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needsahuman.

Will AI replace materials engineers?

A little.

This job scores 73 out of 100 on (higher is safer). Today people do 51% of the work with AI’s help, and 49% still needs a person.

Updated 3 October 2026 17-2131 2129 2026-Q4
Architecture and EngineeringMaterials Engineers17-2131 · 2026-Q4
0% AI does it51% AI helps49% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 49%AI helps 51%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Each ridge is a slice of the job's task time.Needs a human 49%AI helps 51%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Materials Engineers, O*NET-SOC 17-2131. 49% of the job’s task time still needs a human, so 49 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 49% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 49%AI helps 51%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 49%AI helps 51%AI does it 0%
Conduct or supervise tests on raw materials or finished products to ensure their quality.Needs a human
Review new product plans, and make recommendations for material selection, based on design objectives such as strength, weight, heat resistance, electrical conductivity, and cost.AI helps
Evaluate technical specifications and economic factors relating to process or product design objectives.AI helps
Solve problems in a number of engineering fields, such as mechanical, chemical, electrical, civil, nuclear, and aerospace.AI helps
Plan and implement laboratory operations to develop material and fabrication procedures that meet cost, product specification, and performance standards.Needs a human
Analyze product failure data and laboratory test results to determine causes of problems and develop solutions.AI helps
Determine appropriate methods for fabricating and joining materials.AI helps
Guide technical staff in developing materials for specific uses in projected products or devices.Needs a human
Design and direct the testing or control of processing procedures.AI helps
Plan and evaluate new projects, consulting with other engineers and corporate executives, as necessary.Needs a human
Supervise the work of technologists, technicians, and other engineers and scientists.Needs a human
Supervise production and testing processes in industrial settings, such as metal refining facilities, smelting or foundry operations, or nonmetallic materials production operations.Needs a human
Perform managerial functions, such as preparing proposals and budgets, analyzing labor costs, and writing reports.AI helps
Monitor material performance, and evaluate its deterioration.Needs a human
Replicate the characteristics of materials and their components, using computers.AI helps
Conduct training sessions on new material products, applications, or manufacturing methods for customers and their employees.Needs a human
Modify properties of metal alloys, using thermal and mechanical treatments.Needs a human
Teach in colleges and universities.Needs a human
Design processing plants and equipment.AI helps
Present technical information at conferences.AI helps
Write for technical magazines, journals, and trade association publications.AI helps

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: 2037–2051

Most likely between 2037 and 2051 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
A little.
By 2045
80%
of our scenarios have AI largely doing this job by 2045 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)
By 2060
100%
of our scenarios have AI largely doing this job by 2060 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could do a little of this job (A little.)100%Today2030: 70.0% of scenarios: AI could do a little of this job (A little.)70%2030: 30.0% of scenarios: AI could partly do this job (Partly.)30%20302035: 40.0% of scenarios: AI could partly do this job (Partly.)40%2035: 50.0% of scenarios: AI could mostly do this job (Mostly.)50%2035: 10.0% of scenarios: AI could largely do this job (Largely.)10%20352040: 10.0% of scenarios: AI could partly do this job (Partly.)10%2040: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2040: 60.0% of scenarios: AI could largely do this job (Largely.)60%20402045: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2045: 80.0% of scenarios: AI could largely do this job (Largely.)80%20452050: 100.0% of scenarios: AI could largely do this job (Largely.)100%20502055: 100.0% of scenarios: AI could largely do this job (Largely.)100%20552060: 100.0% of scenarios: AI could largely do this job (Largely.)100%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%100.0%0.0%
20300.0%0.0%30.0%70.0%0.0%
203510.0%50.0%40.0%0.0%0.0%
204060.0%30.0%10.0%0.0%0.0%
204580.0%20.0%0.0%0.0%0.0%
2050100.0%0.0%0.0%0.0%0.0%
2055100.0%0.0%0.0%0.0%0.0%
2060100.0%0.0%0.0%0.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.1 out of 5 for consequence and decisions 3.6 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 4.8 and physical closeness 3.0 out of 5; caring for or serving people is 1.9 out of 5 in importance.
RegulationWorkers rate responsibility for others' health and safety 3.8 out of 5.
LicensingUsual entry requirement (BLS): bachelor's degree.
Physical work0% of the task time is physical.

What would it cost to hand the work to AI?

The share of the year AI could handle (537 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$50–$5,370
A person’s wage for the same hours
$18,650–$45,340

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

0%
of the task time is physical work
None needed
the kind of robot the physical work would need
Little of this job is physical, so robotics is not what holds AI back.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 49%AI helps 51%AI does it 0%
Writing · 6.6% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 37% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 4.5% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 4.4% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 15.9% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 16.3% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 15.3% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 49%AI helps 51%AI does it 0%
How exposed is it?

Still needs a human: 73/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 49% needs a human, 51% AI helps, 0% AI does it. Still needs a human: 73/100 ↑ safer. Will AI replace them? A little.

People are asking

How often people ask whether AI will replace this job: on Google, and by estimate, in AI assistants.

In the US

Under 10
Google searches a month, 12-month average to
1
estimated questions to AI assistants in September 2026
Estimated questions to AI assistants a month, October 2025 to September 2026: from 0 to 1

Source: DataForSEO, US and UK, fetched October 3, 2026. Google figures are Google Ads’ rounded monthly averages. The AI figure is DataForSEO’s estimate from Google’s “People also ask” data, not a count from any AI assistant. UK workers are ONS employment figures matched to this job, so the UK rate per 1,000 is an estimate. Search figures are not part of our open dataset.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 73/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

AI will automate some design, simulation, and data-analysis tasks, but human materials engineers will still be needed for judgment, experimentation, validation, manufacturing constraints, and safety-critical decisions.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudeNo

AI will significantly augment materials discovery and simulation, but replacing materials engineers requires physical testing, judgment, and contextual expertise that AI lacks.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI will automate routine data analysis, property prediction, and materials screening, it will augment rather than fully replace materials engineers, who are still needed for physical synthesis, hands-on testing, and complex decision-making.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate routine materials-engineering tasks, but human judgment, physical testing, manufacturing integration, and accountability will likely remain essential.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Materials Engineers? A little. Still needs a human: 73/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/materials-engineers/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

Put the badge on your site

The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.