Automation index

How much of a Waste technician’s job can AI already do?

A waste code comes earlier. The waste going where it should, not the next bin, do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

IS WORK OVER?

22%

AI can already do 22% of this job.

#392 / 633

Waste technician

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
Code, characterise and the paper. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Plant, the mix and the one you cannot. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
Move, the haulier and the note. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Inspection, the tip and not hiding. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
The producer, the saving and not diluting. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
Where it should, not next door. Estimate No 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

IS WORK OVER?

31%

#33 / 633

Information specialist

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
Classify, index and describe holdings. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Thesauri, metadata and the internal search. Estimate No public source provides a precise figure. This is our estimate.	16%	52%	+8.3
Answer queries and retrieve what nobody can find. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Records policy, retention and destruction. Estimate No public source provides a precise figure. This is our estimate.	18%	22%	+4
Train people who file badly and people who do not file. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
The organisation’s memory, and not losing it. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		30%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low