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needsahuman

Will AI replace computer hardware engineers?

A little.

This job scores 70 out of 100 on (higher is safer). Today AI could do about 17% of the work by itself, people do 19% with AI’s help, and 64% still needs a person.

Updated 3 October 2026O*NET-SOC 17-2061UK SOC 5244, 2124Release 2026-Q4
Architecture and EngineeringComputer Hardware Engineers17-2061 · 2026-Q4
17% AI does it19% AI helps64% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 64%AI helps 19%AI does it 17%
Each ridge is a slice of the job's task time.Needs a human 64%AI helps 19%AI does it 17%
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.

Computer Hardware Engineers, O*NET-SOC 17-2061. 64% of the job’s task time still needs a human, so 64 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 O*NET, and where AI stands on each today. 64% of the task time still needs a human.

Each block is one task; its height is its share of working time.Needs a human 64%AI helps 19%AI does it 17%
The job's task list: the parts AI can do are blacked out.Needs a human 64%AI helps 19%AI does it 17%
Update knowledge and skills to keep up with rapid advancements in computer technology.Needs a human
Design and develop computer hardware and support peripherals, including central processing units (CPUs), support logic, microprocessors, custom integrated circuits, and printers and disk drives.Needs a human
Confer with engineering staff and consult specifications to evaluate interface between hardware and software and operational and performance requirements of overall system.Needs a human
Build, test, and modify product prototypes, using working models or theoretical models constructed with computer simulation.Needs a human
Write detailed functional specifications that document the hardware development process and support hardware introduction.AI does it
Test and verify hardware and support peripherals to ensure that they meet specifications and requirements, by recording and analyzing test data.Needs a human
Direct technicians, engineering designers or other technical support personnel as needed.Needs a human
Provide technical support to designers, marketing and sales departments, suppliers, engineers and other team members throughout the product development and implementation process.Needs a human
Select hardware and material, assuring compliance with specifications and product requirements.AI helps
Store, retrieve, and manipulate data for analysis of system capabilities and requirements.AI does it
Analyze user needs and recommend appropriate hardware.AI does it
Evaluate factors such as reporting formats required, cost constraints, and need for security restrictions to determine hardware configuration.AI helps
Provide training and support to system designers and users.Needs a human
Monitor functioning of equipment and make necessary modifications to ensure system operates in conformance with specifications.Needs a human
Specify power supply requirements and configuration, drawing on system performance expectations and design specifications.AI helps
Assemble and modify existing pieces of equipment to meet special needs.Needs a human
Analyze information to determine, recommend, and plan layout, including type of computers and peripheral equipment modifications.AI helps
Recommend purchase of equipment to control dust, temperature, and humidity in area of system installation.AI helps

Is it better than a person? The evidence

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

When could it be replaced?

Could be largely automated 2037–2052

80% of scenarios between 2037 and 2052. A range from our scenario model of capability, adoption and friction, not a forecast that the job ends.

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 scenarios behind its replacement range.

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: 50.0% of scenarios: AI could do a little of this job (A little.)50%2030: 50.0% of scenarios: AI could partly do this job (Partly.)50%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%50.0%50.0%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 O*NET work context, licensing and the evidence we have.

LiabilityMistakes are rated 2.6 out of 5 for consequence and decisions 3.3 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 4.5 and physical closeness 2.8 out of 5; caring for or serving people is 2.1 out of 5 in importance.
LicensingUsual entry requirement (BLS): bachelor's degree.
RegulationWorkers rate responsibility for others' health and safety 2.7 out of 5.
Physical work22% of the task time is physical; robots have been shown on 74% of that time.

What would it cost to hand the work to AI?

The share of the year AI could handle (657 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$70–$6,570
A person’s wage for the same hours
$29,370–$71,200

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.

22%
of the task time is physical work
Dexterous humanoid
the kind of robot the physical work would need
Not commercial: no cited robot does most of this work; humanoids are at demonstration and pilot stage.

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 64%AI helps 19%AI does it 17%
Writing · 5.7% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 56.2% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 6.4% 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 · 6.2% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 3% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 10.3% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 12.3% 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 64%AI helps 19%AI does it 17%
How exposed is it?

Still needs a human: 70/100↑ 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: 64% needs a human, 19% AI helps, 17% AI does it. Still needs a human: 70/100 ↑ 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

40
Google searches a month, 12-month average to August 2026
Google searches a month, September 2025 to August 2026: from 30 to 40
3
estimated questions to AI assistants in September 2026
Estimated questions to AI assistants a month, October 2025 to September 2026: from 0 to 3
0.52
Google searches a month for every 1,000 people in the job
94th of 197 among all jobs we have search data for

In the UK

20
Google searches a month, 12-month average to August 2026
0.61
Google searches a month for every 1,000 people in the job in the UK (estimated)
88th of 197 among jobs we have UK search data for

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: 70/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

AI will automate many design, verification, and optimization tasks, but human hardware engineers will still be needed for architecture, trade-offs, physical constraints, and accountability.

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

AI will significantly augment hardware engineering by accelerating design, simulation, and testing, but the physical constraints, domain expertise, and creative problem-solving required for hardware design mean human engineers will remain essential within this timeframe.

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

While AI will automate significant portions of chip design, layout optimization, and verification, human engineers will remain essential for high-level architecture, physical lab testing, and navigating real-world manufacturing constraints.

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

AI will automate routine design, simulation, and documentation, but hardware engineers will remain essential for architecture, physical testing, trade-offs, and accountability.

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 Computer Hardware Engineers? A little. Still needs a human: 70/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/computer-hardware-engineers/ (accessed 3 October 2026).

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

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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.