In short
- An audit looks at three layers at once: processes (which are repeatable and ready to support), data (where it is and whether it can be used) and people (who can lead the implementation from the inside).
- Without someone on the company's side, every implementation stays dependent on the supplier — which is why the people layer weighs as much as the data.
- The output is a roadmap for the year, not a deck: which area to support first, what to prepare in parallel, how to spread projects over time.
- Ideas from the company ≠ a catalogue of use cases. The list comes from the processes and bottlenecks of one specific plant.
- An audit can be skipped when there is one obvious, repetitive process crying out for support. Then a conversation is enough, and a full diagnosis would be spending money to confirm the known.
What the Audit Actually Checks
A good AI readiness audit looks at the company from several angles at once, because readiness isn't just about technology. The first is processes — which ones are documented, repeatable, and ready to support right away, and which need sorting out first. The second is data: where it lives, what condition it's in, whether it can actually be used, or whether it's scattered across spreadsheets, emails, and paper files. The third is people — who in the company has what it takes to drive the implementation from the inside and then keep developing the solution independently. Without that person, every implementation stays dependent on the vendor.
That's what the audit is really for: a list of concrete implementation ideas, each with a feasibility assessment, plus a return estimate for the most promising ones. Ideas drawn from this specific company — from its processes and bottlenecks — not copied from a generic catalog of AI use cases.
What You Get From the Audit
The result is a document, not a slide deck to file away in a drawer. A roadmap for the year ahead: which area to support first, what to prepare in parallel, how to sequence the following projects over time. Plus an executive summary and a return estimate in concrete terms — hours saved, fewer errors, new service capabilities.
The roadmap still holds even if the company spreads execution over a year and a half or two. It stays a recommendation — the company decides what to take from it, and when. As a side benefit, the same document often serves as the substantive backbone of a grant application, if the implementation is to be financed through the Dig.IT program.
When the Audit Makes Sense — and When to Skip It
Being honest here: not every company needs an audit.
It makes sense when a company has several departments and many possible directions, and it's not clear which one to tackle first. In that case, the roadmap saves months and money that would otherwise go toward the wrong choice. It also makes sense when the implementation is meant to be funded by a grant, since it provides a ready-made basis for the application.
You can skip it when the company already has one obvious, repeatable process that's clearly crying out for support, and just wants to start there. In that situation, the assessment fits into a short conversation, and a full audit would be an expense spent confirming something that's already known. A lighter entry point in that case is the Applied AI Test or a consultation — you can start with either one and decide afterward whether a full diagnosis is needed.
Frequently asked questions
What does an AI readiness audit examine?
Three things at once: which processes are documented and repeatable enough to support; what state the data is in and whether it can be used at all; and who in the company has the aptitude to lead the implementation from the inside and then develop the solution independently.
What does the company get from an audit?
A roadmap for the coming year together with a list of concrete ideas, each with a feasibility assessment and a return estimate for the most promising ones, plus a summary for the board. The map holds up even if the company spreads delivery over two years.
When is an audit not needed?
When there is one obvious, repetitive process that clearly calls for support and the question is simply where to begin. A short conversation or a free readiness assessment is then the lighter entry point, and a full diagnosis would be an expense confirming what is already known.
Is an audit useful for a grant application?
Yes — the same document often becomes the substantive backbone of an application when the implementation is to be financed from a grant. That is one of the situations where an audit pays for itself independently of the implementation.
What's Next
If you don't know where to start with AI and there are several possible directions, the audit is the cheapest way to avoid picking the wrong one. If your direction is already clear, start with a conversation and move straight to implementation. What exactly the audit includes, in which scale variants, and at what cost, I describe on its page.
→ See what the AI Readiness Audit includes
→ Book a 30-minute consultation
