Gini Loh System Tools

AI Automation Index

Will AI Replace Service Unit Operators, Oil and Gas?

Task-level automation exposure for Service Unit Operators, Oil and Gas: 19 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified
Developed & audited by Gini Loh

Automation Exposure

24% weighted task index

19 of 19 tasks scored

Median Salary

$58,160 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

43,140 people hold this job — size, not growth

Projected 2025–35

+1.1% employment change

3,800 openings a year · BLS line item

Pay by state

BLS OEWS publishes 27 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$28,280 – $106,480

Highest medians

Alaska $106,480
Missouri $90,580
Montana $77,750
New Mexico $64,990
Nebraska $62,990

Lowest medians

Kentucky $28,280
Illinois $41,680
New York $45,750
Kansas $46,230
Arkansas $48,120

State figures come from the 47-5013 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 24%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 50%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 13%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 7%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 7%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 61/100 High

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

19 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 7%

1 tasks

Medium exposure (≥ 35%) 15%

3 tasks

Low exposure (below 35%) 78%

15 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Emerging & rewritten tasks

Tasks O*NET added or rewrote for this occupation in its recent updates (05/2025 – 08/2026), with who proposed them. Additions are not in the scored task inventory — they are new work O*NET is still measuring, so they appear here and nowhere in the index. A Revision replaces a task that is scored, which is why only those move the "Rewritten by O*NET" share.

  • Revision 07/2013 · Incumbent

    Maintain and perform safety inspections on rigs, equipment, and other tools.

    Replaced: Maintain and perform safety inspections on equipment and tools.

Constituent Tasks

#20451 · Core · 13% automatable Revision

Maintain and perform safety inspections on equipment and tools.

visual inspection — Construction equipment inspection is physical, hands-on

Inspect equipment or tools to be used in construction or excavation. Maintain extraction or excavation equipment.
#7080 · Core · 10% automatable

Operate controls that raise derricks or level rigs.

physical manipulation — Crane/hoist operation demands real-time physical control

Operate cranes, hoists, or other moving or lifting equipment.
#20452 · Core · 30% automatable

Listen to engines, rotary chains, or other equipment to detect faulty operations or unusual well conditions.

visual inspection — Extraction operations oversight is physical, hazardous, human-led

Monitor extraction operations.
#7083 · Core · 80% automatable

Prepare reports of services rendered, tools used, or time required, for billing purposes.

text generation — Generate operational reports from structured data

Prepare operational reports.
#7076 · Core · 4% automatable

Install pressure-control devices onto wellheads.

physical manipulation — Hands-on plumbing in structures

Install plumbing or piping.
#7074 · Core · 42% automatable

Confer with others to gather information regarding pipe or tool sizes or borehole conditions in wells.

interpersonal — On-site construction discussion is contextual, physical

Communicate with other construction or extraction personnel to discuss project details.
#7078 · Core · 15% automatable

Operate pumps that circulate water, oil, or other fluids through wells to remove sand or other materials obstructing the free flow of oil.

physical manipulation — Hands-on pump and compressor operation

Operate pumps or compressors.
#7075 · Core · 10% automatable

Drive truck-mounted units to well sites.

situated mobility — Truck driving needs real-world navigation and control

Drive trucks or truck-mounted equipment.
#7088 · Core · 22% automatable

Interpret instrument readings to ascertain the depth of obstruction.

physical manipulation — Physical site dimension measurement

Measure work site dimensions.
#7077 · Core · 10% automatable

Thread cables through derrick pulleys, using hand tools.

physical manipulation — Crane/hoist operation demands real-time physical control

Operate cranes, hoists, or other moving or lifting equipment.
#7085 · Core · 50% automatable

Select fishing methods or tools for removing obstacles such as liners, broken casing, screens, or drill pipe.

decision support — Construction equipment selection needs site and safety judgment

Select construction equipment.
#7079 · Core · 6% automatable

Close and seal wells no longer in use.

physical manipulation — Site preparation, heavy physical work

Prepare excavation or extraction sites for commissioning or decommissioning.
#7081 · Supplemental · 20% automatable

Direct drilling crews performing activities such as assembling and connecting pipe, applying weights to drill pipes, or drilling around lodged obstacles.

interpersonal — Directing crews in the field is human leadership work

Direct construction or extraction personnel.
#19874 · Supplemental · 40% automatable

Apply green technologies or techniques, such as the use of coiled tubing, slim-hole drilling, horizontal drilling, hydraulic fracturing, or gas lift systems.

decision support — AI advises adoption; humans deploy and integrate

Apply new technologies to improve work processes.
#7084 · Supplemental · 6% automatable

Operate specialized equipment to remove obstructions by backing off or severing pipes by chemical or explosive action.

physical manipulation — Detonation equipment handled with physical safety

Operate detonation equipment.
#7082 · Supplemental · 6% automatable

Perforate well casings or sidewalls of boreholes with explosive charges.

physical manipulation — Detonation equipment handled with physical safety

Operate detonation equipment.
#7086 · Supplemental · 18% automatable

Examine unserviceable wells to determine actions to be taken to improve well conditions.

visual inspection — Construction equipment inspection is physical, hands-on

Inspect equipment or tools to be used in construction or excavation.
#7089 · Supplemental · 30% automatable

Monitor sound wave-generating or detecting mechanisms to determine well fluid levels.

visual inspection — Extraction operations oversight is physical, hazardous, human-led

Monitor extraction operations.
#7087 · Supplemental · 18% automatable

Insert detection instruments into wells with obstructions.

visual inspection — Construction equipment inspection is physical, hands-on

Inspect equipment or tools to be used in construction or excavation.
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Community Sentiment

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Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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