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Do you agree with the AI automation risk score calculated for this occupation?
AI Automation Index
Task-level automation exposure for Photonics Technicians: 24 O*NET tasks scored against their work activities, plus the simulator.
Automation Exposure
24 of 24 tasks scored
Median Salary
BLS OEWS, May 2025 — this exact occupation
Employment Level
59,930 people hold this job — size, not growth
Projected 2025–35
5,400 openings a year · BLS line item
BLS OEWS publishes 51 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$43,640 – $107,060
Highest medians
Lowest medians
State figures come from the 17-3029 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
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.
Importance-weighted mean of the scored tasks. This is the headline index.
Share of weighted tasks in hands-on or machine-operating work activities.
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Share in documenting, recording, and administrative activities.
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
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.
24 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
6 tasks
3 tasks
15 tasks
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 →Compute or record photonic test data.
text generation — Document test results from provided data
Maintain clean working environments, according to clean room standards.
physical manipulation — Physical cleaning of work areas
Adjust or maintain equipment, such as lasers, laser systems, microscopes, oscilloscopes, pulse generators, power meters, beam analyzers, or energy measurement devices.
physical manipulation — Physical calibration of instruments requires hands
Document procedures, such as calibration of optical or fiber optic equipment.
text generation — Draft procedural documents from provided content
Set up or operate assembly or processing equipment, such as lasers, cameras, die bonders, wire bonders, dispensers, reflow ovens, soldering irons, die shears, wire pull testers, temperature or humidity chambers, or optical spectrum analyzers.
physical manipulation — Precision electronics assembly needs fine dexterity
Assist scientists or engineers in the conduct of photonic experiments.
decision support — AI assists analysis; hands-on research human
Test or perform failure analysis for optomechanical or optoelectrical products, according to test plans.
data analysis — Quantitative failure analysis; domain judgment needed
Assist engineers in the development of new products, fixtures, tools, or processes.
text generation — AI drafts technical methods; expert validates feasibility
Recommend optical or optic equipment design or material changes to reduce costs or processing times.
decision support — Proposes design changes; human validates feasibility
Set up or operate prototype or test apparatus, such as control consoles, collimators, recording equipment, or cables.
physical manipulation — Hands-on control of industrial machinery in unstructured settings
Monitor inventory levels and order supplies as necessary.
data analysis — Materials inventory records and forecasting automatable
Assemble fiber optical, optoelectronic, or free-space optics components, subcomponents, assemblies, or subassemblies.
physical manipulation — Precision electronics assembly needs fine dexterity
Optimize photonic process parameters by making prototype or production devices.
physical manipulation — Physical prototype fabrication is hands-on work
Splice fibers, using fusion splicing or other techniques.
physical manipulation — Instrumentation installation requires hands-on wiring
Build prototype optomechanical devices for use in equipment such as aerial cameras, gun sights, or telescopes.
physical manipulation — Physical prototype fabrication is hands-on work
Terminate, cure, polish, or test fiber cables with mechanical connectors.
data analysis — AI interprets results; human runs physical tests
Perform diagnostic analyses of processing steps, using analytical or metrological tools, such as microscopy, profilometry, or ellipsometry devices.
data analysis — Evaluates operations from data; human owns conclusions
Assemble or adjust parts or related electrical units of prototypes to prepare for testing.
physical manipulation — Precision electronics assembly needs fine dexterity
Repair or calibrate products, such as surgical lasers.
physical manipulation — Physical calibration of instruments requires hands
Design, build, or modify fixtures used to assemble parts.
decision support — AI drafts electronics; engineer validates and tests
Assemble components of energy-efficient optical communications systems involving photonic switches, optical backplanes, or optoelectronic interfaces.
physical manipulation — Precision electronics assembly needs fine dexterity
Lay out cutting lines for machining, using drafting tools.
text generation — Electronics schematics need expert verification and standards
Mix, pour, or use processing chemicals or gases according to safety standards or established operating procedures.
physical manipulation — Physical preparation of materials by hand
Fabricate devices, such as optoelectronic or semiconductor devices.
physical manipulation — Fabricating devices needs dexterous hands-on assembly
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<script src="https://giniloh.com/embed.js" async></script> Community Sentiment
Do you agree with the AI automation risk score calculated for this occupation?
Method
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
See the full method →Related Article
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