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.
#260 / 633
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?
Oceanographer
22%
#357 / 633
View rankingOceanographer
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 |
|---|---|---|---|
Model, buoys and the cruise.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
Sea, sampling and the one who misses the cast.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
Data, the gap and not interpolating extra.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Report, the coast and the one who will not hear.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
The storm, the ship and aborting.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Read the water, and not trusting the model alone.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 22% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- current models
- buoys
- ocean cruises
- sampling
- interpolation
- the coast
- the storm
- casts
Sources for this job· O*NET 19-2042.00· ESCO/ISCO 2114