Will AI replace Petroleum Pump System Operators, Refinery Operators, and Gaugers?
Most of the work in Petroleum Pump System Operators, Refinery Operators, and Gaugers still leans on things AI struggles with — research rates its theoretical AI reach at only ~20%, and real-world use lower still.
O*NET-SOC 51-8093
How your 17 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~20%). By late 2025, real-world AI use had reached about 4% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~20%), real-world use (~4%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 17 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Monitor process indicators, instruments, gauges, and meters to detect and report any possible problems.
- Read automatic gauges at specified intervals to determine the flow rate of oil into or from tanks, and the amount of oil in tanks.
- Plan movement of products through lines to processing, storage, and shipping units, using knowledge of system interconnections and capacities.
- Read and analyze specifications, schedules, logs, test results, and laboratory recommendations to determine how to set equipment controls to produce the required qualities and quantities of products.
- Record and compile operating data, instrument readings, documentation, and results of laboratory analyses.
- Start pumps and open valves or use automated equipment to regulate the flow of oil in pipelines and into and out of tanks.
- Control or operate manifold and pumping systems to circulate liquids through a petroleum refinery.
- Operate control panels to coordinate and regulate process variables such as temperature and pressure, and to direct product flow rate, according to process schedules.
- Signal other workers by telephone or radio to operate pumps, open and close valves, and check temperatures.
- Verify that incoming and outgoing products are moving through the correct meters, and that meters are working properly.
- Operate auxiliary equipment and control multiple processing units during distilling or treating operations, moving controls that regulate valves, pumps, compressors, and auxiliary equipment.
- Synchronize activities with other pumphouses to ensure a continuous flow of products and a minimum of contamination between products.
- Patrol units to monitor the amount of oil in storage tanks, and to verify that activities and operations are safe, efficient, and in compliance with regulations.
- Maintain and repair equipment, or report malfunctioning equipment to supervisors so that repairs can be scheduled.
- Collect product samples by turning bleeder valves, or by lowering containers into tanks to obtain oil samples.
- Inspect pipelines, tightening connections and lubricating valves as necessary.
- Conduct general housekeeping of units, including wiping up oil spills and performing general cleaning duties.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.