Will AI replace computer hardware engineers?
Updated
Computer hardware engineers score 51 of 100 for AI exposure. The largest share of their task time, 79%, is work AI speeds up while they stay in charge. AI can take over 13% outright, and 8% stays with people.
- 13% AI can do it
- 79% AI helps
- 8% Needs a person
High exposure
Higher than 77% of the 923 occupations we scored.
Task by task
We graded 18 tasks, listed here from most to least exposed. AI can do 2 of them today, speeds up 14 and leaves 2 to people.
| Task | AI exposure |
|---|---|
| Write detailed functional specifications that document the hardware development process and support hardware introduction. LLMs draft detailed functional specs well; engineers review technical accuracy. | 65% AI can do it |
| Store, retrieve, and manipulate data for analysis of system capabilities and requirements. Data storage, retrieval and scripted analysis are highly automatable today. | 60% AI can do it |
| Specify power supply requirements and configuration, drawing on system performance expectations and design specifications. AI can calculate power budgets; engineers verify safety margins. | 50% AI helps |
| Select hardware and material, assuring compliance with specifications and product requirements. AI can compare datasheets to specs; engineers make final selections. | 45% AI helps |
| Analyze user needs and recommend appropriate hardware. AI can draft hardware recommendations from stated user requirements. | 45% AI helps |
| Evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration. AI can model cost options; security decisions need human review. | 45% AI helps |
| Provide technical support to designers, marketing and sales departments, suppliers, engineers and other team members throughout the product development and implementation process. AI drafts answers and docs; live support to teams stays human. | 40% AI helps |
| Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications. AI can propose layout options; on-site planning needs people. | 40% AI helps |
| Update knowledge and skills to keep up with rapid advancements in computer technology. AI speeds up literature summaries, but learning stays personal. | 35% AI helps |
| Test and verify hardware and support peripherals to ensure that they meet specifications and requirements, by recording and analyzing test data. Lab testing is physical; AI can analyze logged test data. | 35% AI helps |
Show the other 8 tasks
| Task | AI exposure |
|---|---|
| Provide training and support to system designers and users. AI drafts training materials; live instruction and support stay human. | 35% AI helps |
| Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives. AI assists chip design tools; engineers lead architecture decisions. | 30% AI helps |
| Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system. AI can summarize specs; live interface discussions stay with people. | 30% AI helps |
| Monitor functioning of equipment and make necessary modifications to ensure system operates in conformance with specifications. Routine monitoring can be scripted; physical fixes need technicians. | 30% AI helps |
| Recommend purchase of equipment to control dust, temperature, and humidity in area of system installation. Site assessment is physical; AI can help draft purchase recommendations. | 25% AI helps |
| Build, test, and modify product prototypes, using working models or theoretical models constructed with computer simulation. Physical prototyping stays manual; simulation setup gets AI help. | 20% AI helps |
| Direct technicians, engineering designers or other technical support personnel as needed. Directing and managing people is interpersonal and accountable work. | 15% Needs a person |
| Assemble and modify existing pieces of equipment to meet special needs. Physical assembly and rework of equipment requires skilled hands. | 10% Needs a person |
How computer hardware engineers compare
All occupations (923)
Architecture and engineering (56)
Pay and outlook in the US
- Median pay
- $161,740 a year, May 2025
- People employed
- 76,660 in the US, May 2025
- Projected change in jobs
- +9.1% from 2024 to 2034
Skills to build
- Review AI-drafted functional specifications for technical accuracy
- Verify power budgets and safety margins in SPICE
- Write hardware test scripts in Python and Perl
- Write and verify Verilog and SystemVerilog hardware designs
- Lead architecture decisions for CPUs and custom integrated circuits
- Hold a Professional Engineer (PE) license for signed designs
Safer roles nearby
5 related occupations with lower scores.
Questions about computer hardware engineers and AI
Will computer hardware engineers be replaced by AI?
Partly. About 4 in 10 working hours go to tasks AI can already do, mostly writing functional specifications and storing, retrieving, and analyzing data. Engineers still review technical accuracy, make final component selections, and decide the architecture.
Will AI take over computer engineering?
AI can already do 13% of the task time in computer engineering and speeds up another 79%. People still do 8% of it. The US has 76,660 computer hardware engineer jobs, with a projected change of +9.1% from 2024 to 2034.
Which tasks is AI taking over for computer hardware engineers?
Functional specifications and data handling come first. Writing detailed functional specs carries an exposure score of 65, and storing, retrieving, and scripting analysis of system requirements scores 60, so AI drafts specs well while engineers review technical accuracy. Power supply specifications follow at 50, since AI can calculate power budgets while engineers verify the safety margins.
Which tasks stay human for computer hardware engineers?
Physical assembly and rework of equipment stays human, because it needs skilled hands on real hardware. Directing technicians and design staff also stays with people, since it is interpersonal and accountable work. Physical prototyping remains manual, and AI only helps set up the simulations.
How can computer hardware engineers stay valuable as AI spreads?
Shift time toward bench work, architecture, and review of AI output. Check every AI-drafted spec and power budget in SPICE and MATLAB before release. Keep assembly and rework skills sharp on physical prototypes, and lead CPU and custom integrated circuit architecture decisions in Verilog and SystemVerilog projects.
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