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AI Maturity Model · نضج الذكاء الاصطناعي

Where AI fits — stage by stage.

AI in go-to-market is not on/off. It matures through four levels — from assisting a human, to running on its own. The skill is placing each task at the right level: too early and it breaks trust; too late and you leave compounding on the table.

Bolting AI on everywhere at once?

Four levels — assisted to autonomous.

Map every task to a level, then move it up only when the data and the trust are there.

Level 1

Assisted

AI drafts; a human decides and sends. Speed with full human judgment in the loop.

Level 2

Augmented

AI recommends the next move from the record; the human approves. Judgment, scaled.

Level 3

Automated

AI runs defined plays end to end within guardrails; humans handle exceptions.

Level 4

Autonomous

AI orchestrates a motion and self-corrects from outcomes. Humans set the goal and the limits.

The clever bit: maturity is per-task, not per-company. The best teams run Level 1 and Level 4 side by side — each task placed where its data and risk allow.

The GTM Maturity Model · level 1 → 5

Name your maturity level before you scale it.

most teams1Ad hocHeroics & gut feel. No shared system.
2RepeatableA playbook exists; some of it gets used.
OS installs3DefinedOne language across the team — the OS is live.
4ManagedDecisions run on data and the 5×5 matrix.
5Self-optimisingThe machine compounds — AI-native growth.
The leap that matters is Level 1 → 3 — one shared language across the team. That is exactly what installing the OS does.
The OS

AI is one model of eight.

The AI Maturity Model is how the OS scales — paired with Data, Moat and Operation. See how the whole engine runs.