AI Automation Index

Will AI Replace Materials Scientists?

Analyze the automation vulnerability, task-level AI risk, salary, and demand projection for Materials Scientists. Run the upskilling simulator.

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• Developed & audited by Gini Loh

AI Vulnerability

19% risk score

Median Salary

$117,790 / year

Growth Demand

Low

Constituent Task Mix

We parsed O*NET's 16 constituent tasks for this occupation and classified them by AI threat risk.

High Automation Risk (Routine Tasks) 0%
Medium Automation Risk (Cognitive/Technical) 38%
Low Automation Risk (Strategy/Leadership) 62%

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constituent Tasks

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.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

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.

Semi-structured task combining routine and non-routine responsibilities.

Test material samples for tolerance under tension, compression, and shear to determine the cause of metal failures.

Semi-structured task combining routine and non-routine responsibilities.

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.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Recommend materials for reliable performance in various environments.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

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.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Devise testing methods to evaluate the effects of various conditions on particular materials.

Semi-structured cognitive task involving analysis, inspection, or monitoring.

Test individual parts and products to ensure that manufacturer and governmental quality and safety standards are met.

Semi-structured task combining routine and non-routine responsibilities.

Confer with customers to determine how to tailor materials to their needs.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Visit suppliers of materials or users of products to gather specific information.

Semi-structured task combining routine and non-routine responsibilities.

Write research papers for publication in scientific journals.

Semi-structured task combining routine and non-routine responsibilities.

Teach in colleges and universities.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

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O*NET Methodology

O*NET Data Source

This page dynamically extracts data structures sponsored by the U.S. Department of Labor. Our AI classification applies cognitive task automation risk models to individual tasks.

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