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Will AI replace commercial divers?

Nah.

Nearly all of the work is hands-on repair, welding and rigging underwater, where machines can film and assist but not fix. This job scores 85 out of 100 on (higher is safer). Today people do 6% of the work with AI’s help, and 94% still needs a person.

Updated 3 October 2026 49-9092 5319 2026-Q4
Installation, Maintenance, and RepairCommercial Divers49-9092 · 2026-Q4
0% AI does it6% AI helps94% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 94%AI helps 6%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the work stays in the water with people

Commercial diving is repair work done in a place that punishes mistakes. Divers inspect and test submerged structures, weld and cut metal at depth, rig and move heavy loads, and patch pipelines, pilings and hulls. Before any of that, someone decides whether the water, the current and the structure allow a dive at all. That judgment is made on the boat, by people who will live with the result.

The second reason is the hands. A diver works by feel in low visibility, threading a bolt, clearing marine growth, setting a clamp against swell. Our robotics read for this job puts most of the task time in the physical column and rates the capability needed at the dexterous humanoid tier, which is the hardest class of machine to build and the furthest from routine field use. Remotely operated vehicles are real and widely used, but they are mostly eyes, lights and a manipulator arm under human control, not a self-directed repair crew.

So the honest answer to the question people type, will AI replace commercial divers, is that software is reshaping the paperwork and the survey end of the trade while the wet work stays human. The share of task time that still needs a person here is 94%, and the tasks in that group are the ones the industry pays for: going in, fixing something, and coming back.

What AI does, what it assists, and what it leaves to divers

The tasks our data puts in the AI-does group are desk-side: writing up inspection records and sorting or tagging survey footage so an engineer can find the frame that matters. That slice of task time is 0%. It is the part of a diver’s day that happens dry, after the dive.

Assistance is broader in effect than in size. Software helps plan dives and gas schedules, flags corrosion and cracks in video from a camera or vehicle, and keeps logs tied to position data. The assisted share of task time is 6%. Machine vision can mark a weld seam as suspect; a diver or a supervisor still decides whether to cut it out. If you want the detail behind this split, our coverage score method explains how task time is counted.

What is left to people is the trade itself: underwater welding and cutting, equipment checks and gas management, rigging and salvage, and communication with the surface while conditions change. Confined-space entry, zero-visibility work by touch, and emergency response all sit here too. Our overall coverage figure for this job is 7 out of 100, which reflects how little of the work a system can take end to end today.

What the evidence covers, and what it does not

No study has put an AI system against a working commercial diver and measured who did the job better. The evidence grade here is D, our lowest tier, which means the quality comparison has not been measured. We do not publish a parity number when that is the case, and you should treat any site that does with suspicion.

What would settle it is specific and testable: a controlled trial of autonomous inspection against diver inspection on the same structures, with defect-detection rates reported; a demonstration of unmanned underwater welding or clamp installation to code, without a diver standing by; and incident data comparing machine-only and diver-assisted operations. Until something like that exists, the fair statement is that machines have taken survey and observation hours, not repair hours. The wider method, including how we grade evidence, is on our scoring methodology page.

The labor data is steadier ground. The Bureau of Labor Statistics counts about 3,450 commercial divers in the United States, with median pay of $72,990 (BLS, 2025) and projected employment growth of 4.8% from 2025 to 2035. That is a small, specialized trade growing slowly, not a shrinking one.

When subsea work could shift to machines

Most likely after 2046 (8 in 10 of our scenarios). Our replacement-year method explains what that window measures and how the spread is built.

Two things could pull it earlier. Cost is the clearest: the cost panel above compares machine time with a crewed dive spread, and the gap gives operators a strong reason to send a vehicle wherever one will do. Safety rules point the same way, because every hour a person is not in the water at depth is an hour of risk removed.

Two things hold it back. Dexterity is the first: resident vehicles and arms can brush, scan and film, but setting, torquing and welding against current is still a human skill, and our robotics tier reflects that. The second is the economics of a small market. Fewer than four thousand divers nationwide (BLS, 2025) is a thin commercial prize for anyone building a purpose-made subsea repair robot, so investment follows oil and gas inspection instead.

Good to know: ROV growth has been visible in this trade for decades, and the diving workforce has kept growing alongside it.

How to stay needed in this trade

Lean into the work that keeps you on the critical path. Three areas stand out: underwater welding and cutting to code, rigging and salvage on live structures, and dive supervision, including gas planning, equipment checks and emergency response. Those are the tasks our list keeps firmly in the human column.

