Will AI replace computer hardware engineers?

Unlikely, though parts of the work are changing. About 1h 7m of an 8-hour shift goes to tasks touched by AI working on its own. The other 6h 53m (86%) stays with people. Separately, BLS expects about 9.1% more of these jobs by 2035 (all jobs: +3.5%).

AI shows up regularly in 4 of 18 tasks, about 1h 7m of a typical shift. The biggest ones:

• Write detailed functional specifications that document the hardware development process and support hardware introduction. (36m a shift, AI mostly does it alone)
• Store, retrieve, and manipulate data for analysis of system capabilities and requirements. (12m a shift, AI mostly does it alone)
• Analyze user needs and recommend appropriate hardware. (12m a shift, AI mostly does it alone)
• Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications. (6m a shift, AI mostly does it alone)

Not in workplaces like this one, based on a 2026 review of robot deployments. 3 more tasks have only been done in factory setups built around the machine, so they stay with people here. For 1 physical task, no robot has shown it can do the work yet.

6h 53m of a typical shift, or 86%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives. (1h 37m a shift)
• Build, test, and modify product prototypes, using working models or theoretical models constructed with computer simulation. (1h 1m a shift)
• Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system. (55m a shift)
• Test and verify hardware and support peripherals to ensure that they meet specifications and requirements, by recording and analyzing test data. (55m a shift)
• Provide technical support to designers, marketing and sales departments, suppliers, engineers and other team members throughout the product development and implementation process. (30m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 50% talk face to face with others every day

For the 3 tasks in this job where AI shows up and timing data exists, a typical request takes about 5h 4m for a person alone and about 39m with AI. These are Claude's own estimates from real conversations in April and May 2026 (Anthropic Economic Index). They describe single requests, not whole workdays, and time saved on a task doesn't mean jobs are cut. The biggest gaps:

• Store, retrieve, and manipulate data for analysis of system capabilities and requirements (about 7h 17m alone, 40m with AI)
• Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications (about 5h 4m alone, 37m with AI)
• Analyze user needs and recommend appropriate hardware (about 2h 47m alone, 39m with AI)

On Indeed, job postings in the Mechanical Engineering sector are at 168% of their February 2020 level (all U.S. postings: 104%), up 43.4% from a year earlier, as of Oct 9, 2026. BLS separately expects about 4,100 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $161,740 a year ($77.76 an hour), 217% above the median for all U.S. jobs ($50,980). Most people in this job earn between $92,940 and $225,330 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects growth of 9.1% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 83,000 jobs in 2035. It expects about 4,100 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 77,000 people in the U.S., roughly 0.05% of all workers (BLS, May 2025). That makes it the 311th largest of the 796 jobs on this site. BLS expects about 83,000 in 2035.

The most common requirement is a bachelor's degree: about 48% of people in the job said so in the official O*NET survey. O*NET rates the job at level 4 of 5 for preparation, which usually means: bachelor's degree. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Operations Analysis, Complex Problem Solving, Systems Evaluation, Active Learning
• Get strong at the parts of the job that stay with people (listed above), which take 6h 53m of a typical shift
• Tools employers list: The MathWorks MATLAB, Python, Perl, Linux, C++
• Learn to use AI well on the tasks where it already shows up in this job (listed above)

These use similar skills, with less of a typical shift touched by AI or robots. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Fuel Cell Engineers (0m touched, $104k median pay)
• Radio Frequency Identification Device Specialists (0m touched, $130k median pay)
• Mechatronics Engineers (0m touched, $123k median pay)
• Electrical and Electronic Engineering Technologists and Technicians (19m touched, $78k median pay)

Each task carries its own evidence label. For this job: 4 observed in real AI use, 14 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.