Will materials engineers be replaced by AI?
Updated
Materials engineers score 40 of 100 for AI exposure. The largest share of their task time, 76%, is work AI speeds up while they stay in charge. AI can take over 4% outright, and 20% stays with people.
- 4% AI can do it
- 76% AI helps
- 20% Needs a person
Moderate exposure
Higher than 53% of the 923 occupations we scored.
Task by task
We graded 21 tasks, listed here from most to least exposed. AI can do 1 of them today, speeds up 16 and leaves 4 to people.
| Task | AI exposure |
|---|---|
| Write for technical magazines, journals, and trade association publications. AI drafts technical articles well; author reviews and edits. | 65% AI can do it |
| Perform managerial functions, such as preparing proposals and budgets, analyzing labor costs, and writing reports. AI drafts proposals, budgets and reports; inputs need human review. | 60% AI helps |
| Evaluate technical specifications and economic factors relating to process or product design objectives. AI can compare specs and cost trade-offs quickly; engineer decides. | 55% AI helps |
| Review new product plans, and make recommendations for material selection, based on design objectives such as strength, weight, heat resistance, electrical conductivity, and cost. AI can compare materials against design objectives; engineer selects. | 55% AI helps |
| Replicate the characteristics of materials and their components, using computers. Simulation software and AI speed up modelling; experts set it up. | 55% AI helps |
| Analyze product failure data and laboratory test results to determine causes of problems and develop solutions. AI can sift test data and suggest causes; engineer validates. | 50% AI helps |
| Solve problems in a number of engineering fields, such as mechanical, chemical, electrical, civil, nuclear, and aerospace. AI reasons across engineering fields; engineer applies and verifies. | 50% AI helps |
| Determine appropriate methods for fabricating and joining materials. AI can recommend fabrication and joining methods; execution is physical. | 40% AI helps |
| Design and direct the testing or control of processing procedures. AI can draft test plans; directing physical processing stays human. | 35% AI helps |
| Plan and evaluate new projects, consulting with other engineers and corporate executives, as necessary. AI drafts project plans; consulting executives needs human judgement. | 35% AI helps |
Show the other 11 tasks
| Task | AI exposure |
|---|---|
| Present technical information at conferences. AI helps build slides and abstracts; live presenting is human. | 35% AI helps |
| Design processing plants and equipment. CAD and AI assist layout; plant design needs expert engineering judgement. | 35% AI helps |
| Teach in colleges and universities. AI prepares course content; live teaching and mentoring stay human. | 35% AI helps |
| Monitor material performance, and evaluate its deterioration. Sensor monitoring is physical; AI helps interpret degradation data. | 30% AI helps |
| Guide technical staff in developing materials for specific uses in projected products or devices. AI supports technical guidance docs; leading staff stays human. | 30% AI helps |
| Plan and implement laboratory operations to develop material and fabrication procedures that meet cost, product specification, and performance standards. AI can help plan lab procedures; hands-on operations remain physical. | 30% AI helps |
| Conduct training sessions on new material products, applications, or manufacturing methods for customers and their employees. AI can draft training materials; delivering sessions is in-person. | 25% AI helps |
| Conduct or supervise tests on raw materials or finished products to ensure their quality. Hands-on lab testing; AI only helps with data reporting. | 18% Needs a person |
| Supervise the work of technologists, technicians, and other engineers and scientists. Supervising people requires live judgement and accountability. | 15% Needs a person |
| Modify properties of metal alloys, using thermal and mechanical treatments. Heat and mechanical treatment is physical furnace and press work. | 12% Needs a person |
| Supervise production and testing processes in industrial settings, such as metal refining facilities, smelting or foundry operations, or nonmetallic materials production operations. On-site supervision of smelting and foundry operations is physical. | 12% Needs a person |
How materials engineers compare
All occupations (923)
Architecture and engineering (56)
Pay and outlook in the US
- Median pay
- $112,860 a year, May 2025
- People employed
- 22,770 in the US, May 2025
- Projected change in jobs
- +7.5% from 2024 to 2034
Skills to build
- Select materials in Excel against strength, weight, heat resistance and cost
- Run failure analysis in MATLAB or Python on lab data
- Hold hands-on lab testing on raw materials and finished parts
- Run heat and mechanical treatment of metal alloys at the furnace
- Review AI-drafted reports and proposals in Microsoft Word before sign-off
Safer roles nearby
2 related occupations with lower scores.
Questions about materials engineers and AI
Will AI replace materials engineers?
Partly. About 4 in 10 working hours for materials engineers go to tasks AI can already do, mostly drafting technical articles and writing proposals, budgets and reports. Hands-on lab testing, furnace work and supervising people stay with the engineer.
Which materials engineering tasks is AI taking over?
AI is taking over journal and trade article drafting first, with an exposure score of 65, because it writes a usable first draft and the engineer only reviews and edits it. Proposals, budgets and reports come next at exposure 60, since AI assembles the numbers and text while the engineer checks every input.
Which materials engineering tasks stay human?
Heat and mechanical treatment of metal alloys stays human because it is furnace and press work done at the machine. Supervising smelting and foundry operations on site is physical presence work, and lab testing of raw materials and finished products is hands-on, with AI only helping to report the data afterward.
How can materials engineers stay valuable?
Keep the material selection call and the hands-on work, and let AI handle the drafting. Sign off material choices in Excel against strength, weight, heat resistance and cost. Check every AI-suggested failure cause in MATLAB or Python against your lab results, and spend time in the test lab and on the furnace floor.
Related jobs
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