Oil and gas workers

AI Overlap Index
34.9 / 100
Selectively Exposed

Physical, social, or oversight-heavy work that AI augments rather than replaces.

SOC · Construction And Extraction

Bureau of Labor Statistics
Median pay
$52,610/yr
Hourly
$25/hr
Jobs 2024
115,900
Projected 2034
117,200
10-yr outlook
+1% · Slower than average
Employment change
1,400
Entry education
No formal educational credential
SOC code

Signal composition

how the 0-100 score is assembled

Task Automation Impact weight 60%
19.3
contribution to AOI: 11.6
Automation Potential weight 10%
30.0
contribution to AOI: 3.0
Market Pressure weight 15%
55.0
contribution to AOI: 8.2
Entry Barrier Erosion weight 15%
80.0
contribution to AOI: 12.0

By seniority

multiplicative adjustment from category curve

Entry
41.2
mult 1.18x
Mid
34.9
mult 1.00x
Senior
29.7
mult 0.85x

Entry-level roles carry the brunt because they concentrate the most automatable subset of tasks. Senior work is insulated by judgment, relationships, and accountability.

Task-level analysis

scored 0-100 for current-generation AI feasibility, weighted by BLS-stated importance

10 tasks · model: claude-sonnet-4-5-20250929
Important t5

Monitor mud pumps and fluid flow during drilling operations

AI can monitor sensor data, detect anomalies in fluid flow patterns, and alert operators to issues. However, human judgment is still needed for interpreting complex situations, making real-time adjustments, and handling unexpected conditions during active drilling.

BLS evidence: Derrick operators 'monitor mud pumps; mud returns (the mud discharged during drilling operations); and the flow of fluids used when drilling.'

48
automation
Important t3

Inspect equipment for defects and safety concerns

AI vision systems can detect some equipment defects and anomalies from images/sensors, but physical inspection in variable field conditions, tactile assessment, and judgment about safety-critical issues in high-stakes environments still requires substantial human involvement.

BLS evidence: Workers 'maintain equipment, including inspecting for defects or safety concerns' and derrick operators are 'responsible for routine inspection and maintenance of derrick equipment.'

35
automation
Supporting t10

Clean oil rigs, equipment, and work areas

Cleaning oil rigs involves physical labor in outdoor, hazardous environments with oil, mud, and irregular surfaces. While some industrial cleaning robots exist, the unstructured oilfield environment and need to navigate around active operations limits automation potential.

BLS evidence: Roustabouts 'clean oil rigs, equipment, and work areas.'

22
automation
Supporting t9

Load and unload tools, equipment, and supplies

Loading and unloading heavy equipment requires physical strength, spatial reasoning in cluttered outdoor environments, and coordination with crew members. While some warehouse robotics exist, oilfield conditions are too variable and unstructured for current automation.

BLS evidence: Workers 'may also help load and unload supplies or equipment on offshore rigs' and drillers 'may assist with loading and unloading tools, equipment, and other rig parts.'

20
automation
Core t2

Coordinate rig movement and drilling processes with crew members

Coordinating rig movement requires real-time spatial awareness, physical presence on-site, and dynamic human-to-human communication in noisy, hazardous environments where miscommunication can be fatal. AI cannot replace the embodied coordination required.

BLS evidence: Workers 'coordinate rig movement and processes with crew members' and 'collaborate as a crew to assemble, operate, and maintain drilling equipment.'

18
automation
Important t7

Direct and supervise crew members on oil rigs

Supervising crew members on oil rigs requires physical presence, real-time safety judgment in hazardous conditions, interpersonal leadership, and dynamic decision-making in unpredictable situations that AI cannot replicate.

BLS evidence: Drillers 'direct and monitor the work of derrick operators and roustabouts on an oil rig.'

15
automation
Core t8

Operate equipment to increase oil flow or remove obstructions from wells

Operating well intervention equipment requires physical manipulation of machinery in field conditions, real-time problem-solving for obstructions, and hands-on adjustments that current AI and robotics cannot perform autonomously in variable downhole environments.

BLS evidence: Service unit operators 'operate equipment used to increase oil flow from producing wells or to remove stuck pipes, casing, tools, or other obstructions from drilling wells.'

14
automation
Core t1

Set up and operate drilling equipment such as drills and pumps

Operating drilling equipment requires real-time physical manipulation in harsh, unpredictable outdoor environments with high-stakes safety considerations. Current robotics cannot match the dexterity and environmental adaptability required for this task.

BLS evidence: Oil and gas workers 'set up or operate equipment, such as drills and pumps, used in oil and gas exploration and extraction.'

12
automation
Important t6

Assemble and disassemble oilfield equipment and structures

Assembly and disassembly of heavy oilfield structures requires significant physical strength, dexterity in outdoor conditions, coordination with crew members, and manipulation of large components that robotics cannot handle in typical field environments.

BLS evidence: Roustabouts 'assemble and repair oilfield equipment, such as mud pumps, shakers, and pipes' and workers 'help move rigs and related structures.'

10
automation
Important t4

Adjust and repair drilling and extraction equipment

Repairing drilling equipment requires fine motor skills, physical strength, improvisation with tools in unpredictable field conditions, and hands-on problem-solving that current robotics cannot perform in the variable oilfield environment.

BLS evidence: Oil and gas workers 'adjust and repair equipment' and drillers 'complete routine maintenance and repairs to drilling equipment.'

8
automation

Task heatmap

automation score by task, sorted by weighted contribution

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External signals and sources

category-level priors and BLS fields that feed the four non-task signals

Automation Potential
30
karpathy 3/10
  • Karpathy/BLS Digital AI Exposure (0-10 scale rescaled to 0-100)
Market Pressure
55
outlook: Slower than average
  • BLS projected outlook: Slower than average (1%)
  • Indeed demand signal (monthly refresh pending)
Entry Barrier Erosion
80
ed: No formal educational credential
  • BLS typical entry-level education: No formal educational credential
  • Credential trend signal (annual refresh)

Related in Construction And Extraction

closest AOI neighbors in the same category