AILAT
Organization report
Illustrative AI literacy baseline
A workforce-level view of current AI knowledge, practical application, critical evaluation, and responsible use.
Executive snapshot
Overall readiness
A concise baseline for deciding where learning investment should go first.
Organization average
59.4/100
2.6 / 5 · Cohort average
A continuous cohort average. The distribution below shows the profile behind it.
- Relative strength
- Conceptual
- Priority dimension
- Evaluate & Create
Participation
Assessment coverage
Coverage is reported alongside outcomes so the program team can judge how representative the baseline may be.
- Links distributed
- 100
- Started
- 89
- Completed
- 84
- Outstanding
- 16
Four-dimension profile
Where capability is concentrated
Organization averages use a 0–100 scale. Read the shape across dimensions before reducing the result to one number.
Distribution
How literacy levels are spread
The cohort profile can reveal a mixed starting point even when the overall average appears straightforward.
- Level 1Foundational14%
- Level 2Emerging31%
- Level 3Capable36%
- Level 4Critical15%
- Level 5Advanced4%
Cohort comparisons
Differences across privacy-eligible roles
Only groups meeting the minimum reporting threshold appear. In a live report, unsafe breakdowns are withheld or folded before the data reaches this page.
| Role / function | Completed | Average score | Literacy level |
|---|---|---|---|
| Sales / Consulting | 22 | 60 | Level 4 · Critical |
| Project Management / Consulting | 18 | 56 | Level 3 · Capable |
| Research | 17 | 64 | Level 4 · Critical |
| Assistant | 9 | 48 | Level 3 · Capable |
| Other | 18 | 55 | Level 3 · Capable |
“Other” is a privacy-protected folded group—not an extra role category chosen by the client.
Recommended action
Turn the baseline into a learning plan
The report translates the weakest shared dimensions into practical, vendor-neutral priorities.
- 01
Strengthen evaluation before increasing tool complexity
Practise checking AI output against source material, spotting unsupported claims, and deciding when human review is required.
- 02
Turn responsible-use principles into role-level routines
Use realistic scenarios to connect privacy, bias, transparency, and accountability to the decisions each function already makes.
- 03
Preserve the conceptual strength while training application
Build practical exercises on top of the cohort’s stronger conceptual base rather than repeating a generic AI introduction for everyone.
Method & privacy
How to read this report responsibly
Aggregate evidence only
Individual results are not included. Groups below 5 completions are not shown, and complementary suppression limits inference by subtraction.
Important limitations
Results measure current AI knowledge and reasoning, not proficiency with a specific tool. They are not designed for hiring, employee ranking, certification, or causal claims about training impact.