Will AI replace petroleum pump system operators, refinery operators, and gaugers?

Some tasks are already handled by AI or machines; the rest still needs a person. About 3h 7m of an 8-hour shift goes to tasks that AI or robots largely take over. The breakdown: 28m that AI mostly does alone, 2h 38m that robots have done in real workplaces. The other 4h 54m (61%) stays with people. Separately, BLS expects about 1.9% fewer of these jobs by 2035 (all jobs: +3.5%).

AI shows up regularly in 1 of 24 tasks, about 28m of a typical shift. The biggest ones:

• Record and compile operating data, instrument readings, documentation, and results of laboratory analyses. (28m a shift, AI mostly does it alone)

For some tasks, yes. Robots have done 4 of this job's tasks in workplaces like this one, about 2h 38m of a typical shift. 10 more tasks have only been done in factory setups built around the machine, so they stay with people here. For 1 physical task, no robot has shown it can do the work yet.

• Monitor process indicators, instruments, gauges, and meters to detect and report any possible problems. (1h 13m a shift; e.g. Spot (Spot CAM+IR, FLIR MUVE C360, Enhanced Autonomy Payload), in use)
• 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. (40m a shift; e.g. Spot (Boston Dynamics) at Chevron, in use)
• Start pumps and open valves or use automated equipment to regulate the flow of oil in pipelines and into and out of tanks. (28m a shift; e.g. CPS/DCI tank farm automation (PLC/SCADA oil-movement system), in use)
• Read automatic gauges at specified intervals to determine the flow rate of oil into or from tanks, and the amount of oil in tanks. (17m a shift; e.g. Spot (Boston Dynamics) with MFE/Teledyne FLIR payloads, in use)

4h 54m of a typical shift, or 61%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Operate control panels to coordinate and regulate process variables such as temperature and pressure, and to direct product flow rate, according to process schedules. (1h 2m a shift)
• Maintain and repair equipment, or report malfunctioning equipment to supervisors so that repairs can be scheduled. (28m a shift)
• Signal other workers by telephone or radio to operate pumps, open and close valves, and check temperatures. (23m a shift)
• Control or operate manifold and pumping systems to circulate liquids through a petroleum refinery. (23m a shift)
• Operate auxiliary equipment and control multiple processing units during distilling or treating operations, moving controls that regulate valves, pumps, compressors, and auxiliary equipment. (23m a shift)

Much of it comes down to where and how the work happens. In-person, hands-on and high-stakes work is where AI and robots have made the least headway so far. In the official O*NET survey of people in this job:

• 95% work in very hot or cold conditions at least weekly
• 88% say a mistake would be very or extremely serious
• 87% work outdoors in all weather every day

On Indeed, job postings in the Production & Manufacturing sector are at 124% of their February 2020 level (all U.S. postings: 104%), up 12.6% from a year earlier, as of Oct 9, 2026. BLS separately expects about 2,700 openings a year in this job through 2035. Across all U.S. postings, 7.3% now mention AI skills. Sector postings cover more than this one job and move for many reasons besides AI.

The median pay is about $96,710 a year ($46.50 an hour), 90% above the median for all U.S. jobs ($50,980). Most people in this job earn between $57,110 and $115,880 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer. Pick a state to compare:

BLS projects a decline of 1.9% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 32,000 jobs in 2035. Even so, it expects about 2,700 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 33,000 people in the U.S., roughly 0.02% of all workers (BLS, May 2025). That makes it the 461st largest of the 796 jobs on this site. BLS expects about 32,000 in 2035.

The most common requirement is a high school diploma: about 97% of people in the job said so in the official O*NET survey. O*NET rates the job at level 2 of 5 for preparation, which usually means: high school diploma, some training. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Operations Monitoring, