Opens in a new tab
needsahuman
Search ⌘KGet the data
Construction and ExtractionPile Driver Operators47-2072 · 2026-Q4
0% AI does it0% AI helps100% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 100%AI helps 0%AI does it 0%
Each ridge is a slice of the job's task time.Needs a human 100%AI helps 0%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.

Pile Driver Operators, O*NET-SOC 47-2072. 100% of the job’s task time still needs a human, so 100 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. 100% of the task time still needs a human.

Each block is one task; its height is its share of working time.Needs a human 100%AI helps 0%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 100%AI helps 0%AI does it 0%
Move hand and foot levers of hoisting equipment to position piling leads, hoist piling into leads, and position hammers over pilings.Needs a human
Move levers and turn valves to activate power hammers, or to raise and lower drophammers that drive piles to required depths.Needs a human
Drive pilings to provide support for buildings or other structures, using heavy equipment with a pile driver head.Needs a human
Conduct pre-operational checks on equipment to ensure proper functioning.Needs a human
Clean, lubricate, and refill equipment.Needs a human

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 no sooner than 2048, most likely after 2060

80% of scenarios after 2048. 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?
Nah.
By 2045
10%
of our scenarios have AI largely doing this job by 2045 (Largely.)
90% still have it mostly needing a person (A little. or Nah.)
By 2060
10%
of our scenarios have AI largely doing this job by 2060 (Largely.)
90% 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: this job mostly needs a person (Nah.)100%Today2030: 100.0% of scenarios: this job mostly needs a person (Nah.)100%20302035: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2035: 10.0% of scenarios: AI could do a little of this job (A little.)10%20352040: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2040: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%20402045: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2045: 10.0% of scenarios: AI could largely do this job (Largely.)10%20452050: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2050: 10.0% of scenarios: AI could largely do this job (Largely.)10%20502055: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2055: 10.0% of scenarios: AI could largely do this job (Largely.)10%20552060: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2060: 10.0% of scenarios: AI could largely do this job (Largely.)10%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%0.0%100.0%
20300.0%0.0%0.0%0.0%100.0%
20350.0%0.0%0.0%10.0%90.0%
20400.0%10.0%0.0%0.0%90.0%
204510.0%0.0%0.0%0.0%90.0%
205010.0%0.0%0.0%0.0%90.0%
205510.0%0.0%0.0%0.0%90.0%
206010.0%0.0%0.0%0.0%90.0%

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.

Physical work100% of the task time is physical; robots have been shown on 18% of that time.
LiabilityMistakes are rated 4.2 out of 5 for consequence and decisions 4.2 out of 5 for impact; someone has to answer for them.
RegulationWorkers rate responsibility for others' health and safety 4.7 out of 5; the sector has its own rules on who may do the work.
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 4.6 and physical closeness 3.9 out of 5; caring for or serving people is 2.5 out of 5 in importance.
LicensingUsual entry requirement (BLS): high school diploma or equivalent, then moderate-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (0 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$0–$0
A person’s wage for the same hours
$0–$0

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.

100%
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 100%AI helps 0%AI does it 0%
Writing · 0% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 0% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% 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 · 0% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 0% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 100% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 0% 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 100%AI helps 0%AI does it 0%
How exposed is it?

Still needs a human: 89/100↑ 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: 100% needs a human, 0% AI helps, 0% AI does it. Still needs a human: 89/100 ↑ safer. Will AI replace them? Nah.

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: 89/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI and automation may take over some machine-control, monitoring, and safety-assistance tasks, but skilled pile driver operators will still be needed for complex site conditions, judgment, and supervision.

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

Pile driving requires physical equipment operation, on-site judgment, and adaptation to unpredictable ground conditions that remain far beyond current robotics and AI capabilities within a 10-year timeframe.

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

While AI and automation will increasingly handle the positioning, precision driving, and monitoring tasks, human operators will still be required on-site to manage complex, unpredictable geotechnical conditions, oversee rigging, and ensure safety.

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

AI will automate some repetitive pile-driving tasks, but operators will likely remain necessary for supervision, judgment, safety, and handling unpredictable site conditions over the next decade.

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 Pile Driver Operators? Nah. Still needs a human: 89/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/pile-driver-operators/ (accessed 3 October 2026).

Scores change with each release, so cite the release. The data is open under CC BY 4.0: 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: O*NET 31.0, US Department of Labor (CC BY 4.0).
  • Jobs, pay and projections: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics and Employment Projections 2025–35.
  • How AI is used today: Anthropic Economic Index; Microsoft Research, "Working with AI".
  • What AI can do: our task ratings (rubric r1) and the quality evidence register.
  • UK names and employment: ONS SOC 2020 coding index and Annual Population Survey.

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