Readiness scorecard

Where is your Ai rollout about to stall?

Buying Ai is the easy part. Using it is where things break. The 2026 AWS and Strand Partners report found 64% of UK organisations now use Ai in some form, up from 52% a year earlier, yet only 24% of those adopters have wired it into how the business actually runs.

This is the 12-point check we run before every engagement. Score yourself honestly and find out where your own rollout is most likely to stall, before you spend more on it.

12 questions · about 5 minutes · no call

For each statement, pick No (0), Partly (1) or Yes, and we could prove it (2). Your score and result update as you go.

1 · Strategy and goals

1. We can name the two or three business outcomes we want Ai to move, we have picked the specific tasks where it should help, and we would know if it had moved them.

2. Someone senior owns Ai adoption as a goal, not just Ai purchasing, and it sits on a real plan with dates, time and budget behind it.

2 · Tools and data

3. The people meant to use our Ai tools can actually get into them, with the right access and data, without asking for help every time.

4. Our key information (customer records, documents, processes) is organised well enough that Ai can use it safely and give useful answers.

3 · People and fluency

5. Our team can decide what to hand to Ai and brief it clearly, so they get a useful first draft rather than a vague one.

6. Our team checks Ai output for quality and accuracy, and a person makes the final call on anything that matters.

7. Fluency is spread across the team, not stuck with one or two enthusiasts, so the work does not stop when one person is away.

4 · Process and integration

8. Ai is built into how specific jobs actually get done, with a clear step in the workflow, rather than a separate tool people open when they remember.

9. When Ai does part of a task, we have agreed who reviews it, where the output goes, and how it joins the rest of the work.

5 · Governance and risk

10. We have simple, written ground rules for Ai use (what data can go in, what must stay out, what needs a human sign-off) and the team knows them.

11. We can explain how we use Ai to a customer, auditor or regulator without scrambling, and we keep a basic record of where it is used.

6 · Embedding and measurement

12. Tools we have rolled out are still in genuine daily use 30 days later, and we measure that rather than assuming it.

Your result

0 / 24

0 of 12 answered

Answer the 12 statements to see where your rollout is most likely to stall.

Book a discovery call

Pick the single statement you scored lowest and fix that first. It is almost always worth more than buying another tool.

Keep your result

Want your score and a short action plan emailed?

No call, no pressure. We will send your result, the next step for your band, and a one-page plan for the gap you scored lowest.

Sources. AWS and Strand Partners, Unlocking the UK’s AI Potential (2026): 64% use Ai, 24% of adopters advanced. MIT NANDA, The GenAI Divide: State of AI in Business (2025): about 95% of pilots showed no measurable profit-and-loss impact (coverage). BCG, Where’s the Value in AI? (24 October 2024): 74% yet to show value. Brynjolfsson, Li and Raymond, Generative AI at Work, Quarterly Journal of Economics 140(2) (2025): 14% average productivity gain. The 4 Ds of Ai fluency are from Anthropic’s Ai Fluency framework.