What is AI readiness assessment?
Scoring whether an organisation can absorb a specific AI deployment. Readiness for something, never readiness in the abstract.
A company can be entirely ready for document classification and entirely unready for predictive pricing. So an assessment that scores AI readiness in the abstract produces a number nobody can act on, and the first thing a real one does is name two or three candidate use cases to score against.
The second thing that separates a credible assessment is benchmark disclosure. A score of three out of five means nothing on its own; it means something relative to the client's industry, size and region. Where no real external benchmark exists for a dimension, saying so is the honest move - and most published assessments do not.
| On this | AI readiness assessment | A self-scored readiness quiz |
|---|---|---|
| What it examines | Real data samples, real systems, and the workflow as it runs | What the respondent believes the answer is |
| What it is anchored to | Two or three named candidate use cases | Nothing, which is why the output is a percentage |
| Who benefits from the conclusion | Whoever has to decide, including if the decision is to stop | Frequently the assessor, whose product turns out to be the answer |
- When it is the right answer
- Before a build, and specifically before the second build if the first one stalled.
Start here
If a term here is the one your board paper turns on, ask us about it.
We will send the entry, the evidence behind it, and the honest note about where it does not apply.
You get a reply within one working day, from the engineer who would do the work - not a sales sequence.