Automation index

How much of a Mobile developer’s job can AI already do?

A layout and a store listing come earlier. It not crashing on a real phone do not.

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

Task comparison

IS WORK OVER?

28%

AI can already do 28% of this job.

#92 / 623

Mobile 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
Screens, API and offline state. Estimate No public source provides a precise figure. This is our estimate.	18%	52%	+9.4
Store review, crashlytics and ANRs. Estimate No public source provides a precise figure. This is our estimate.	16%	40%	+6.4
Real device, the notch and fragmented Android. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
CI, tests and the week's release. Estimate No public source provides a precise figure. This is our estimate.	16%	28%	+4.5
Product, the redesign and not breaking what people use. Estimate No public source provides a precise figure. This is our estimate.	18%	14%	+2.5
That it does not crash, and not ignoring the one-star. Estimate No public source provides a precise figure. This is our estimate.	16%	12%	+1.9
Total	100%		28%

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

IS WORK OVER?

25%

#230 / 623

Biomedical engineer

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
Design, validate and document clinical devices and software. Estimate No public source provides a precise figure. This is our estimate.	18%	48%	+8.6
Tests, MDR and risk. Estimate No public source provides a precise figure. This is our estimate.	16%	32%	+5.1
Hospital, clinicians and maintenance. Estimate No public source provides a precise figure. This is our estimate.	16%	22%	+3.5
Vendors, quality and traceability. Estimate No public source provides a precise figure. This is our estimate.	16%	18%	+2.9
User training and post-market watch. Estimate No public source provides a precise figure. This is our estimate.	18%	16%	+2.9
Not putting a half-built prototype in theatre. Estimate No public source provides a precise figure. This is our estimate.	16%	14%	+2.2
Total	100%		25%

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