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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 Computer Hardware Engineers: 18 O*NET tasks scored against their work activities, plus the simulator.
Automation Exposure
18 of 18 tasks scored
Median Salary
BLS OEWS, May 2025 — this exact occupation
Employment Level
76,660 people hold this job — size, not growth
Projected 2025–35
4,100 openings a year · BLS line item
BLS OEWS publishes 42 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$78,320 – $185,180
Highest medians
Lowest medians
State figures come from the 17-2061 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.
18 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
9 tasks
6 tasks
3 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 →Update knowledge and skills to keep up with rapid advancements in computer technology.
information retrieval — AI tracks technical updates; human validates depth
Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives.
decision support — AI drafts electronics; engineer validates and tests
Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system.
interpersonal — Conferring with technical staff on plans is relational work
Build, test, and modify product prototypes, using working models or theoretical models constructed with computer simulation.
data analysis — AI interprets results; human runs physical tests
Write detailed functional specifications that document the hardware development process and support hardware introduction.
text generation — Draft procedural documents from provided content
Test and verify hardware and support peripherals to ensure that they meet specifications and requirements, by recording and analyzing test data.
decision support — AI can plan/analyze tests; execution is physical
Direct technicians, engineering designers or other technical support personnel as needed.
interpersonal — Supervising engineers needs accountability and motivation
Provide technical support to designers, marketing and sales departments, suppliers, engineers and other team members throughout the product development and implementation process.
decision support — Proposes design changes; human validates feasibility
Select hardware and material, assuring compliance with specifications and product requirements.
decision support — Project material selection needs spec and site judgment
Store, retrieve, and manipulate data for analysis of system capabilities and requirements.
data analysis — Analyzes design requirements; human architects system
Analyze user needs and recommend appropriate hardware.
information retrieval — Product-use advice is largely informational with review
Evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration.
data analysis — Analyzes design requirements; human architects system
Provide training and support to system designers and users.
information retrieval — Product-use advice is largely informational with review
Monitor functioning of equipment and make necessary modifications to ensure system operates in conformance with specifications.
decision support — AI flags compliance deviations; human confirms in the world
Specify power supply requirements and configuration, drawing on system performance expectations and design specifications.
decision support — Operational criteria drafted; human decides
Assemble and modify existing pieces of equipment to meet special needs.
physical manipulation — Assembling components is physical hands-on work
Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications.
data analysis — Analyzes design requirements; human architects system
Recommend purchase of equipment to control dust, temperature, and humidity in area of system installation.
decision support — Proposes design changes; human validates feasibility
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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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