Will materials scientists be replaced by AI?
Updated
Materials scientists score 48 of 100 for AI exposure. The largest share of their task time, 61%, is work AI speeds up while they stay in charge. AI can take over 7% outright, and 32% stays with people.
- 7% AI can do it
- 61% AI helps
- 32% Needs a person
Moderate exposure
Higher than 70% of the 923 occupations we scored.
Task by task
We graded 16 tasks, listed here from most to least exposed. AI can do 1 of them today, speeds up 10 and leaves 5 to people.
| Task | AI exposure |
|---|---|
| Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers. Drafting reports and manuals is highly automatable; author reviews output. | 72% AI can do it |
| Write research papers for publication in scientific journals. AI drafts much of the paper; data, claims, and accountability stay human. | 62% AI helps |
| Recommend materials for reliable performance in various environments. AI aids property database lookup and selection; engineer decides. | 50% AI helps |
| Determine ways to strengthen or combine materials or develop new materials with new or specific properties for use in a variety of products and applications. AI screens candidate compositions; experiments validate new material designs. | 45% AI helps |
| Conduct research on the structures and properties of materials, such as metals, alloys, polymers, and ceramics, to obtain information that could be used to develop new products or enhance existing ones. Literature and modeling speed up research; lab work stays human. | 40% AI helps |
| Perform experiments and computer modeling to study the nature, structure, and physical and chemical properties of metals and their alloys, and their responses to applied forces. Simulation and data analysis get AI help; physical experiments stay manual. | 40% AI helps |
| Devise testing methods to evaluate the effects of various conditions on particular materials. AI can draft test protocols; validating methods needs lab work. | 35% AI helps |
| Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics. AI helps design experiment plans; executing them is lab work. | 33% AI helps |
| Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses. Literature and process knowledge assist; firing and forming trials are physical. | 33% AI helps |
| Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget. Monitoring production floor and budgets needs on site presence. | 28% AI helps |
Show the other 6 tasks
| Task | AI exposure |
|---|---|
| Teach in colleges and universities. Lecture delivery is live; AI helps prep materials and grading. | 28% AI helps |
| Test individual parts and products to ensure that manufacturer and governmental quality and safety standards are met. Part testing and compliance checks are physical; paperwork can be automated. | 22% Needs a person |
| Test material samples for tolerance under tension, compression, and shear to determine the cause of metal failures. Physical load testing and fracture inspection stay hands on. | 20% Needs a person |
| Confer with customers to determine how to tailor materials to their needs. Customer conversations need live judgement; AI only preps briefs. | 20% Needs a person |
| Test metals to determine conformance to specifications of mechanical strength, strength-weight ratio, ductility, magnetic and electrical properties, and resistance to abrasion, corrosion, heat, and cold. Physical mechanical testing needs hands on equipment operation. | 18% Needs a person |
| Visit suppliers of materials or users of products to gather specific information. Site visits require physical presence and in person relationship building. | 8% Needs a person |
How materials scientists compare
All occupations (923)
Life, physical and social science (60)
Pay and outlook in the US
- Median pay
- $117,790 a year, May 2025
- People employed
- 8,470 in the US, May 2025
- Projected change in jobs
- +8.3% from 2024 to 2034
Skills to build
- Run tensile and fracture tests on lab equipment
- Build property models in Python and MATLAB
- Analyze experimental data in R and IBM SPSS Statistics
- Review AI-drafted technical reports in Microsoft Word
- Visit suppliers and product users on site
- Brief sponsors on material selection in Microsoft PowerPoint
Safer roles nearby
5 related occupations with lower scores.
Questions about materials scientists and AI
Will AI replace materials scientists?
Partly. About 3 in 10 working hours of a materials scientist go to tasks AI can already do, mostly drafting reports and manuals and writing research papers. Lab experiments, physical testing, and customer conversations stay with people because they need hands on equipment and live judgement.
Which materials science tasks is AI taking over?
Drafting reports, manuals, and proposals has the highest exposure at 72 out of 100, so AI produces first drafts for sponsors and customers while the author reviews the output. Research paper writing scores 62, since AI drafts much of the text while data and claims stay with the scientist. Screening candidate compositions also gets AI help.
Which materials science tasks stay human?
Visiting suppliers and product users scores 8, the lowest exposure, because site visits need physical presence and in person relationships. Testing metals for strength, ductility, and corrosion scores 18 and needs hands on equipment operation. Customer conversations on tailoring materials score 20 because live judgement stays with the scientist.
How can materials scientists stay valuable?
Run the physical tests yourself and use them to validate every AI-screened composition before it reaches a product. Build simulation models in Python and MATLAB, and check their outputs against measured data. Review each AI-drafted report in Microsoft Word against raw test results before it goes to a sponsor.
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