportionate oversight.
Human review & value
People checking important outputs and meaningful measures of success.
Simple questions.
Clearer decisions.
Each of the 10 questions is worth up to two points. Base your answers on what genuinely exists today, not what you plan to introduce.
Not in place.
There is no reliable process, control or clearly defined approach in this area.
Partly in place.
Something exists, but important gaps, inconsistencies or informal practices remain.
Clear & working.
The foundation is established and sufficiently reliable for responsible AI use.
10 checkpoints × 2 points = 20 points maximum. Your result includes a breakdown and recommended next steps.
Find your starting point.
Choose the option that best describes your business today. You'll see your results immediately and can download your report without submitting contact details.
Your result
0–7 · Build the basics firstAll 10 assessment results
These are the exact scores used to calculate your overall result of 0 / 20.
Your top priorities
The lowest-scoring areas are shown here so you have a clear starting point.
Send your assessment to CloudSec AI
Your score and all 10 answers will be sent in the email. Add your details so we know who to reply to.
How the 0–20 score is interpreted
Useful opportunities exist, but wider use would be risky. Fix the main gaps first.
Start with one or two low-risk AI use cases and fix the obvious gaps as you go.
You have a solid base for wider AI use. Keep reviewing risk, data and ownership for each use case.
Focus on measuring results, keeping controls consistent and scaling the AI use cases that work best.