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AI Readiness Assessment

An AI readiness assessment checks whether a team has the people, processes, knowledge, tools, governance, leadership and measurement it needs to adopt AI. Answer 10 questions about your team and get a score with next steps.

10 questions
PeopleHow comfortable are most employees using a generative AI tool for their own work?
UsageHow often do employees currently use generative AI at work?
ProcessesHave you identified specific recurring tasks where AI should be used?
ProcessesWhen AI is used, is it a one-off chat or a repeatable workflow?
KnowledgeHow easy is it to give AI approved source material — notes, price lists, policies, procedures?
ToolsWhich AI tools are employees allowed to use?
GovernanceDo employees know which information must not go into an AI tool?
GovernanceBefore AI output is used — sent to a customer, put in a report — who checks it?
LeadershipHow involved is leadership in AI adoption?
MeasurementHow do you know whether an AI workflow is working?

How it works

Ten multiple-choice questions cover eight areas. Each answer scores 0 to 4. Your overall score is the average across all answers, scaled to 100; each area gets its own score the same way. The calculation is fixed and runs in your browser — the same answers always give the same result.

ScoreStageWhat it usually looks like
0–25ExploringAI is mostly individual curiosity. The fastest progress comes from one approved tool and one narrow task per team.
26–50Early adoptionPeople are using AI, each in their own way. The gap is shared workflows, written data rules and someone who owns adoption.
51–75ScalingThere are real workflows and some structure. The work now is consistency: review steps, measurement, and training by function.
76–100AI-enabledAI is part of how work gets done, with ownership and review. Keep measuring, and retire workflows that stopped earning their place.

Why this matters

Most teams do not fail at AI because of the model. They stall because nobody decided which tasks are worth it, which tool is allowed, what data is off-limits, or who checks the output. Those are organisational questions, and they can be answered in an afternoon once someone asks them.

How to interpret your result

  • Look at the lowest area first. An overall 60 with governance at 25 is a governance problem, not a 60.
  • Compare answers inside the team. If a manager answers “written guidance” and the team answers “no guidance”, the guidance has not landed.
  • A low score is not a verdict. Exploring is where every team starts. The next step is one tool and one narrow task.
  • A high score needs evidence. If you scored 80+, can you name three workflows, their owners and when each was last reviewed?

What the eight areas cover

  • People. Comfort comes from doing one real task, not from a product tour. Train each team on work it already does.
  • Usage. Have each person list three weekly tasks and score them. The narrowest task that passes becomes their first workflow.
  • Processes. A chat gives an answer. A workflow has inputs, steps, a reviewer and an owner, and runs the same way next week.
  • Knowledge. If nobody can point to the approved notes, price list or procedure, the model has nothing reliable to work from. Fix the source first.
  • Tools. People are already using personal accounts. Pick one approved tool, make it available, and tell everyone which one it is.
  • Governance. Two lists: what must never go into an AI tool, and which outputs need a named person to check them before use.
  • Leadership. Adoption stalls when it is everybody’s side project. One named owner, one page a week: what changed, what is at risk, what needs a decision.
  • Measurement. Ask three things: was it tested on real work, was it accurate enough to use, should it continue. Attendance and enthusiasm are not measures.

Best practices

  • Have three or four people take it separately, then discuss the differences.
  • Retake it a quarter after training. The area scores should move; if they do not, the training did not change the work.
  • Do not average teams together. Sales and operations are usually at different stages.

Questions people ask

What is an AI readiness assessment?

An AI readiness assessment evaluates whether a team has what it needs to adopt AI effectively: people who are comfortable using it, identified tasks, documented source material, approved tools, data and review rules, leadership ownership and a way to measure results.

How long does it take?

About three minutes. There are 10 multiple-choice questions and you see your score immediately.

Do I need to enter my email?

No. The score, the category breakdown and the recommendations are shown without sign-up. Nothing you answer is sent to a server; the calculation runs in your browser.

Is the score scientifically validated?

No. The AI Man Jack AI Readiness Score is a structured self-assessment based on what we see in hands-on training sessions. It is a conversation starter for a team, not a benchmark against other companies.

Who should take it?

Whoever is responsible for how a team works: a department head, an operations lead, a founder. It is most useful when three or four people on the same team take it separately and compare answers.

What should we do with a low score?

Start with the lowest category. In most teams that is governance or processes: write down what must not go into an AI tool, then pick one narrow recurring task and turn it into a workflow with a named reviewer.

Turn the score into a plan.

A half-day workshop covers the lowest areas with your team, on tasks they already do.

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