GistGarden

Will AI replace Aerospace Engineers?

Work in Aerospace Engineers sits in the in-between: AI reaches some of it (~57% in theory) but is only measured doing about 8% today — part human, part machine.

The Hybrid Zone Part human, part AI — already a blend.

O*NET-SOC 17-2011

How your 10 core tasks split

90% within AI's reach
3 AI can do this now
6 AI speeds this up
1 Still on you
AI could do · GPT-4 study
57%
49-pt gap
AI actually does · 2026 report
8%

Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.

⚡ The short answer

Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~57%). By late 2025, real-world AI use had reached about 8% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.

Where this job sits among 738 jobs

Being automatedTicking (can, but unused)Relatively safeQuietly happeningYOU0%50%100%0%40%75% → How much AI could do (theory) → How much AI is actually used (late 2025)

Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.

Mixedconfidence

Read this as a range, not a verdict

The signals here partly disagree — AI's theoretical reach (~57%) and its real-world use (~8%) tell different stories. AI-risk scores also shift a lot by which model does the rating (2.7%–51.5% in one 2026 study), so this is a direction of travel, not a fixed answer.

See all 10 tasks, ratedBased on real task-level AI scores — click to collapse
AI can already do this3 of 10
  • Formulate mathematical models or other methods of computer analysis to develop, evaluate, or modify design, according to customer engineering requirements.
  • Write technical reports or other documentation, such as handbooks or bulletins, for use by engineering staff, management, or customers.
  • Maintain records of performance reports for future reference.
AI speeds this up6 of 10
  • Formulate conceptual design of aeronautical or aerospace products or systems to meet customer requirements or conform to environmental regulations.
  • Plan or coordinate investigation and resolution of customers' reports of technical problems with aircraft or aerospace vehicles.
  • Direct or coordinate activities of engineering or technical personnel involved in designing, fabricating, modifying, or testing of aircraft or aerospace products.
  • Evaluate product data or design from inspections or reports for conformance to engineering principles, customer requirements, environmental regulations, or quality standards.
  • Develop design criteria for aeronautical or aerospace products or systems, including testing methods, production costs, quality standards, environmental standards, or completion dates.
  • Analyze project requests, proposals, or engineering data to determine feasibility, productibility, cost, or production time of aerospace or aeronautical products.
Still on you1 of 10
  • Plan or conduct experimental, environmental, operational, or stress tests on models or prototypes of aircraft or aerospace systems or equipment.

My job is in The Hybrid Zone 🤝

Half me, half machine. Honestly? Not mad about it.

Theoretical estimate · not a prediction · gistgarden.com

How we measured this — and how fresh it is

AI's theoretical reach data: 2023

From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.

Real-world AI use 2026 report

From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).

Task list & ratings O*NET 30.3

Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.

Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.

This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.