Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Materials Scientists:
47.2%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
There are a reasonable number of sources for this result, but there is some disagreement between them.
Contributing sources
AI Resilience Report forMaterials Scientists
$117,790 median salary•600 annual openings•SOC Code: 19-2032.00
Materials Scientists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 8 sources.
Materials science is labeled "Somewhat Resilient" because AI is genuinely changing how a big chunk of the work gets done, especially the research and analysis side, where tools can now run simulations, scan thousands of papers, and even suggest new ideas in days instead of months. That means the job is shifting: scientists who once spent most of their time on repetitive data crunching will need to focus more on guiding AI tools, asking the right questions, and making creative judgment calls that software cannot make on its own.
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Materials science is labeled "Somewhat Resilient" because AI is genuinely changing how a big chunk of the work gets done, especially the research and analysis side, where tools can now run simulations, scan thousands of papers, and even suggest new ideas in days instead of months. That means the job is shifting: scientists who once spent most of their time on repetitive data crunching will need to focus more on guiding AI tools, asking the right questions, and making creative judgment calls that software cannot make on its own.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Materials Scientists
Updated Quarterly
How is AI changing Materials Scientists jobs?
Right now, AI is mostly augmenting materials scientists — helping them work faster — rather than replacing them. At Argonne National Laboratory, researchers built a team of AI agents that automates atomistic simulations from start to finish, potentially reducing discovery time from months or years to just days, using collaborating specialist agents [1] that pick models, run simulations, and analyze results after a scientist types a plain-English prompt. For writing and reading papers, a team at IIT Delhi trained LLaMat, a materials-specific language model [2], which was evaluated across 42 tasks including natural-language understanding, structured information extraction, and crystal structure generation, and outperformed several widely used commercial LLMs like Claude, GPT and Gemini.
Researchers at Karlsruhe Institute of Technology are also using AI to scan mountains of journal articles for new research ideas [3], but the lead scientist stressed the findings aren't an invention machine — they're an analytic tool to identify new ideas and provide targeted support for scientific creativity. Physical lab visits, supervising production, and judgment calls about safety remain firmly human.
Sources
How fast is AI adoption growing for Materials Scientists?
Adoption is moving quickly on the research side because commercial tools are cheap while lab experiments are slow and expensive — Deloitte's 2026 manufacturing outlook [4] highlights AI and agentic systems as top competitive priorities, and the field's leading society, TMS, just hosted the 4th World Congress on AI in Materials and Manufacturing (AIM 2026) [5] to help members apply these tools. Adoption is slower for tasks that need hands-on lab work, supplier visits, or safety accountability. Encouragingly, the U.S. Bureau of Labor Statistics projects [6] that employment of chemists and materials scientists will grow 7% from 2025 to 2035 — much faster than average — suggesting AI is expanding, not shrinking, opportunities for curious young scientists.
Sources
Will AI replace Materials Scientists?
Not entirely. We think AI will take over some tasks, but not the whole job.
Materials science sits at a 47.2% AI Resilience Score, which tells you the field is genuinely changing. AI is already doing real work here. At Argonne National Laboratory, AI agents now automate atomistic simulations end to end, compressing what once took months into days [1]. Specialized models can scan thousands of journal articles to surface new research ideas, though researchers are clear these tools support scientific creativity rather than replace it [3]. Routine literature review, data extraction, and simulation setup are all moving toward AI assistance fast.
What stays human is the harder stuff: physical lab work, safety accountability, supplier relationships, and the judgment calls that come with turning a promising simulation into a real material. Those aren't going away. Adoption of AI tools is also uneven, moving quickly on the research side but slowly wherever hands-on work is required [4].
The job market picture is cautiously encouraging. The U.S. Bureau of Labor Statistics projects 7% employment growth for chemists and materials scientists through 2035, faster than average, which suggests AI is opening doors rather than closing them [6]. The scientists who learn to work alongside these tools will likely be the most valuable ones in the room.
Sources
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Latest AI news for Materials Scientists
These articles highlight the transformative impact of AI on materials science careers. For instance, the Materials Project is providing vast AI-ready datasets, enabling researchers to accelerate discoveries. Additionally, educational initiatives at institutions like the University of Wisconsin focus on integrating AI into curricula, preparing students for this evolving field. As companies like Radical AI establish advanced labs, new job opportunities will emerge, emphasizing the need for professionals skilled in both materials science and AI. Embracing these changes can enhance career resilience in a rapidly advancing industry.
DCSE Annual Conference 2026 | AI in Materials Science & Scientific Machine Learning
www.tudelft.nl • 2/6/2026
The DCSE Annual Conference 2026 brings together the TU Delft community and invited guests to explore the growing impact of artificial intelligence in...
Governor Hochul Celebrates Radical AI Establishing New York’s First Fully Autonomous Materials Science Labs At The Brooklyn Navy Yard
esd.ny.gov • 1/27/2026
Materials Science R&D Company Will Renovate New Headquarters and Build Advanced AI-Driven Labs. Project Will Create 115 New High-Paying Jobs...
10 Emerging AI Solutions for Material Science [2026]
www.startus-insights.com • 1/20/2026
Discover 10 top startups developing AI solutions for material science in 2026 & find out how their solutions will impact your business!
Accelerating Discovery: How the Materials Project Is Helping to Usher in the AI Revolution for Materials Science
newscenter.lbl.gov • 1/13/2026
The open-access materials database managed by Berkeley Lab has surpassed 650,000 registered users, enabling AI-ready scientific datasets at...
Leading the future of materials science education in the AI era
engineering.wisc.edu • 1/7/2026
Artificial intelligence opens enormous opportunities to transform materials science and materials-driven technologies, and the Department of...
More Career Info
Career: Materials Scientists
They study different materials to understand how they work and create new ones for products like phones, cars, and sports gear.
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Employment & Wage Data
Median Wage
$117,790
Jobs (2025)
8,600
Growth (2025-35)
+8.3%
Annual Openings
600
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Teach in colleges and universities.
2
Visit suppliers of materials or users of products to gather specific information.
3
Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics.
4
Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget.
5
Confer with customers to determine how to tailor materials to their needs.
6
Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses.
7
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 one...
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
