Automation index
How much of a Parking attendant’s job can AI already do?
A barrier comes earlier. Running the car park without wrecking the person who lost the ticket do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Parking attendant
24%
AI can already do 24% of this job.
#284 / 703
View rankingParking attendant
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Barriers, tickets and the count.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The one who cannot find the car and the one who will not pay.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Incidents, the down barrier and the jam.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Shift, cash and cashing up.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
The event, the full house and not blocking the street.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Run the car park, and not wrecking the lost-ticket person.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 24% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- barriers
- parking tickets
- space count
- cashing up
- stuck barrier
- events
- lost cars
- exit jam
Sources for this job· O*NET 33-9091.00· ESCO/ISCO 5414
IS WORK OVER?
Instructional designer
27%
#158 / 703
View rankingInstructional designer
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Aim, the storyboard and the module.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 48% | +8.6 |
Pilot, the learner and what is not understood.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Activity, the feedback and not putting a silly test.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
LMS, the figure and not inflating completion.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The client, the deadline and not cutting the practice.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That they learn, and not leaving the empty video.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 27% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- course storyboard
- modules
- learner pilot
- activities
- LMS
- completion
- feedback
- not a silly test
Sources for this job· O*NET 25-9031.00· ESCO/ISCO 2351