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Will AI replace derrick operators, oil and gas?

Nah.

Racking pipe, running the mud system and repairing derrick equipment are hands-on rig tasks that software can only assist with. This job scores 86 out of 100 on (higher is safer). Today people do 7% of the work with AI’s help, and 93% still needs a person.

Updated 3 October 2026 47-5011 8132 2026-Q4
Construction and ExtractionDerrick Operators, Oil and Gas47-5011 · 2026-Q4
0% AI does it7% AI helps93% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 93%AI helps 7%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 derrick work stays with the rig crew

Ask whether AI will replace derrick operators and the answer sits in the tasks, not in the headlines. Most of the shift is physical and shared. Operators rack and guide drill pipe in the derrick or mast, run the pipe-handling equipment, and keep the mud and pump system in step with what the hole is doing. Software can read every sensor on the rig. It cannot guide a stand of pipe into the fingerboard, or notice that a line is running rough.

The rest of the job pulls in the same direction. Mixing and conditioning drilling mud, inspecting cables, blocks and derrick gear, repairing pumps and valves, and reacting when pressure or returns change. That work happens in mud, noise, wind and cold, next to people whose safety depends on the next call. Accountability for it sits with a named person, not a model.

Here is the share of task time our scoring leaves with a person: 93%. The work a machine would have to take over is mostly physical, and at a level our robotics tier calls dexterous humanoid. No fielded system does that on a working drill floor today. You can see how the headline figure is built on the methodology page.

What AI does, what it helps with, and what stays with people

The tasks AI can already handle alone are the recording ones: logging pump pressure, mud volumes, tank levels and shift readings, then pushing them into a report. Share of task time in that group: 0%. None of it touches the pipe.

The assist group is bigger in practice. Rig automation flags abnormal pressure trends, suggests mud weight changes, and warns of stuck-pipe risk before a crew would see it. It also schedules maintenance on pumps and lines. Share of task time where AI helps a person rather than working alone: 7%. The operator still makes the call and still turns the wrench.

What stays human is the floor work itself. Tripping pipe and racking it safely, controlling the mud system as conditions change, and inspecting and repairing derrick equipment. Coverage, our answer to “can AI do it?”, lands at 5 on a 0 to 100 scale for this job. How that is measured is set out on the coverage method page.

The evidence, and what is missing

Nobody has published a clean head-to-head test of automated systems against derrick operators. Our evidence grade for “is it better than a person?” is D, which on this site means no direct comparison exists yet. So we publish no parity number for this job. A grade with no test behind it would be a guess dressed up as data.

What would settle it is specific: a reported field trial of automated pipe-handling and mud control on working rigs, measured against crewed floors on tripping speed, stuck-pipe and lost-circulation incidents, downtime and recordable injuries, with enough method detail to check. Equipment makers publish results from their own installations, but those are not independent tests against a crew. The grading scale is explained on the quality parity page.

Good to know: drilling automation is real on some new-build rigs, and it mostly changes how many hands are needed on the floor rather than removing the role.

When this could change

Most likely after 2048 (8 in 10 of our scenarios). What that window measures is set out on the replacement-year method page.

Two things could pull the window in. Automated pipe-handling and robotic drill floors are already specified on some new-build and offshore rigs, and each new rig sets the baseline for the next. Progress on dexterous robots that work outdoors in dirt and water would matter more here than any advance in language models.

Two things hold it back. Most US drilling runs on an existing fleet, and retrofitting a derrick is capital work that competes with day rates. And a rig floor is a safety-regulated workplace where a person signs for the lift, the well-control check and the repair. Employment is also not collapsing: BLS counts about 10,590 derrick operators in oil and gas, with projected employment up 1.6% from 2025 to 2035 (BLS, 2025).

How to stay needed on the floor

Lean into the work that is hardest to hand over. First, pipe handling and tripping judgment, including the calls that keep a trip safe when hole conditions turn. Second, mud system control, so you read returns, weight and volumes faster than the alarm does. Third, inspection and repair of derrick equipment, pumps and lines, which is where crews get kept when headcount tightens.

Two skills raise your floor. Learn to troubleshoot the rig’s automation and sensor stack, so you can tell a bad reading from a bad hole. And build formal safety and well-control credentials, because accountability is the part that does not transfer to software.

If you want to see where this sits against neighboring jobs, rotary drill operators, service unit operators and roustabouts share much of the same floor. You can also put any two jobs side by side on the compare tool, read the wider picture for extraction workers and the mining, oil and gas sector, or browse the jobs that mostly need a person list.

Frequently asked questions

Are automated drilling rigs cutting derrick operator jobs?

Automation changes the mix of hands on a rig more than it removes the role. Pipe-handling systems and sensor monitoring reduce some manual watching, while repair, inspection and mud work stay. Federal projections show employment for derrick operators in oil and gas rising 1.6% between 2025 and 2035 (BLS, 2025), which is slow growth rather than decline.

Are heavy equipment operators going to be replaced by AI?

Machine guidance and semi-autonomous equipment are spreading, mostly on fixed, repeatable ground like mine haul roads. Jobs with changing terrain, rigging, inspection and shared safety duties move much slower. The pattern is task erosion: the routine passes to software, the hands-on and accountable parts stay. The task list above shows how that split falls for derrick work.

What does a derrick operator actually do?

Derrick operators work the upper part of the rig and the pipe-handling gear. They rack and guide drill pipe during trips, run and monitor the mud mixing and circulating system, watch pump pressure and tank levels, inspect cables, blocks and derrick equipment, and repair pumps and valves. The job mixes physical rig work with close attention to well conditions.

Which drilling tasks can software already handle?

Recording and reporting are the clearest cases: logging pressures, mud volumes and shift readings, and generating paperwork. Monitoring software also flags pressure trends, stuck-pipe risk and maintenance due dates earlier than a person would. What it does not do is handle pipe, mix and condition mud at the shaker, or carry out repairs on the floor.

How much do derrick operators earn?

Median annual pay for derrick operators in oil and gas is about $58,620, and federal data counts roughly 10,590 of these jobs in the United States (BLS, 2025). Earnings vary with rotation, overtime, offshore versus land work, and basin activity, so actual take-home can sit well above the median in a busy drilling year.

What should a derrick operator learn next?

Two directions pay off. Get fluent with the rig’s automation and sensor systems, so you can diagnose a faulty reading and work with the alerts instead of around them. Then push on formal safety and well-control certification. Crews keep people who can both run the floor and sign for the decisions a machine cannot own.

Each ridge is a slice of the job's task time.Needs a human 93%AI helps 7%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.

Derrick Operators, Oil and Gas, O*NET-SOC 47-5011. 93% of the job’s task time still needs a human, so 93 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 . 93% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 93%AI helps 7%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 93%AI helps 7%AI does it 0%
Start pumps that circulate mud through drill pipes and boreholes to cool drill bits and flush out drill cuttings.Needs a human
Control the viscosity and weight of the drilling fluid.Needs a human
Listen to mud pumps and check regularly for vibration and other problems to ensure that rig pumps and drilling mud systems are working properly.Needs a human
Inspect derricks, or order their inspection, prior to being raised or lowered.Needs a human
Prepare mud reports, and instruct crews about the handling of any chemical additives.AI helps
Position and align derrick elements, using harnesses and platform climbing devices.Needs a human
Inspect derricks for flaws, and clean and oil derricks to maintain proper working conditions.Needs a human
Supervise crew members, and provide assistance in training them.Needs a human
Repair pumps, mud tanks, and related equipment.Needs a human
Steady pipes during connection to or disconnection from drill or casing strings.Needs a human
Weigh clay, and mix with water and chemicals to make drilling mud, using portable mixers.Needs a human
Guide lengths of pipe into and out of elevators.Needs a human
Clamp holding fixtures on ends of hoisting cables.Needs a human
String cables through pulleys and blocks.Needs a human
Set and bolt crown blocks to posts at tops of derricks.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 2048

Most likely after 2048 (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
10%
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
70%
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: 90.0% of scenarios: this job mostly needs a person (Nah.)90%2030: 10.0% of scenarios: AI could do a little of this job (A little.)10%20302035: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2035: 80.0% of scenarios: AI could do a little of this job (A little.)80%2035: 10.0% of scenarios: AI could partly do this job (Partly.)10%20352040: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2040: 40.0% of scenarios: AI could do a little of this job (A little.)40%2040: 40.0% of scenarios: AI could partly do this job (Partly.)40%2040: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%20402045: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2045: 50.0% of scenarios: AI could partly do this job (Partly.)50%2045: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2045: 10.0% of scenarios: AI could largely do this job (Largely.)10%20452050: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2050: 20.0% of scenarios: AI could partly do this job (Partly.)20%2050: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2050: 30.0% of scenarios: AI could largely do this job (Largely.)30%20502055: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2055: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2055: 50.0% of scenarios: AI could largely do this job (Largely.)50%20552060: 10.0% of scenarios: this job mostly needs a person (Nah.)10%2060: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2060: 70.0% of scenarios: AI could largely do this job (Largely.)70%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%10.0%90.0%
20350.0%0.0%10.0%80.0%10.0%
20400.0%10.0%40.0%40.0%10.0%
204510.0%30.0%50.0%0.0%10.0%
205030.0%40.0%20.0%0.0%10.0%
205550.0%40.0%0.0%0.0%10.0%
206070.0%20.0%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 3.9 out of 5 for consequence and decisions 3.8 out of 5 for impact; someone has to answer for them.
Clients want a personFace-to-face contact is rated 4.7 and physical closeness 3.7 out of 5; caring for or serving people is 3.9 out of 5 in importance.
RegulationWorkers rate responsibility for others' health and safety 4.3 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.
Physical work85% of the task time is physical; robots have been shown on 76% of that time.
LicensingUsual entry requirement (BLS): no formal educational credential, then short-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (106 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$10–$1,060
A person’s wage for the same hours
$2,210–$4,170

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.

85%
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 93%AI helps 7%AI does it 0%
Writing · 7.3% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 9.1% 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 · 76% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 7.6% 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 93%AI helps 7%AI does it 0%
How exposed is it?

Still needs a human: 86/100↑ 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: 93% needs a human, 7% AI helps, 0% AI does it. Still needs a human: 86/100 ↑ 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: 86/100 ↑ safer. Will AI replace them? Nah.

ChatGPTPartly

AI and automation will likely reduce some derrick-operator tasks and staffing needs, but safety-critical, maintenance, and on-site decision-making roles will still require humans in many drilling operations.

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

Derrick operators work in dynamic, physically demanding oilfield environments requiring hands-on equipment handling, real-time judgment, and adaptability that current robotics and AI cannot yet reliably replicate at scale.

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

While automated drilling systems and robotics will take over many hazardous physical and monitoring tasks on the rig floor, human operators will still be needed to oversee complex operations, handle unexpected mechanical issues, and manage unpredictable well conditions.

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

AI will automate routine monitoring and pipe-handling tasks, but human derrick operators will likely remain necessary for physical work, safety judgment, maintenance, and emergencies.

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 Derrick Operators, Oil and Gas? Nah. Still needs a human: 86/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/derrick-operators-oil-and-gas/ (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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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.