Methodology

How the assessment is scored

The dimensions, the levels, the way answers become a number, and the things this measure will not claim. The option-by-option scoring key is the one thing not on this page: it goes to reviewers on request, because a key you have read is a score you chose rather than a measurement.

The five dimensions

Fixed, and the same for everyone. They are not weighted: the index is the plain mean of the five, so no dimension quietly counts more than another.

Awareness: Knowing where AI helps, where it fails, and when not to use it.
Instruction: Directing AI clearly with context, constraints, and intent.
Verification: Checking AI output for accuracy before relying on it.
Governance: Using AI within policy, privacy, and risk boundaries.
Integration: Building AI into real workflows so gains compound.

The four levels

Every dimension is scored one to four. The words matter more than the numbers, because the numbers average and the words do not.

Unaware

You have not yet worked out where this applies to you, so the risk it carries is unmanaged rather than accepted.

Exploring

You are using AI here and finding out what it does. Results are real but inconsistent, and you cannot yet predict which you will get.

Applied

You use this reliably for real work and know where it stops. This is the level at which AI is genuinely doing something for you.

Fluent

You direct this deliberately, check it where checking matters, and have built it into how work gets done rather than doing it by hand each time.

How an answer becomes a score

Each option in each question is mapped to one of the four levels. You pick an option, that option carries a level, and your score for a dimension is the mean of the three answers you gave for it. Three questions per dimension means a score lands on thirds rather than whole numbers, which is what lets it tell a 3.0 from a 3.3.

The mapping lives on the server and the browser only ever sends the option you chose, so the answer key is not readable in the page.

You're on a deadline. An AI tool gives you a specific market figure you need for a slide and cites a named, real-looking source. You have 20 minutes left.

What actually demonstrates good judgment here?

Verify every claim across the whole deck before you send any part of it on.
Cut the figure and rework the slide around it so that you do not need one.
Use it. It cites a named source, and you cannot chase every number on deadline.
Spend the 20 minutes on this one figure, because fabricated citations are common.

The highest-scoring answer is frequently not the most thorough or the most cautious one. Over-caution is a real failure mode and is scored as one.

What holds the headline band down

If any single dimension comes out at Unaware, the band next to your score is held at Exploring however high the mean is. The number is never altered, only the word.

An average hides its worst component. Someone Fluent on four dimensions and Unaware on Verification averages 3.4 and would otherwise read as broadly competent while being unable to tell whether AI output is true. That is the exact failure this measure exists to catch, so it is not averaged away.

What this will not tell you

No percentile until there are enough people. It appears at 20 results and not before. Only organic takers count. Demo data and paid research panels are excluded by construction, so a new source cannot quietly start counting.
No tier below the median. There is no participation label.
No movement claim on a thin round. A department shows movement only with at least 8 people measured in both rounds being compared. The organization figure needs 20. Below those, the arrow is not drawn at all rather than drawn faintly.
No arrow for a movement smaller than 0.2. On a one-to-four scale across a department, anything under that is inside the error on the mean. An arrow is a claim that something changed, so it is not printed for a difference this instrument cannot resolve.
No department mean below 5 people. A department reports a per-dimension mean only once that many of its people have been measured, on the dashboard and in the evidence pack alike. Below it the cell is empty rather than estimated. This is a convention rather than a derived bound — the standard deviation of this instrument is not established, so nobody can compute the point at which a mean becomes stable.
No superlative on a tie. If several dimensions are equally weak, the result says so rather than naming one.
This is not a credential. It is a rubric score and a description of a profile shape. It certifies nothing.

How a consultant is matched to you

The recommendation is derived from the result, not sold. Two things decide who appears:

The dimension you scored lowest. Consultants are tagged by hand for the dimensions they work in, and only those tagged for your lowest dimension are eligible. Where several dimensions tie at the bottom, Verification is preferred, because it is the one where being wrong is most expensive.
Rotation across everyone eligible. Which of them you see is fixed by your result id, so it does not reshuffle when you reload, but it differs between people. Demand spreads across the whole pool instead of collecting on whoever happens to sort first.

Anyone missing a photo, a description or a booking link is not shown at all, so a card is never a placeholder. Nobody is ranked by what they pay.

Disclosure. AIFluency operates the Coaching Hub and earns a fee on bookings made through it. We both measure the gap and sell help closing it, and you should read the recommendation knowing that.

What this score is not

This is a self-assessment of judgment across five dimensions. It is not a credential, and it has not been validated for use in selection, promotion, compensation or termination decisions. It has no established predictive validity for job performance, and the level mappings are ours rather than an external standard.

Use it to decide what to work on, and to see where a team is thin. Do not use it to decide who to hire, who to promote, who to pay more, or who to let go.

Who set the mappings, and what that is worth

The level mappings are set by AIFluency, informed by how each dimension plays out in real work. They are published rather than hidden so you can judge them yourself.

None of the fifteen has been reviewed independently. Every level assignment is a considered first pass by the author and has not been keyed by an outside practitioner. Until that happens, no single result is used to make a claim about any individual.

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