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AI Automation Index
Will AI Replace Nanotechnology Engineering Technologists and Technicians?
Task-level automation exposure for Nanotechnology Engineering Technologists and Technicians: 25 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
40%
weighted task index
25 of 25 tasks scored
Median Salary
$66,120 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
75,570 people hold this job — size, not growth
Projected 2025–35
+3.1%
employment change
6,600 openings a year · BLS line item
Pay by state
BLS OEWS publishes 46 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$46,470 – $79,330
Highest medians
Oklahoma $79,330
Maryland $79,090
California $79,070
Washington $78,430
Oregon $75,760
Lowest medians
Puerto Rico $46,470
Mississippi $50,180
South Dakota $54,570
West Virginia $57,240
Tennessee $58,070
State figures come from the 17-3026 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 40%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 33%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 7%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 20%
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 15/100
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
25 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) 24%
6 tasks
Medium exposure (≥ 35%) 30%
8 tasks
Low exposure (below 35%) 46%
11 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
#22047 · Core · 30% automatable
Produce images or measurements, using tools or techniques such as atomic force microscopy, scanning electron microscopy, optical microscopy, particle size analysis, or zeta potential analysis.
physical manipulation — Physical/chemical property testing by hand
Measure physical or chemical properties of materials or objects.
#22063 · Core · 75% automatable
Maintain accurate record or batch-record documentation of nanoproduction.
data analysis — Maintain records systems; human owns integrity
Maintain operational records or records systems.
#22053 · Core · 18% automatable
Calibrate nanotechnology equipment, such as weighing, testing, or production equipment.
physical manipulation — Physical calibration of instruments requires hands
Calibrate scientific or technical equipment.
#22046 · Core · 10% automatable
Maintain work area according to cleanroom or other processing standards.
physical manipulation — Physical cleaning of work areas
Maintain clean work areas.
#22049 · Core · 18% automatable
Repair nanotechnology processing or testing equipment or submit work orders for equipment repair.
physical manipulation — Physical calibration and upkeep of test equipment
Maintain test equipment.
#22068 · Core · 19% automatable
Assist nanoscientists or engineers in processing or characterizing materials according to physical or chemical properties.
physical manipulation — Physical/chemical property testing by hand
Measure physical or chemical properties of materials or objects. Operate precision equipment to control microscopic or nanoscopic processes.
#22048 · Core · 45% automatable
Collaborate with scientists or engineers to design or conduct experiments for the development of nanotechnology materials, components, devices, or systems.
information retrieval — Tech landscape synthesis aided; prototyping human
Research engineering applications of emerging technologies.
#22045 · Core · 8% automatable
Operate nanotechnology compounding, testing, processing, or production equipment in accordance with appropriate standard operating procedures, good manufacturing practices, hazardous material restrictions, or health and safety requirements.
physical manipulation — Microscopic precision control is fine manual dexterity
Operate precision equipment to control microscopic or nanoscopic processes.
#22054 · Core · 45% automatable
Monitor hazardous waste cleanup procedures to ensure proper application of nanocomposites or accomplishment of objectives.
data analysis — AI analyzes monitoring data; human samples in field
Monitor activities affecting environmental quality.
#22051 · Core · 55% automatable
Monitor equipment during operation to ensure adherence to specifications for characteristics such as pressure, temperature, or flow.
decision support — AI flags compliance deviations; human confirms in the world
Monitor processes for compliance with standards.
#22050 · Core · 10% automatable
Measure or mix chemicals or compounds in accordance with detailed instructions or formulas.
physical manipulation — Physical preparation of materials by hand
Prepare materials for processing.
#22056 · Core · 30% automatable
Inspect or measure thin films of carbon nanotubes, polymers, or inorganic coatings, using a variety of techniques or analytical tools.
physical manipulation — Physical/chemical property testing by hand
Measure physical or chemical properties of materials or objects.
#22065 · Core · 78% automatable
Prepare capability data, training materials, or other documentation for transfer of processes to production.
text generation — Draft procedural documents from provided content
Prepare procedural documents.
#22052 · Core · 45% automatable
Collect or compile nanotechnology research or engineering data.
information retrieval — Tech landscape synthesis aided; prototyping human
Research engineering applications of emerging technologies.
#22061 · Core · 78% automatable
Prepare detailed verbal or written presentations for scientists, engineers, project managers, or upper management.
text generation — Internal technical reports drafted; human reviews
Prepare technical reports for internal use.
#22055 · Core · 65% automatable
Contribute written material or data for grant or patent applications.
text generation — Draft disclosures; legal accountability human
Prepare contracts, disclosures, or applications.
#22060 · Core · 40% automatable
Implement new or enhanced methods or processes for the processing, testing, or manufacture of nanotechnology materials or products.
decision support — Process improvements need physical/organizational execution
Implement design or process improvements.
#22058 · Core · 60% automatable
Develop or modify wet chemical or industrial laboratory experimental techniques for nanoscale use.
decision support — Protocols drafted; scientific validity human-owned
Devise research or testing protocols.
#22069 · Core · 82% automatable
Assist nanoscientists or engineers in writing process specifications or documentation.
text generation — Draft technical design docs from provided details
Document technical design details.
#22067 · Supplemental · 55% automatable
Measure emission of nanodust or nanoparticles during nanocomposite or other nano-scale production processes, using systems such as aerosol detection systems.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
#22062 · Supplemental · 30% automatable
Perform functional tests of nano-enhanced assemblies, components, or systems, using equipment such as torque gauges or conductivity meters.
data analysis — AI interprets results; human runs physical tests
Test performance of electrical, electronic, mechanical, or integrated systems or equipment.
#22057 · Supplemental · 55% automatable
Compare the performance or environmental impact of nanomaterials by nanoparticle size, shape, or organization.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
#22059 · Supplemental · 8% automatable
Process nanoparticles or nanostructures, using technologies such as ultraviolet radiation, microwave energy, or catalysis.
physical manipulation — Microscopic precision control is fine manual dexterity
Operate precision equipment to control microscopic or nanoscopic processes.
#22064 · Supplemental · 5% automatable
Assemble components, using techniques such as interference fitting, solvent bonding, adhesive bonding, heat sealing, or ultrasonic welding.
physical manipulation — Assembling components is physical hands-on work
Assemble equipment or components.
#22066 · Supplemental · 55% automatable
Analyze the life cycle of nanomaterials or nano-enabled products to determine environmental impact.
data analysis — Impact assessment aided; site-specific data human
Investigate the environmental impact of projects.
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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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