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Where does your organisation stand with AI?

Answer 10 questions and find out how ready you are out of 100. You’ll also get suggested next steps to improve your readiness.

Start the check
  1. Unaware 0–20
  2. Exploring 20–40
  3. Experimenting 40–60
  4. Operational 60–80
  5. Embedded 80–100

See where you stand.

An AI readiness assessment in ten questions, about five minutes.

The score is worked out in your browser.

With JavaScript off there is no on-screen score, but the ten questions are all here. Answer them for yourself, then tell us what you found and we will read them with you.

OpenKit readiness check

About you 01–03
01

What's your role?

Pick one

We tailor the recommendations to the kind of decisions you can actually make.

02

What industry are you in?

Pick one

This never changes your score; it only shapes the recommendations.

03

How big is the company?

Pick one

Team size shapes which AI patterns actually work for you.

How the team uses AI today 04–08
04

Which AI tools is the team paying for or using regularly?

Pick all that apply

Multi-select. We care about what people actually open, not what shows up on the company card.

05

How would you describe the team's overall AI use?

Pick one

Honest answers get better reports. We've seen 'don't know' enough times that it doesn't count against you.

06

Where is AI actually being used?

Pick all that apply

Multi-select. The areas where work has visibly changed — not the ones where it could.

07

What's stopping the team getting more out of AI?

Pick all that apply

Multi-select. Pick the ones that genuinely apply — this is where most of the report comes from.

08

Are any of these quietly happening?

Pick all that apply

Multi-select. This stays between you and the report — but it informs the risk section honestly.

The year ahead 09–10
09

What's one thing you'd fix about how the team uses AI today?

Optional, free text

Optional. One sentence is fine. This is the quote the report opens with.

10

AI plans for the year ahead?

Pick one

This sets the urgency of the recommendations.

A result you can act on.

Answered honestly, the ten questions give you an indicative read of where your team stands and which risks are worth acting on first. Three things come back.

Your score and tier

A number out of 100, and where it lands on the five stages.

The risks in your answers

The quiet ones an audit flags first, surfaced from what you told us.

Three moves to make next

Concrete steps, chosen from your answers, across the pillars that matter.

How the score reads.

The scale is the arc at the top of this page: five stages, twenty points each, unaware through to embedded. Your industry sets the benchmark you are read against, and it never moves your own score.

  1. Unaware0–20

    AI hasn't meaningfully arrived yet. That's a cleaner starting point than a mess of half-adopted tools, and the first move is mapping where it would earn its place.

  2. Exploring20–40

    Tools are appearing but the work hasn't changed shape yet. The next stretch decides whether this compounds or stalls.

  3. Experimenting40–60

    Pockets of real use, no system. You're one decision away from momentum, or from sprawl that a future audit has to untangle.

  4. Operational60–80

    AI is doing real work in places. The gap now is coverage, governance and measurement, the unglamorous half that makes it stick.

  5. Embedded80–100

    Ahead of the indicative benchmark for your industry. The next step is measuring impact properly and hardening the governance underneath it.

An AI audit is where that read gets grounded in your actual tools, data and workflows, and where the number stops being indicative.

The plan draws from five pillars.

Your three moves are chosen from these, weighted by where the gaps are in your answers.

01

Strategy & leadership

  • Define the business problem first
  • Translate problems into measurable KPIs
  • Craft and socialise a clear AI vision

02

Data & infrastructure

  • Run a non-technical data audit
  • Prioritise one high-value data domain and focus all cleaning effort there first
  • Stand up a lightweight data governance council to set rules for quality and access

03

People & culture

  • Launch an AI fluency programme so the whole team knows what the tools can and cannot do
  • Identify and back your AI champions, the early adopters who will mentor their peers
  • Create safe, low-risk space to experiment, and frame AI as augmenting people, not replacing them

04

Governance & ethics

  • Assemble a multidisciplinary risk council across legal, security, HR and the business
  • Adopt a recognised framework like the NIST AI RMF rather than inventing your own
  • Make a basic risk assessment mandatory in every new AI project proposal

05

Implementation & value

  • Pick one high-impact, manageable pilot against a significant pain point with a contained scope
  • Measure a baseline before launch so the after has a before to point at
  • Define balanced KPIs across cost, capability and strategic value, then review honestly

Things people ask.

How long does the AI readiness check take?

About five minutes. Ten questions, most a single click, and one optional open-text box you can skip. Your answers stay in your browser unless you choose to send us your details.

What do I get at the end?

A score out of 100, your tier on a five-stage scale, the risks we noticed in your answers, and three concrete moves to make next. It is all on screen, and it downloads as a PDF if you want a copy to keep.

How accurate is the score?

It is an indicative self-assessment, scored from your answers in your browser. An AI Audit is where the picture becomes grounded in your actual tools, data and workflows.

What happens to my answers?

They score your result in your browser. Nothing leaves your device unless you ask for the PDF after your result, in which case your answers reach the OpenKit team. The PDF is built in your browser too. De-identified aggregates feed our analytics; we do not sell your answers or pass them on.

Will OpenKit contact me afterwards?

Only if you ask for the PDF and turn the follow-up switch on, and it is off until you turn it on. The result is yours either way, and it tells you how to reach us if you want to take it further.

How is the score worked out?

Each answer carries a weight: role, size, tools, where AI is used, what is blocking it, and the risks quietly running. Your industry never changes your score; it only shapes the recommendations.

Do I need to sign up or install anything?

No. There is no email gate and nothing to install. You answer ten questions and read your result on the page; the PDF copy is optional, and that is the only step that asks for your details.

Who is OpenKit?

A UK AI engineering firm. The questions here are the ones we ask in the first hour of a real audit; when the picture warrants it, we build and embed what earns its place.

Take your result into an audit.

The check shows where the gaps are. An audit puts numbers on them inside your actual workflows, and we build the first automation into how your team already works. We reply within one working day.