AI summary (citable)
Attendance is not adoption. The AI adoption KPIs worth tracking after training measure whether people actually use the tools, whether real tasks moved to AI and stayed there, how much time was freed and how many artifacts shipped. Pick a small set of these before the training, capture a baseline, then measure again at thirty and ninety days. The strongest single signal is a real task that moved to AI and did not move back, which a hackathon produces by design.
Contents
- The real question adoption KPIs should answer
- The KPIs that matter, and the ones that mislead
- How to baseline before you train
- The decision framework in four questions
- Honest cost logic without invented prices
- A worked model with math
- Adoption over time, visualised
- Why a thirty-day dip is normal
- EU AI Act: what Article 4 asks for
- What you should do next
- FAQ
1. The real question adoption KPIs should answer
The question is not "did people attend" or even "are people satisfied", it is "is work being done differently, and is it sticking". Satisfaction scores feel good and predict little. A KPI set built around behaviour, active usage, tasks retained on AI, time freed and artifacts in production, answers the real question. If you cannot see those, you are measuring the event, not the adoption. Decide the behaviour you want to see, then measure that.
If your only number after a training is the attendance sheet, you measured the room, not the work. Adoption lives in what people still do in ninety days. – Tim Jamboula, Founder of Corporathon
2. The KPIs that matter, and the ones that mislead
| KPI | What it tells you | Signal quality |
|---|---|---|
| Active weekly users on the tool | whether usage is real, not one-off | strong |
| Tasks retained on AI at 90 days | whether the change stuck | strong |
| Hours freed per person per week | whether it produced value | strong |
| Artifacts shipped and in use | whether output is real | strong |
| Prompts run per user | activity, not outcome | weak on its own |
| Satisfaction score | sentiment, not behaviour | weak on its own |
| Attendance rate | presence, not capability | weak |
Weight the strong KPIs and treat the weak ones as context. High prompt counts with no retained tasks is activity theatre. A single retained task with real hours freed beats a wall of satisfied faces.
3. How to baseline before you train
A KPI without a baseline is a number with no meaning. Before the training, capture the current state of the two or three tasks you expect to change, how long they take, who does them, how often. That baseline is cheap to collect and it is what turns a post-training number into evidence. Without it, you are left guessing whether ninety hours a month were always spent that way or not.
4. The decision framework in four questions
- Which two or three behaviours must change? Measure those, not everything. A short KPI set beats a dashboard nobody reads.
- Do you have a baseline? Capture it before the training, or the after-number means little.
- When will you measure? Set thirty and ninety-day checkpoints upfront, adoption shows over time.
- Who owns the numbers? A KPI with no owner is not tracked. Name the person before you start.
Strong answers mean your measurement will be credible. Weak answers mean fix the baseline and ownership before you spend on the training.
5. Honest cost logic without invented prices
Credible pricing depends on variables, not a flat rate. Measurement has its own honest cost.
Instrumentation. Some tools report usage natively, others need light setup. That effort is real.
Baseline collection. Capturing the starting state takes time upfront and saves argument later.
Review cadence. Thirty and ninety-day reviews are recurring effort, not a one-off.
Ownership. Someone has to own the KPIs, which is a real, if small, cost.
Corporathon deliberately shows no fixed prices yet. The right shape comes out of these variables in a short call.
6. A worked model with math
A purely illustrative model you can replace with your own figures.
You track one KPI, hours freed per person per week, for a team of ten. Baseline shows a task taking three hours per person weekly. At the ninety-day check, active users have moved 40 percent of it to AI.
Hours freed: 1.2 hours × 10 people = 12 hours per week.
Across 45 working weeks: 540 hours per year.
At an internal rate of 58 EUR per hour: about 31,320 EUR of modelled annual value, visible only because a baseline existed.
This is a model, not a guarantee and not a client figure. The point is that the value was measurable only because a baseline was captured and a real KPI was chosen, not because a satisfaction survey scored well.
7. Adoption over time, visualised
Visualization: adoption curve after training (schematic).
adoption
100% |
| ___------- plateau (stuck)
75% | __------
| __-
50% | _-- dip and recovery
| _- \___ /
25% | _- \____/
| __-
0% +---------------------------------------------->
day 0 day 7 day 30 day 60 day 90
8. Why a thirty-day dip is normal
Without repetition and application, retained knowledge drops fast, which is what the forgetting curve has described since the 19th century. That is why adoption curves often dip around day thirty, the initial enthusiasm fades and the old workflow tempts people back. Teams that reach the ninety-day plateau are usually the ones who scheduled application early and had support through the dip. A KPI set that only checks at day seven misses this entirely and calls a training a success right before it fades.
9. EU AI Act: what Article 4 asks for
Since 2 February 2025, Article 4 of the AI Regulation asks for a sufficient level of AI literacy among staff, appropriate to role and context. Adoption KPIs support this indirectly, retained tasks and documented usage by role are stronger evidence of literacy than an attendance list. The KPIs are a building block, not an official certificate, and they do not guarantee automatic compliance. The company assesses the adequacy of its overall programme itself.
Choose your adoption KPIs before you train
Two ways in, depending on how far along you are.
Book directly: Book a strategy call. Thirty minutes, we pick two or three KPIs and a baseline for a real task.
Read first: drop your email and get the adoption KPI template plus a baseline sheet. No spam, unsubscribe anytime.
10. What you should do next
Pick two or three behaviour KPIs, capture a baseline before any training, and set thirty and ninety-day checkpoints with a named owner. Weight retained tasks and hours freed over prompt counts and satisfaction. If you want a fast way to generate both the behaviour change and its baseline, run a hackathon on a real task. In just one week you can go from first call to a working prototype whose usage is your first data point.
Ready when you are
Book directly: Book a strategy call. We pick KPIs and a baseline for a real task.
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