Materials Scientists

Most exposed tasks

No task is classified fully automatable in this release. The highest-exposure task relative to this role is shown in the free snapshot above; the assistive work is detailed next.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

• Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.60
• Write research papers for publication in scientific journals.55
• 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.50

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

• Visit suppliers of materials or users of products to gather specific information.20
• Teach in colleges and universities.20
• Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget.25

Task exposure values and classifications are published, versioned estimates audited against the anchored rubric. This page reads them from the data release rather than generating them at request time. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 38 puts Materials Scientists in the third quartile of analyzed occupations. In practice, exposure this high is about the mix: 0 of 16 analyzed tasks lean automatable, 9 augmentable, and 7 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

• $117,790median wage
• 8,470employed
• 600annual openings
• +4.6%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Related roles

Adjacent by skills or family — no exposure claim implied.

• Materials Engineers 40
• Nanosystems Engineers 38
• Microsystems Engineers 43
• Chemical Engineers 40
• Mechanical Engineer 42
• Chemists 36

How this score was calculated

FAQ — Materials Scientists

Will AI replace Materials Scientists?

This score cannot predict whether this occupation or any individual job will be replaced. It shows which tasks current and near-term AI can perform or accelerate, which tasks remain more durable, and where a worker can adapt. Employer decisions, demand, regulation, and how the role changes are outside the score.

What does a score of 38 mean for a Materials Scientists?

It means that, weighted across the 16 tasks we analyzed for this role, the task mix sits at 38 on a 0–100 exposure scale — in the third quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.

Which tasks in this role are most exposed to AI?

This role has no strongly automatable task in the current data release.

Which parts of this job are most durable?

The most durable responsibilities are: Visit suppliers of materials or users of products to gather specific information; Teach in colleges and universities; Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.

Is this score personalized to me?

No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.