Two skills raise your value quickly. The first is running and interpreting the machines: pilot a remotely operated vehicle, read sonar and video, and know when the footage is lying. The second is inspection reporting, including non-destructive testing methods, so you can sign off findings an engineer will act on. Divers who can do both the dive and the data become the person a client calls first.

If you are weighing nearby trades, the closest work on deck and in marine operations is worth a look: riggers, ship engineers and sailors and marine oilers. You can also see where this job sits among other maintenance and repair occupations, read the picture for the oil and gas sector, browse the jobs that mostly need a person (our top band, Nah.) on our safest jobs list, or put two trades side by side with the job comparison tool.

Frequently asked questions

How much do commercial divers make?

The Bureau of Labor Statistics reports median annual pay of $72,990 for commercial divers (BLS, 2025). Pay varies widely by sector and depth work. Inland civil and marine construction diving sits lower; offshore and saturation work pays far more, with long rotations and significant time away from home. Certifications in welding and non-destructive testing tend to lift day rates.

Are ROVs taking diving jobs?

Remotely operated vehicles have taken a lot of observation, survey and routine inspection work, especially at depth where diving is expensive and risky. They have not taken much repair work. Welding, clamp installation, rigging and salvage still need hands and judgment in the water. The task list above shows which parts of the job machines assist with and which stay with people.

Is commercial diving a dying trade?

The federal projections do not describe a dying trade. BLS expects employment in this occupation to grow 4.8% between 2025 and 2035, from a base of roughly 3,450 jobs (BLS, 2025). It is a small field, so hiring is cyclical and tied to offshore energy, bridge work and port projects. Entry is competitive and schools outnumber openings in some regions.

Will saturation diving be automated first?

Deep work is where the economics favor machines most, because keeping a person under pressure is costly and hazardous. That pressure has already moved much deep inspection to vehicles. Deep repair is the harder problem: tools must be placed, torqued and welded against current. Until a machine can do that unsupervised, saturation crews stay part of the plan for the heaviest jobs.

What jobs will be gone by 2030?

No occupation in our data is scored as gone by 2030. Change shows up as task erosion and fewer entry-level openings long before whole jobs disappear. The clearest pressure is on screen-based work that is mostly text, data or routine review. You can see where any job sits, and the window we estimate for it, on the rankings page.

What should a new diver learn beyond dive school?

Add a second trade on top of the diving ticket. Underwater welding and cutting, non-destructive testing, and hydraulic tool work all make you harder to replace on a job sheet. Learning to pilot a remotely operated vehicle and read its video and sonar also helps, because many contracts now mix machine survey with diver repair on the same project.

Each ridge is a slice of the job's task time.Needs a human 94%AI helps 6%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.

Commercial Divers, O*NET-SOC 49-9092. 94% of the job’s task time still needs a human, so 94 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 , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 94% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 94%AI helps 6%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 94%AI helps 6%AI does it 0%
Check and maintain diving equipment, such as helmets, masks, air tanks, harnesses, or gauges.Needs a human
Take appropriate safety precautions, such as monitoring dive lengths and depths and registering with authorities before diving expeditions begin.Needs a human
Communicate with workers on the surface while underwater, using signal lines or telephones.Needs a human
Descend into water with the aid of diver helpers, using scuba gear or diving suits.Needs a human
Inspect and test docks, ships, buoyage systems, plant intakes or outflows, or underwater pipelines, cables, or sewers, using closed circuit television, still photography, and testing equipment.Needs a human
Obtain information about diving tasks and environmental conditions.AI helps
Inspect the condition of underwater steel or wood structures.Needs a human
Operate underwater video, sonar, recording, or related equipment to investigate underwater structures or marine life.Needs a human
Repair ships, bridge foundations, or other structures below the water line, using caulk, bolts, and hand tools.Needs a human
Cut and weld steel, using underwater welding equipment, jigs, and supports.Needs a human
Carry out non-destructive testing, such as tests for cracks on the legs of oil rigs at sea.Needs a human
Take test samples or photographs to assess the condition of vessels or structures.Needs a human
Supervise or train other divers, including hobby divers.Needs a human
Perform activities related to underwater search and rescue, salvage, recovery, or cleanup operations.Needs a human
Recover objects by placing rigging around sunken objects, hooking rigging to crane lines, and operating winches, derricks, or cranes to raise objects.Needs a human
Install, inspect, clean, or repair piping or valves.Needs a human
Set or guide placement of pilings or sandbags to provide support for structures, such as docks, bridges, cofferdams, or platforms.Needs a human
Install pilings or footings for piers or bridges.Needs a human
Salvage wrecked ships or their cargo, using pneumatic power velocity and hydraulic tools and explosive charges, when necessary.Needs a human
Remove obstructions from strainers or marine railway or launching ways, using pneumatic or power hand tools.Needs a human
Drill holes in rock and rig explosives for underwater demolitions.Needs a human
Remove rubbish or pollution from the sea.Needs a human
Perform offshore oil or gas exploration or extraction duties, such as conducting underwater surveys or repairing and maintaining drilling rigs or platforms.Needs a human
Cultivate or harvest marine species or perform routine work on fish farms.Needs a human

