Medium AI Risk Average

Materials scientists

SOC Code: 19-2032

Materials scientists carries a 32% AI exposure score (Medium automation risk), with a median annual wage of $104,160 and +4.9% projected employment growth from 2024 to 2034 (BLS), affecting approximately 8,700 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
32% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+4.9%
2024–2034 (BLS)
+400 jobs
Median Annual Wage
$104,160
BLS May 2024
How wage figures are sourced →
The verdict

At 32% AI exposure, Materials scientists sits 5 points below the 37.2% average across 832 U.S. occupations - more exposed than 37% of them. Most of its core tasks still require human judgment.

32%
AI exposure
37th
percentile
+4.9%
Job growth 2024–34
$104,160
Median wage

Where Materials scientists sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

AI exposure distribution - Materials scientists marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 63% by AI exposure Higher AI exposure than 37% of all 832 occupations.

Materials scientists has ai exposure of 32%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.

Materials scientists vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Materials scientists is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk21.8%34.1%46.5%58.9%71.3%0%3.3%6.6%9.8%13.1%AI exposure (%) →Projected growth (%) →Materials scientistsMedical scientistsOccupational healthEnvironmental scientChemistsLifeBiological techniciaClinicalSchool psychologistsBiological scientistChemical techniciansPsychologists

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

8,700
Employment 2024
9,100
Projected 2034
+4.9%
Change (%)
+400
Change (jobs)

Occupation Insight

Materials scientists (SOC 19-2032) carries an AI exposure score of 32%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.

The economic context matters alongside the risk score. BLS counted approximately 8,700 workers in this occupation in 2024, and projects a +4.9% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $104,160, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Bachelor's degree, plus None of related experience.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Materials scientists. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
Bachelor's degree
Work Experience
None
On-the-Job Training
None

Top Tasks (O*NET)

  1. 1. 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.
  2. 2. 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.
  3. 3. Test material samples for tolerance under tension, compression, and shear to determine the cause of metal failures.
  4. 4. 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.
  5. 5. Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.
  6. 6. Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics.
  7. 7. Recommend materials for reliable performance in various environments.
  8. 8. Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget.
  9. 9. Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses.
  10. 10. 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.

Key Skills Required

  • Reading Comprehension
  • Active Listening
  • Science
  • Critical Thinking
  • Complex Problem Solving
  • Writing
  • Speaking
  • Active Learning
  • Judgment and Decision Making
  • Mathematics

Knowledge Areas

  • Engineering and Technology
  • Chemistry
  • Physics
  • Mathematics
  • Computers and Electronics
  • Production and Processing
  • Design
  • Mechanical
  • English Language
  • Education and Training

Frequently Asked Questions

Will AI replace Materials scientists?

Materials scientists has an AI exposure score of 32%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.

What is the job outlook for Materials scientists?

According to BLS Employment Projections 2024-2034, Materials scientists is projected to grow by 4.9% over the decade. Current employment stands at approximately 8,700 workers.

What skills are needed for Materials scientists?

Key skills for Materials scientists include Reading Comprehension, Active Listening, Science, and others. Typical entry-level education is Bachelor's degree.

How much do Materials scientists earn?

The median annual wage for Materials scientists is $104,160, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Materials scientists?

The typical entry-level education for Materials scientists is Bachelor's degree. Employers generally expect None of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.

Which companies employ Materials scientists?

Materials scientists roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

1.6
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.