AI Automation Index

Will AI Replace Roustabouts, Oil and Gas?

Task-level automation exposure for Roustabouts, Oil and Gas: 13 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

7% weighted task index

13 of 13 tasks scored

Median Salary

$46,960 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

44,970 people hold this job — size, not growth

Projected 2025–35

+3.6% employment change

4,100 openings a year · BLS line item

Pay by state

BLS OEWS publishes 23 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$44,850 – $60,810

Highest medians

Alaska $60,810

North Dakota $60,480

Montana $58,800

Florida $57,080

Nebraska $53,340

Lowest medians

Louisiana $44,850

Arkansas $44,960

Texas $45,950

Kansas $46,220

Illinois $46,500

State figures come from the 47-5071 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 7%

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

Physical work 100%

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

Judgment & influence 0%

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

Routine administration 0%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

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

Consequence of error 3/100 Low

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

13 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) 0%

0 tasks

Medium exposure (≥ 35%) 0%

0 tasks

Low exposure (below 35%) 100%

13 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 →

Constituent Tasks

#7112 · Core · 4% automatable

Unscrew or tighten pipes, casing, tubing, and pump rods, using hand and power wrenches and tongs.

physical manipulation — Hands-on plumbing in structures

Install plumbing or piping.

#7116 · Core · 10% automatable

Dismantle and repair oil field machinery, boilers, and steam engine parts, using hand tools and power tools.

physical manipulation — Physical maintenance of mechanical equipment

Maintain mechanical equipment.

#7119 · Core · 10% automatable

Guide cranes to move loads about decks.

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

Operate cranes, hoists, or other moving or lifting equipment.

#20145 · Core · 15% automatable

Walk flow lines to locate leaks, using electronic detectors and by making visual inspections, and repair the leaks.

visual inspection — Physical locating of worn parts needs hands-on presence

Locate equipment or materials in need of repair or replacement. Maintain extraction or excavation equipment.

#23978 · Core · 6% automatable

Lay gas and oil pipelines.

physical manipulation — Production equipment installation is physical trade work

Install production equipment or systems. Install plumbing or piping.

#7113 · Core · 5% automatable

Bolt together pump and engine parts.

physical manipulation — Physical assembly of products by hand

Assemble products or production equipment.

#7115 · Core · 3% automatable

Move pipes to and from trucks, using truck winches and motorized lifts, or by hand.

physical manipulation — Physical loading in construction or extraction

Load or unload materials used in construction or extraction.

#23979 · Core · 5% automatable

Clean trucks used in the fields.

physical manipulation — Hands-on washing of vehicle surfaces and parts

Clean vehicles or vehicle components.

#7121 · Supplemental · 6% automatable

Dig holes, set forms, and mix and pour concrete into forms to make foundations for wood or steel derricks.

physical manipulation — Physical handling of substances in workspace

Mix substances or compounds needed for work activities. Dig holes or trenches. Pour materials into or on designated areas.

#7120 · Supplemental · 7% automatable

Supply equipment to rig floors as requested and provide assistance to roughnecks.

physical manipulation — Manual moving of construction materials on site

Assist skilled construction or extraction personnel. Move construction or extraction materials to locations where they are needed.

#7111 · Supplemental · 10% automatable

Clean up spilled oil by bailing it into barrels.

physical manipulation — Work site cleaning is physical labor

Clean work sites.

#7117 · Supplemental · 3% automatable

Dig drainage ditches around wells and storage tanks.

physical manipulation — Manual digging with tools in ground

Dig holes or trenches.

#7122 · Supplemental · 3% automatable

Cut down and remove trees and brush to clear drill sites, to reduce fire hazards, and to make way for roads to sites.

physical manipulation — Manual clearing of debris and vegetation outdoors

Remove debris or vegetation from work sites.

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Community Sentiment

Do you agree?

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

Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
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. 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. 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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