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AI Automation Index
Will AI Replace Team Assemblers?
Task-level automation exposure for Team Assemblers: 11 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
34%
weighted task index
11 of 11 tasks scored
Median Salary
$44,650 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Very High
1,405,030 people hold this job — size, not growth
Projected 2025–35
+1.1%
employment change
138,700 openings a year · BLS roll-up 51-2090
Pay by state
BLS OEWS publishes 52 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$24,610 – $50,330
Highest medians
District of Columbia $50,330
Hawaii $49,630
Alaska $49,390
Nevada $49,050
Iowa $48,920
Lowest medians
Puerto Rico $24,610
Arkansas $36,990
New Jersey $37,620
Georgia $38,310
Texas $38,320
OEWS has no state row for this exact code, so figures come from the 51-2090 roll-up. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 34%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 48%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 33%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 7%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 7/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
11 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 30%
3 tasks
Medium exposure (≥ 35%) 13%
1 tasks
Low exposure (below 35%) 58%
7 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#20157 · Core · 45% automatable
Perform quality checks on products and parts.
visual inspection — Material quality often needs hands-on or visual inspection
Evaluate quality of materials or products.
#20160 · Core · 80% automatable
Review work orders and blueprints to ensure work is performed according to specifications.
information retrieval — Parse specs and materials from orders
Read work orders or other instructions to determine product specifications or materials requirements.
#8468 · Core · 5% automatable
Rotate through all the tasks required in a particular production process.
physical manipulation — Physical assembly of products by hand
Assemble products or production equipment.
#8469 · Core · 60% automatable
Determine work assignments and procedures.
decision support — Sequence planning aided; production constraints human-verified
Plan production or operational procedures or sequences.
#20163 · Core · 33% automatable
Supervise assemblers and train employees on job procedures.
interpersonal — Equipment instruction requires live demonstration and correction
Instruct workers to use equipment or perform technical procedures. Direct operational or production activities.
#20159 · Core · 5% automatable
Shovel, sweep, or otherwise clean work areas.
physical manipulation — Hands-on cleaning of work areas
Clean work areas.
#8472 · Supplemental · 4% automatable
Provide assistance in the production of wiring assemblies.
physical manipulation — Fine dexterity assembling electronics
Assemble electrical or electronic equipment.
#20162 · Supplemental · 10% automatable
Maintain production equipment and machinery.
physical manipulation — Physical production equipment maintenance
Maintain production or processing equipment.
#20161 · Supplemental · 82% automatable
Complete production reports to communicate team production level to management.
data analysis — Record production data into structured logs
Record operational or production data.
#20158 · Supplemental · 10% automatable
Package finished products and prepare them for shipment.
physical manipulation — Physically packaging products for shipment
Package products for storage or shipment.
#20164 · Supplemental · 10% automatable
Operate machinery and heavy equipment, such as forklifts.
situated mobility — Driving forklifts requires real-world navigation and control
Operate forklifts or other loaders.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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