AI organisation readiness
It takes whatever your organisation already does and does more of it, faster. Most companies asking which AI tools to buy should be asking these six questions first.
Stage 1 · Decide
The team knows what matters and can say no to everything else.
The three answers test. Ask three people, separately, to name the top three priorities this quarter. Reveals:If you get three different answers, you have your answer.
AI speeds up delivery. If the priorities are wrong, you just build the wrong things faster.
Stage 1 · Decide
One named owner per outcome, with decision making authority.
The failed project test. Pick a recent project that went wrong and ask who owned it. Reveals:A team name means ownership is diffuse. Multiple names means it is contested.
AI makes producing work easy. Someone still has to review it. If no one owns it, it piles up unread.
Stage 2 · Learn
Retrospectives happen, produce actions, and the actions change behaviour.
The action audit. Pull the actions from the last three retros and count how many were done. Reveals:A retro that produces uncompleted actions is a meeting, not a team that learns.
Getting value from AI needs evaluations and learning. It makes mistakes. If nobody looks at what went wrong, the same mistakes keep happening and there is no progression.
Stage 2 · Learn
How the organisation works is written down, not held in one person’s head.
The bus factor count. For each critical system, ask who else could run it tomorrow. Reveals:Every answer that comes back ‘nobody’ is a dependency AI cannot help with.
AI is only as good as the context you give it. If how things work lives in people’s heads, there is nothing to point it at.
Stage 3 · Scale
Trusted data, trusted deployments, and clear rules on what AI is allowed to do.
The metric trace. Take one number leadership reviews and trace it back to raw data. Count the manual steps and name who would notice if one broke. Reveals:Fragile manual pipelines that any AI application will inherit.
AI answers always look right. Built on bad data they are wrong at scale, and they still look right.
Stage 3 · Scale
The organisation has adopted new ways of working before, and made them stick.
The adoption ledger. List the last five changes you attempted and count how many stuck past six months. Reveals:Fewer than three, and AI is just another change that will not stick.
AI adoption is a change problem, not a tooling problem. Push it on a team that is not ready and ‘we tried AI and it did not work’ joins the graveyard of past initiatives.
Score each 1 to 4
At that level AI amplifies the dysfunction rather than routing around it. A contained pilot is a fine way to surface these gaps. Betting core operations before closing them is not.
These six dimensions are the spine of our readiness to scale assessment: a fixed-scope diagnostic with field tests and a scored read of where you stand. If the questions landed close to home, we’d love to talk.