This is an extract from the deliverable a company receives at the end of an AI-Ready audit: 6 dimensions, 24 scored criteria, a maturity score and prioritised recommendations. The client cannot be identified — and no client outcome is claimed here.
Proof is only worth something if its scope is clear. Here is exactly what was kept, what was removed, and what is not demonstrated.
The client is a French SME. Its sector, size and location are deliberately withheld: those are precisely the details that would make it recognisable.
The question asked was the one most business owners are asking today: where do we start with AI — and is this even the right time? AI projects in SMEs rarely fail for technical reasons. They fail because the data cannot be mobilised, because processes are not measured, or because nobody internally owns the subject.
So the audit does not set out to sell a technology. It establishes a factual picture, scores what is in place, and states what must be consolidated before investing.
Each dimension — Data, Processes, Tools, Governance, Skills, Culture — is scored on four criteria, each rated from 0 (Non-existent) to 4 (Optimised). The overall score is the sum of the 24 ratings, brought back to 100.
Scores are based on interviews and on a review of the material the company provides. Where a point was not covered, the report says so explicitly rather than estimating it — that is a constant drafting principle.
The AI-Ready audit format is scoped over 2 to 3 weeks.
The report itself is in French. This page summarises its content and method in English; the PDF has deliberately not been re-typeset, so that what you download is exactly the document that was produced.
Every page carries the notice “Version publique anonymisée — exemple de livrable LinkTec Labs” (anonymised public version — LinkTec Labs sample deliverable).
Three generic findings that hold well beyond this company.
The same company scores 3/4 on GDPR compliance and 0/4 on centralising its data. An overall score — here 44/100 — says almost nothing unless it is broken down. The value of an audit lies in the detail, not the average.
Some processes were already automated (4/4), yet no tracking of delays, errors or re-keying existed (0/4). Without measuring friction, there is no way to prioritise where automation would help most — nor to demonstrate a gain afterwards.
Culture 10/16, Tools 4/16: teams open to change, already through one successful transformation, but a closed information system and no AI tool deployed. Willingness does not compensate for missing foundations.
Fourteen pages: scope of the extract, method and reading grid, maturity profile, the six dimensions in detail, the synthesis and the full scoring grid. No sign-up required.
Download the extract (PDF)Twenty minutes are enough to tell whether an AI-Ready audit makes sense for you — and, if it does not, to say so.
