What the assessment includes
What the quick questionnaire checks, what the deeper interview asks, and why the assessment measures behavior instead of tool knowledge.
The assessment has two parts. The quick questionnaire gives the first orientation. The deeper interview verifies what someone actually does with AI.
The two parts complement each other. The questionnaire shows how someone perceives their own work with AI. The interview adds concrete examples, outputs, and working habits.
#Quick questionnaire
The quick questionnaire takes about 5 minutes. It asks about four ways of working with AI:
| Area | What it looks for |
|---|---|
| Conversation | How someone uses AI for thinking, research, summaries, and problem solving |
| Creation | How they create texts, presentations, visuals, or drafts with AI |
| Building | Whether they use AI to create tools, websites, prototypes, or scripts |
| Orchestration | Whether they connect multiple steps, tools, or automations |
The questions are not a quiz. We do not ask whether you know the names of the newest models. We care where you actually use AI and how deeply you work with it.
#Deeper interview
The deeper interview is led by Aimee and takes about 15 to 20 minutes. It asks like a curious colleague, not an examiner.
It typically asks about:
- the last concrete situation where you used AI,
- repeated tasks you do again and again,
- tools you actually use,
- outputs, templates, or workflows you created with AI,
- places where work with AI gets stuck.
At the end, there may be a practical scenario from your field. We are not looking for the "right answer". We want to understand how you would think about the situation and where you would involve AI.
#Why the assessment is short
With AI, a few good questions are more useful than a long questionnaire. One concrete situation often says more than ten general scales.
That is why we combine a short questionnaire with an interview. When what someone says about themselves differs from what they describe in concrete examples, concrete behavior carries more weight.
#What the assessment does not test
- Knowledge of specific prompts.
- Awareness of the latest AI trends.
- Technical programming skills.
- Personality or "AI talent".
We measure current practice: how someone uses AI, what outputs are created, and whether the way of working changes.
#How answers become a result
The questionnaire creates the first hypothesis. The interview confirms, adjusts, or sharpens it. The result is a level, a natural style of working with AI, a next step, and a baseline numeric measure for later comparison.