Gini Loh System Tools

AI Automation Index

Will AI Replace Computer Hardware Engineers?

Task-level automation exposure for Computer Hardware Engineers: 18 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

56% weighted task index

18 of 18 tasks scored

Median Salary

$161,740 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

76,660 people hold this job — size, not growth

Projected 2025–35

+9.1% employment change

4,100 openings a year · BLS line item

Pay by state

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

California $185,180
Washington $169,120
Massachusetts $167,600
New Mexico $165,350
Texas $163,860

Lowest medians

Mississippi $78,320
Louisiana $83,550
Wisconsin $83,670
Puerto Rico $85,660
Oklahoma $95,600

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.

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 56%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 3%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 54%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 6%

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

18 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) 47%

9 tasks

Medium exposure (≥ 35%) 37%

6 tasks

Low exposure (below 35%) 16%

3 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

#7391 · Core · 80% automatable

Update knowledge and skills to keep up with rapid advancements in computer technology.

information retrieval — AI tracks technical updates; human validates depth

Update technical knowledge.
#7407 · Core · 50% automatable

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

Design electronic or computer equipment or instrumentation.
#7399 · Core · 55% automatable

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

Confer with technical personnel to prepare designs or operational plans.
#7396 · Core · 23% automatable

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

Test performance of electrical, electronic, mechanical, or integrated systems or equipment. Create physical models or prototypes.
#7402 · Core · 78% automatable

Write detailed functional specifications that document the hardware development process and support hardware introduction.

text generation — Draft procedural documents from provided content

Prepare procedural documents.
#7393 · Core · 35% automatable

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

Conduct validation tests of equipment or processes.
#7398 · Core · 30% automatable

Direct technicians, engineering designers or other technical support personnel as needed.

interpersonal — Supervising engineers needs accountability and motivation

Supervise engineering or other technical personnel.
#7392 · Core · 68% automatable

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

Recommend technical design or process changes to improve efficiency, quality, or performance.
#7400 · Core · 58% automatable

Select hardware and material, assuring compliance with specifications and product requirements.

decision support — Project material selection needs spec and site judgment

Select project materials.
#7401 · Core · 68% automatable

Store, retrieve, and manipulate data for analysis of system capabilities and requirements.

data analysis — Analyzes design requirements; human architects system

Analyze design requirements for computer or electronics systems.
#7397 · Core · 69% automatable

Analyze user needs and recommend appropriate hardware.

information retrieval — Product-use advice is largely informational with review

Analyze design requirements for computer or electronics systems. Advise customers on the use of products or services.
#7406 · Core · 68% automatable

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

Analyze design requirements for computer or electronics systems.
#7404 · Core · 58% automatable

Provide training and support to system designers and users.

information retrieval — Product-use advice is largely informational with review

Train personnel on proper operational procedures. Advise customers on the use of products or services. Provide technical guidance to other personnel.
#7394 · Core · 55% automatable

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

Monitor processes for compliance with standards.
#7403 · Core · 65% automatable

Specify power supply requirements and configuration, drawing on system performance expectations and design specifications.

decision support — Operational criteria drafted; human decides

Determine operational criteria or specifications.
#7405 · Supplemental · 5% automatable

Assemble and modify existing pieces of equipment to meet special needs.

physical manipulation — Assembling components is physical hands-on work

Assemble equipment or components.
#7395 · Supplemental · 68% automatable

Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications.

data analysis — Analyzes design requirements; human architects system

Analyze design requirements for computer or electronics systems.
#7408 · Supplemental · 68% automatable

Recommend purchase of equipment to control dust, temperature, and humidity in area of system installation.

decision support — Proposes design changes; human validates feasibility

Recommend technical design or process changes to improve efficiency, quality, or performance.
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Community Sentiment

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Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 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. 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. 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

See the full method →

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