AI exposure by occupation, O*NET 19-2032.00
Will AI replace Materials Scientists?
Materials Scientists: AI can already handle 5 of 16 tasks; the work mostly needs a frontier-tier model.
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Every task, scored
The 16 tasks O*NET 30.3 lists for Materials Scientists, from most to least exposed. 5 reach 60 or more, the level at which AI already handles a task.
| Task | AI exposure | Evidence | Model tier |
|---|---|---|---|
| Write research papers for publication in scientific journals. | Observed | Efficient | |
| Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers. | Estimated | Efficient | |
| Confer with customers to determine how to tailor materials to their needs. | Observed | Efficient | |
| Devise testing methods to evaluate the effects of various conditions on particular materials. | Estimated | Standard | |
| Recommend materials for reliable performance in various environments. | Estimated | Frontier | |
| 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. | Estimated | Standard | |
| Test material samples for tolerance under tension, compression, and shear to determine the cause of metal failures. | Estimated | Standard | |
| Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget. | Estimated | Standard | |
| 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. | Estimated | Frontier | |
| Test individual parts and products to ensure that manufacturer and governmental quality and safety standards are met. | Estimated | Standard | |
| Visit suppliers of materials or users of products to gather specific information. | Estimated | Efficient | |
| 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. | Estimated | Efficient | |
| 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. | Estimated | Frontier | |
| Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics. | Estimated | Frontier | |
| Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses. | Estimated | Efficient | |
| Teach in colleges and universities. | Estimated | Efficient |
Observed: scored from AI use recorded in the Anthropic Economic Index (June 2026 release), 2 of 16 tasks. Estimated: scored from the task's O*NET 30.3 work activity, 14 of 16. Importance is O*NET's 1 to 5 rating of how central the task is. Model tier is the lowest tier that can do the task under the published rubric; "No tier" marks hands-on work.
The model tier this role needs
A frontier-tier model or lower covers 100% of the role's importance-weighted task work. 100% of the work is something AI can address at some tier.
Efficient, standard and frontier tiers come from the JobRoute model tier reference. The recommended tier is the lowest one that covers 80% of the work AI can address. How the method works.
Wages, employment and outlook
- US employment
- 8,470
- Median annual wage
- $117,790
- Middle half of earners
- $89,990 to $150,550
- Projected change, 2024 to 2034
- +4.9%
Employment and wages: BLS Occupational Employment and Wage Statistics, May 2025, national. Projection: BLS Employment Projections 2024 to 2034.
Adjacent roles
The occupations that reuse the most of this role's skills, with the usual time to move. These are the first places to look when you plan to redeploy or retrain people in this role.
- Materials Engineers 79% skill overlap, about 7 months to move Exposure48
- Medical Scientists, Except Epidemiologists 66% skill overlap, about 12 months to move Exposure65
- Nanosystems Engineers 66% skill overlap, about 12 months to move Exposure57
- Chemists 65% skill overlap, about 12 months to move Exposure59
- Food Scientists and Technologists 64% skill overlap, about 13 months to move Exposure52
Skill overlap and transition time from the JobRoute role adjacency graph on O*NET 30.3 skills.
Questions about Materials Scientists and AI
Will AI replace Materials Scientists?
AI already handles 5 of the 16 tasks O*NET lists for this occupation, at a task exposure of 60 or more, and the role's importance-weighted exposure is 57 out of 100. JobRoute scores tasks, not whole jobs, so the score shows how much of the work changes rather than whether the job disappears. BLS projects employment to change by +4.9% from 2024 to 2034.
What is the AI exposure of Materials Scientists?
57 out of 100 on JobRoute's task exposure measure, the importance-weighted average of the role's O*NET task scores. Higher means more of the work is AI-doable today. 2 of the 16 task scores are observed in the Anthropic Economic Index (June 2026 release), and the other 14 are estimated from each task's O*NET work activity.
Which Materials Scientists tasks can AI already do?
The tasks with the highest exposure are: Write research papers for publication in scientific journals; Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers; Confer with customers to determine how to tailor materials to their needs. They are three of the 5 tasks that reach 60 or more.
What AI model tier does this role need?
A frontier-tier model or lower covers 100% of the role's importance-weighted task work. JobRoute assigns each task the lowest tier that can do it under a published rubric and recommends the lowest tier that covers 80% of the work AI can address.
How many people work as Materials Scientists, and what do they earn?
8,470 people in the United States, with a median annual wage of $117,790 (BLS Occupational Employment and Wage Statistics, May 2025). BLS Employment Projections expect a change of +4.9% from 2024 to 2034.
How to cite
Data version 2026-11-02, JobRoute method v1.0.0. Download all occupations or this occupation as JSON. Methodology.
JobRoute (2026). AI exposure: Materials Scientists. Data version 2026-11-02, method v1.0.0. Built on O*NET 30.3, BLS OEWS May 2025 and the Anthropic Economic Index (June 2026). CC BY 4.0. https://www.jobroute.ai/jobs/materials-scientists
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