Home · The model
AI doesn't fail in one place. It fails where strategy, data, people or governance quietly lag the ambition. So we score the seven things that decide whether AI actually sticks — each on evidence, each on the same 0–5 ladder, rolled into one number you can defend.
The shape of it
The seven dimensions aren't a flat checklist. They group into three foundations — the conditions that have to hold for AI to move from intent to impact.
The intent and the guardrails — whether AI is genuinely steered from the top, and bounded by real accountability.
The means to build — the data, the people, and the platform that turn ambition into working systems.
The proof it works — AI live in the operation, and the value it creates measured and reaching the business.
What we measure
Each is scored 0–5 on its own evidence — and a weak one drags the whole climb, no matter how strong the rest look.
Is there a funded AI strategy tied to business goals — with a named owner, a roadmap, and the budget to back it, not just a slide?
Do your policies for risk, ethics and accountability exist — and actually bite, with real oversight rather than good intentions?
Is your data available, clean, governed and ready to build on — or scattered, manual, and quietly blocking every use case?
Do teams have the skills — and does AI literacy reach beyond a handful of specialists into the people who'll actually use it?
Do you have the compute, platforms and MLOps to run AI in production — reliably, securely, and sovereign by design?
Are use cases live in daily operations and trusted — or stuck in the sandbox, impressive in a demo and absent in the work?
Can you measure the value AI creates — and is it reaching the business, reported to leadership, and improving over time?
The scale
Every dimension climbs the same six rungs. It's deliberately the same scale across all seven, so a 3 in Data means the same kind of maturity as a 3 in Strategy.
The same 0–5 ladder for every dimension — and a level is only yours when the evidence backs it.
AI isn't really on the agenda. No capability, no ownership — the work here is the basics.
Early intent and a few enthusiasts. Pieces are being put in place, but nothing holds together yet.
Pilots run and standards appear. This is exactly where most organizations stall — between proof and scale.
Governed, funded, and in production. Solid ground — the value now is in scaling what already works.
Scaled across functions, monitored, and improving. You're ahead; the job is to protect the lead.
AI is woven into the business and aligned to national goals. Few organizations reach here — fewer stay.
Most maturity scores are a workshop consensus dressed up as a number. Ours isn't. Every rung on every axis has to be earned against evidence — auditable, reproducible, and the same standard for everyone. That's what makes the score defensible to a board, and honest enough to act on.
Our own model, built on the structure of Saudi's national AI framework.We don't claim official endorsement — we bring the framework's rigour, and the hands to act on the result.
Get a gut read in a minute with the free self-check — or book the evidence-based assessment and put a defensible number on every dimension.