Gini Loh System Tools

AI Automation Index

Will AI Replace Aerospace Engineers?

Task-level automation exposure for Aerospace Engineers: 14 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified
Developed & audited by Gini Loh

Automation Exposure

51% weighted task index

14 of 14 tasks scored

Median Salary

$134,960 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

67,710 people hold this job — size, not growth

Projected 2025–35

+8.3% employment change

3,800 openings a year · BLS line item

Pay by state

BLS OEWS publishes 41 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$88,400 – $159,060

Highest medians

Minnesota $159,060
Washington $158,370
California $157,620
District of Columbia $157,600
Maryland $156,750

Lowest medians

Wisconsin $88,400
Idaho $95,700
Nevada $96,730
Alaska $101,710
Arkansas $102,040

State figures come from the 17-2011 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 51%

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

Physical work 0%

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

Judgment & influence 46%

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

Routine administration 16%

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 31/100 Moderate

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

14 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) 45%

6 tasks

Medium exposure (≥ 35%) 38%

6 tasks

Low exposure (below 35%) 17%

2 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 →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

  • New 05/2025 · AI/SME

    Develop and test autonomous systems for uncrewed aerospace vehicles.

Constituent Tasks

#20724 · Core · 45% automatable

Formulate conceptual design of aeronautical or aerospace products or systems to meet customer requirements or conform to environmental regulations.

decision support — AI drafts electromechanical designs; engineer verifies

Design electromechanical equipment or systems.
#20725 · Core · 60% automatable

Evaluate product data or design from inspections or reports for conformance to engineering principles, customer requirements, environmental regulations, or quality standards.

decision support — Design quality evaluation needs engineering judgment

Evaluate designs or specifications to ensure quality.
#1335 · Core · 35% automatable

Direct or coordinate activities of engineering or technical personnel involved in designing, fabricating, modifying, or testing of aircraft or aerospace products.

interpersonal — Directing design work needs accountability and judgment

Direct design or development activities.
#1337 · Core · 30% automatable

Plan or conduct experimental, environmental, operational, or stress tests on models or prototypes of aircraft or aerospace systems or equipment.

data analysis — AI interprets results; human runs physical tests

Test performance of electrical, electronic, mechanical, or integrated systems or equipment.
#20727 · Core · 30% automatable

Diagnose performance problems by reviewing reports or documentation from customers or field engineers or by inspecting malfunctioning or damaged products.

data analysis — Failure data analysis aided; physical inspection human

Investigate system, equipment, or product failures. Inspect equipment or systems.
#1339 · Core · 60% automatable

Formulate mathematical models or other methods of computer analysis to develop, evaluate, or modify design, according to customer engineering requirements.

data analysis — AI builds computational models; engineer validates assumptions

Create models of engineering designs or methods.
#1340 · Core · 78% automatable

Write technical reports or other documentation, such as handbooks or bulletins, for use by engineering staff, management, or customers.

text generation — Draft procedural documents from provided content

Prepare procedural documents.
#1346 · Core · 75% automatable

Maintain records of performance reports for future reference.

data analysis — Maintain records systems; human owns integrity

Maintain operational records or records systems.
#1341 · Core · 68% automatable

Analyze project requests, proposals, or engineering data to determine feasibility, productibility, cost, or production time of aerospace or aeronautical products.

data analysis — Analyzes design/requirements data; engineer owns judgment

Analyze design or requirements information for mechanical equipment or systems.
#1345 · Core · 35% automatable

Plan or coordinate investigation and resolution of customers' reports of technical problems with aircraft or aerospace vehicles.

interpersonal — Directing QC needs human oversight of physical processes

Direct quality control activities.
#20726 · Supplemental · 65% automatable

Develop design criteria for aeronautical or aerospace products or systems, including testing methods, production costs, quality standards, environmental standards, or completion dates.

decision support — Design criteria drafted; human owns decisions

Determine design criteria or specifications.
#20728 · Supplemental · 35% automatable

Direct aerospace research and development programs.

interpersonal — Directing design work needs accountability and judgment

Direct design or development activities.
#1344 · Supplemental · 51% automatable

Evaluate and approve selection of vendors by studying past performance or new advertisements.

data analysis — Gather performance info, human validates sources

Gather organizational performance information. Approve expenditures.
#19604 · Supplemental · 58% automatable

Research new materials to determine quality or conformance to environmental standards.

information retrieval — Regulation-to-compliance mapping; human verifies

Monitor operational procedures in technical environments to ensure conformance to standards. Evaluate plans or specifications to determine technological or environmental implications. Analyze environmental regulations to ensure organizational compliance.
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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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