AI readiness diagnostic

Ten questions, and a clear read on where you stand

A score, your three biggest gaps, and what to do first. It takes about four minutes, and you can see your result without leaving your details.

What it measures

Ten things that separate a plan from a pile of tools

Start the diagnostic
  1. 01Documented AI strategy
  2. 02Cost of manual work measured
  3. 03A designated AI owner
  4. 04Internal execution capability
  5. 05Competitive AI monitoring
  6. 06Highest-return processes identified
  7. 07Team ready for adoption
  8. 08Clear selection criteria
  9. 09Data and AI usage policy
  10. 10Return measured and reported

The four bands

0–30

Initial stage

Streamline first

Your company is operating reactively. That is a normal place to start, and it is also the place where automating would do the most damage: automating a process nobody has mapped just makes the problems happen faster. The first move is a process audit, not a tool.

31–60

Developing

Connect what you have

You have pieces in place but no strategic coherence between them. You are likely paying for tools that do not talk to each other, with no clear owner. The gain here is not another tool — it is consolidating what exists and deciding who owns the agenda.

61–80

Foundational

Optimize and extend

You have a real foundation. What is usually missing at this stage is the architecture layer: deciding what gets built next, what gets retired, and how the systems you already run get documented well enough that they survive the person who built them.

81–100

Ahead of the field

Scale what works

You are further along than most companies your size. The next step is scaling what already works without multiplying the maintenance burden, and making sure governance keeps up with the surface area you have built.

Let's talk

Send me the process that costs you the most time.

I will tell you whether it is worth automating before you spend anything. Thirty minutes, no commitment, no pitch deck.