Is it better than a person? The evidence

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

When could it be replaced?

When AI could largely do this job: no sooner than 2046

Most likely after 2046 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

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 behind its .

Today
Will AI replace this job?
Nah.
By 2045
20%
of our scenarios have AI largely doing this job by 2045 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)
By 2060
80%
of our scenarios have AI largely doing this job by 2060 (Largely.)
10% 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: 70.0% of scenarios: this job mostly needs a person (Nah.)70%2030: 30.0% of scenarios: AI could do a little of this job (A little.)30%20302035: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2035: 70.0% of scenarios: AI could do a little of this job (A little.)70%2035: 20.0% of scenarios: AI could partly do this job (Partly.)20%20352040: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2040: 30.0% of scenarios: AI could do a little of this job (A little.)30%2040: 40.0% of scenarios: AI could partly do this job (Partly.)40%2040: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%20402045: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2045: 40.0% of scenarios: AI could partly do this job (Partly.)40%2045: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2045: 20.0% of scenarios: AI could largely do this job (Largely.)20%20452050: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2050: 10.0% of scenarios: AI could partly do this job (Partly.)10%2050: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2050: 40.0% of scenarios: AI could largely do this job (Largely.)40%20502055: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2055: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2055: 60.0% of scenarios: AI could largely do this job (Largely.)60%20552060: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2060: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%2060: 80.0% of scenarios: AI could largely do this job (Largely.)80%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%30.0%70.0%
20350.0%0.0%20.0%70.0%10.0%
20400.0%20.0%40.0%30.0%10.0%
204520.0%30.0%40.0%0.0%10.0%
205040.0%40.0%10.0%0.0%10.0%
205560.0%30.0%0.0%0.0%10.0%
206080.0%10.0%0.0%0.0%10.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.8 out of 5 for consequence and decisions 4.2 out of 5 for impact; someone has to answer for them.
Clients want a personFace-to-face contact is rated 4.5 and physical closeness 4.2 out of 5; caring for or serving people is 3.1 out of 5 in importance.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Physical work78% of the task time is physical; robots have been shown on 72% of that time.
RegulationWorkers rate responsibility for others' health and safety 4.5 out of 5.
LicensingUsual entry requirement (BLS): postsecondary nondegree award, 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 (139 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$10–$1,390
A person’s wage for the same hours
$2,900–$10,570

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.

78%
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 94%AI helps 6%AI does it 0%
Writing · 0% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 6% 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 · 4.4% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 7.4% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 7.6% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 70.2% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 4.4% 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 94%AI helps 6%AI does it 0%
How exposed is it?

Still needs a human: 85/100↑ 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: 94% needs a human, 6% AI helps, 0% AI does it. Still needs a human: 85/100 ↑ 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: 85/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI-powered robots and remotely operated vehicles will take over more routine or hazardous underwater inspection and maintenance tasks, but human commercial divers will still be needed for complex, unpredictable, and hands-on work.

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

Commercial diving requires physical dexterity, adaptive problem-solving, and manipulation in unpredictable underwater environments that remain extremely difficult for robotics and AI to replicate cost-effectively within this timeframe.

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

While AI-driven robotics and autonomous underwater vehicles will increasingly take over dangerous, routine inspection and deep-water tasks, human divers will still be essential for complex, adaptable manual labor and unpredictable problem-solving in challenging underwater environments.

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

AI and underwater robots will automate routine inspection and reduce some diving work, but human divers will remain necessary for complex repairs, welding, salvage, and unpredictable underwater operations.

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 Commercial Divers? Nah. Still needs a human: 85/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/commercial-divers/ (accessed 4 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.