by AIVantum

AI Readiness Quick Check

An honest self-check in 10 to 15 minutes: Where does your team really stand when it comes to using AI — and which foundation is currently blocking the next step?

0 / 30 answered

AI Readiness · Quick Check

What this is about

The question "Are we ready for AI?" is diffuse. This quick check translates it into a structured view: across five dimensions, it shows which foundation holds and which one is holding back the next step. At the end, you receive an overall rating, a heatmap per dimension, your levers, and a roadmap teaser — instantly, with no waiting.

Purpose

An orientation, not a report card. A first, honest view of where the next sensible step lies.

Duration

About 10–15 minutes. 30 statements, each rated on a scale from 1 to 5.

Who it is for

A leader or team lead answering on behalf of their own team.

What this test deliberately cannot do — and that is by design. It measures how you see your team yourself, not how it objectively is. The gap between stated and lived readiness, the why behind the gaps, and what a change would really cost in your day-to-day — only the guided conversation uncovers that. The quick check is the honest first stage, not a substitute. More on this at the end.

How to answer

You rate each statement on a scale from 1 (does not apply at all) to 5 (fully applies). If you cannot assess your own position, choose “don't know”. In the assessment it counts as the lowest readiness, because not knowing where you stand is itself a readiness signal.

1Does not apply at all
2Tends not to apply
3Partly applies
4Tends to apply
5Fully applies / established
?Don't know (counts as the lowest readiness)

Statements marked reverse-scored are deliberately phrased in the opposite direction: there, strong agreement means low readiness. They are converted automatically in the assessment (6 − value) — no mental arithmetic required, just answer honestly. “Don't know” and unanswered statements count as the lowest readiness there as well.

1

Foundation

The question behind it: Is there any ground at all for AI adoption to stand on? (Technical & process prerequisites)
My team has a secure, approved environment in which we may use AI tools without requesting individual approval every time.
Our most important recurring workflows are documented well enough that a new colleague could follow them without being talked through.
We have at least one workflow in which AI is already used regularly, not just sporadically.
So far, AI use in our team happens rather by chance — when someone experiments privately — not systematically.reverse-scored
The tools we would need are technically within reach (access, licensing, and budget are settled).
For processes that run through several units, everyone can see who is handling them right now and who decides when there is disagreement.
2

Data & Context

The question behind it: Does AI find reliable material here, including what so far exists only in people's heads? (Findability, access, terms and rules, keeping knowledge current)
The data we need for our work is findable and not scattered across people's heads, email inboxes, and individual drives.
AI answers here often stay generic because the AI does not know our terms, rules and processes.reverse-scored
It is clearly regulated who may access which data and who is responsible for it.
What we have clarified once, such as an exception or a follow-up question, is available the next time instead of having to be asked again.
Our data is predominantly digital and machine-readable, not stored in paper, screenshots, or unstructured PDFs.
The unwritten rules of our work, meaning exceptions, special cases and how decisions are really made here, are written down and not just in individual people's heads.
3

People

The question behind it: Are people able and willing, and do they trust themselves to do it? (Skills, stance, self-efficacy)
Most people on my team could name a specific task where AI already makes their own work easier.
Our attitude toward AI is neither blanket rejection nor blanket hype, but a sober "it depends on what for".
There is room and time for us to try new things without a failed attempt being penalized.
People on my team worry more about being replaced by AI than they feel relieved by it.reverse-scored
I personally feel confident enough to judge when an AI result is usable and when it is not.
We talk openly about what AI is changing for us, rather than everyone quietly drawing their own conclusions.
4

Governance

The question behind it: Are there guardrails, or are we driving without them? (Rules, accountability, ethical guardrails)
It is clear to us what is and is not allowed when working with AI (which data may go in, which may not).
There is a designated person or role accountable for the responsible use of AI.
We have engaged with the transparency and labeling obligations of the EU AI Act that take effect in August 2026.
For our most important expert knowledge, there are named owners who keep it current when rules or processes change.
Here, everyone uses AI at their own discretion — there are no shared rules for it so far.reverse-scored
It is clear to whom a problem or a borderline case in AI use gets escalated.
5

Value Creation & Use Cases

The question behind it: Do we know where AI truly creates value and where people remain irreplaceable? (Condensed operational facets)
We could name two or three specific workflows where using AI would noticeably pay off.
We consciously distinguish between tasks where AI should support us and those that must remain in human hands (judgment, relationships, responsibility).
For the workflows we would automate, the desired outcome can be described clearly enough that success would be recognizable.
We review AI results before we use them further, rather than adopting them unchecked.
Here, AI is used mainly where it happens to attract attention or is demanded, not where the benefit would be greatest.reverse-scored
We would have a rough idea of what benefit would stand against the effort of introducing it.

Not all statements answered yet. Missing answers count like “don't know”, i.e. as the lowest readiness.

Your assessment

Without JavaScript, no computed assessment is shown here. The questionnaire above remains fully readable. Enable JavaScript to see your overall rating, the heatmap per dimension, your levers, and the roadmap teaser. The methodology below applies regardless.

What this self-check deliberately cannot do

These limits are not a weakness to be optimized away — they are what makes the test honest:

  • Self-assessment is not an outside view. The test measures how your team sees itself, not how it is. Only the guided conversation uncovers the gap between stated and lived readiness.
  • It says what, not why and not what it costs. The report shows which step would come next. Why that matters right now and what it costs in your day-to-day — only the conversation answers that.
  • No benchmark, no employee assessment. The quick check is a reflection anchor, never an evaluation instrument for individual people.

The next step: consultant-guided depth

This check shows your profile. What it cannot do: work through the gaps with your team, mirror the self-assessment against lived practice, and assess what the next move would really cost in your context. This is exactly where the guided diagnostic comes in.

Fair and without surprises: the quick check and the initial conversation are free of charge. Only once we have spoken and you decide you want an in-depth diagnostic does a small engagement follow — the fully developed report is then the actual service.

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