AI Readiness

AI readiness measures how prepared an organisation's data, processes, people and governance are to run AI in production, and it is assessed before any model is deployed.

Business & strategyAI readiness assessmentAI maturity
§ 01DefinitionAI Readiness

No jargon, no math

In plain words, what is it?

Readiness is a checklist of four gates. Data: can software actually read what you work with, or does it sit in binders, scans and inboxes? Process: is the target workflow documented, or does every senior operator carry it in their head? People: will users trust the system enough to correct it, and is there a named owner for when it errs? Governance: who signs off, who audits, who can switch it off? You score each gate honestly, and every “not yet” routes to remediation: digitise, document, train, assign. Where it breaks: skipping the gates because a demo looked easy, and discovering in production that your inspection reports were never digitised.

§ 02How it worksFour gates: data, process, owner, then the pilot
  1. 01

    Data. Can the AI read what you actually work with? If not, digitise and clean first.

  2. 02

    Process. Is the workflow written down and stable? Steps that live in one person's head kill automation.

  3. 03

    Owner. Someone named must run the system, answer for it and be able to switch it off.

  4. 04

    Remediate. Every “not yet” goes to fixing, not to a brave pilot.

  5. 05

    Pilot. All gates green: now a pilot stands on solid ground.

§ 04

Want this running in your stack?

We design and ship AI systems with permissions, logs and human approval. It starts with a 30-minute scoping call.