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AI Automation Index
Will AI Replace Semiconductor Processing Technicians?
Task-level automation exposure for Semiconductor Processing Technicians: 17 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
28%
weighted task index
17 of 17 tasks scored
Median Salary
$51,430 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
31,460 people hold this job — size, not growth
Projected 2025–35
+8.2%
employment change
3,400 openings a year · BLS line item
Pay by state
BLS OEWS publishes 20 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$37,290 – $78,940
Highest medians
Arizona $78,940
Oregon $63,330
Florida $62,330
Washington $58,710
Minnesota $57,780
Lowest medians
Nevada $37,290
Texas $38,440
Arkansas $40,610
Utah $40,760
Pennsylvania $46,430
State figures come from the 51-9141 row in the May 2025 state panel. 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 28%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 51%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 15%
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 13/100
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
17 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) 19%
3 tasks
Medium exposure (≥ 35%) 14%
2 tasks
Low exposure (below 35%) 67%
12 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
#12575 · Core · 28% automatable
Inspect materials, components, or products for surface defects and measure circuitry, using electronic test equipment, precision measuring instruments, microscope, and standard procedures.
physical manipulation — Hands-on dimensional measurement of workpieces
Measure dimensions of completed products or workpieces to verify conformance to specifications.
#12577 · Core · 73% automatable
Study work orders, instructions, formulas, and processing charts to determine specifications and sequence of operations.
information retrieval — Parse specs and materials from orders
Read work orders or other instructions to determine product specifications or materials requirements. Review blueprints or other instructions to determine operational methods or sequences.
#12576 · Core · 9% automatable
Clean semiconductor wafers using cleaning equipment, such as chemical baths, automatic wafer cleaners, or blow-off wands.
physical manipulation — Hands-on cleaning of physical workpieces
Clean workpieces or finished products.
#12574 · Core · 82% automatable
Maintain processing, production, and inspection information and reports.
data analysis — Record production data into structured logs
Record operational or production data.
#12580 · Core · 4% automatable
Place semiconductor wafers in processing containers or equipment holders, using vacuum wand or tweezers.
physical manipulation — Mounting workpieces is physical loading
Assemble precision electronics or optical equipment. Mount materials or workpieces onto production equipment.
#12578 · Core · 6% automatable
Load and unload equipment chambers and transport finished product to storage or to area for further processing.
physical manipulation — Physical moving of products between work areas
Load materials into production equipment. Move products, materials, or equipment between work areas.
#12573 · Core · 55% automatable
Manipulate valves, switches, and buttons, or key commands into control panels to start semiconductor processing cycles.
physical manipulation — Command entry often needs physical equipment interface
Enter commands, instructions, or specifications into equipment.
#12587 · Core · 42% automatable
Inspect equipment for leaks, diagnose malfunctions, and request repairs.
text generation — Notifying maintenance needs is routine messaging
Inspect production equipment. Diagnose equipment malfunctions. Notify others of equipment repair or maintenance needs.
#12589 · Supplemental · 12% automatable
Stamp, etch, or scribe identifying information on finished component according to specifications.
physical manipulation — Engraving requires controlled hand tool operation
Engrave designs, text, or other markings onto materials, workpieces, or products.
#12579 · Supplemental · 10% automatable
Clean and maintain equipment, including replacing etching and rinsing solutions and cleaning bath containers and work area.
physical manipulation — Physical production equipment maintenance
Clean workpieces or finished products. Maintain production or processing equipment.
#12584 · Supplemental · 25% automatable
Monitor operation and adjust controls of processing machines and equipment to produce compositions with specific electronic properties, using computer terminals.
visual inspection — Physical product flaw monitoring is on-machine
Monitor equipment operation to ensure that products are not flawed.
#12583 · Supplemental · 3% automatable
Load semiconductor material into furnace.
physical manipulation — Manual loading into hot ovens or furnaces
Load items into ovens or furnaces.
#12585 · Supplemental · 21% automatable
Count, sort, and weigh processed items.
visual inspection — Counting physical products needs presence or sensors
Count finished products or workpieces. Weigh finished products. Sort materials or products for processing, storing, shipping, or grading.
#12591 · Supplemental · 8% automatable
Scribe or separate wafers into dice.
physical manipulation — Hands-on industrial material cutting
Cut industrial materials in preparation for fabrication or processing.
#12586 · Supplemental · 65% automatable
Calculate etching time based on thickness of material to be removed from wafers or crystals.
data analysis — Production requirement calc; human validates inputs
Calculate specific material, equipment, or labor requirements for production.
#12582 · Supplemental · 3% automatable
Etch, lap, polish, or grind wafers or ingots to form circuitry and change conductive properties, using etching, lapping, polishing, or grinding equipment.
physical manipulation — Precision electronics assembly needs fine dexterity
Assemble precision electronics or optical equipment.
#12588 · Supplemental · 3% automatable
Align photo mask pattern on photoresist layer, expose pattern to ultraviolet light, and develop pattern, using specialized equipment.
physical manipulation — Precision electronics assembly needs fine dexterity
Assemble precision electronics or optical equipment.
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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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