Automation index

How much of a Museum educator’s job can AI already do?

A teaching sheet comes earlier. Thirty schoolchildren in front of the work, actually looking, do not.

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

Task comparison

IS WORK OVER?

24%

AI can already do 24% of this job.

#264 / 623

Museum educator

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
Sheets, routes and the teaching kit. Estimate No public source provides a precise figure. This is our estimate.	16%	44%	+7
The tour, the group that will not quiet, and the work. Estimate No public source provides a precise figure. This is our estimate.	18%	12%	+2.2
Workshops, families and Sunday at the museum. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
School, bookings and the missing mediator. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Access, the public who do not come in, and adapting. Estimate No public source provides a precise figure. This is our estimate.	18%	18%	+3.2
That they actually look, and not reciting the label. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		24%

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

IS WORK OVER?

26%

#198 / 623

Web developer

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
Layout, components and API consumption. Estimate No public source provides a precise figure. This is our estimate.	20%	48%	+9.6
Accessibility, performance and technical SEO. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Design, product and the client who changes their mind. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Deploys, incidents and monitoring. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
Tests, code review and documentation. Estimate No public source provides a precise figure. This is our estimate.	16%	16%	+2.6
Not shipping a half-change on a Friday. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		26%

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