Will AI replace Materials Engineers?
AI can do 53% of the work Materials Engineers do at least twice as fast. Real use has not caught up: none of their tasks show up in real AI use yet, but AI could speed up 10 of them. 11 still need a person.
AI is already doing this0 · 0% of time
People already use AI for these tasks in real work, based on Anthropic's analysis of how Claude is used.
- Real AI use has not reached any of this job's tasks yet.
AI could do this next10 · 53% of time
AI can speed these up by at least half, but real use has not caught up yet. These are next in line.
- Analyze product failure data and laboratory test results to determine causes of problems and develop solutions.11% of time
- Design and direct the testing or control of processing procedures.10% of time
- Perform managerial functions, such as preparing proposals and budgets, analyzing labor costs, and writing reports.7% of time
- Supervise the work of technologists, technicians, and other engineers and scientists.6% of time
- Plan and implement laboratory operations to develop material and fabrication procedures that meet cost, product specification, and performance standards.6% of time
- Determine appropriate methods for fabricating and joining materials.5% of time
- Replicate the characteristics of materials and their components, using computers.4% of time
- Design processing plants and equipment.1% of time
- Write for technical magazines, journals, and trade association publications.1% of time
- Present technical information at conferences.1% of time
Still needs a person11 · 47% of time
No real AI use, no proven AI speedup and no robot that can do it yet. This is the part of the job to build on.
- Conduct or supervise tests on raw materials or finished products to ensure their quality.9% of time
- Evaluate technical specifications and economic factors relating to process or product design objectives.6% of time
- Plan and evaluate new projects, consulting with other engineers and corporate executives, as necessary.6% of time
- Review new product plans, and make recommendations for material selection, based on design objectives such as strength, weight, heat resistance, electrical conductivity, and cost.6% of time
- Guide technical staff in developing materials for specific uses in projected products or devices.5% of time
- Monitor material performance, and evaluate its deterioration.4% of time
- Solve problems in a number of engineering fields, such as mechanical, chemical, electrical, civil, nuclear, and aerospace.4% of time
- Supervise production and testing processes in industrial settings, such as metal refining facilities, smelting or foundry operations, or nonmetallic materials production operations.4% of time
- Modify properties of metal alloys, using thermal and mechanical treatments.2% of time
- Conduct training sessions on new material products, applications, or manufacturing methods for customers and their employees.1% of time
- Teach in colleges and universities.under 1% of time
Your week is not the average
Describe what you actually do and get a personal report: your own tasks, what AI can already do, what stays yours and a 90 day plan.
What this means
AI can do most of this work faster, but a real part of the job still needs a person. Real use is still behind at 0 out of 100, so the change here is only getting started. The people who learn which tasks to hand off will pull ahead.
What to do next
- Get ahead on the 10 tasks AI could do next. These move as tools improve, so learning them early pays off.
- Build on the 11 tasks that stay human. This is where your judgment, skill and relationships matter most.
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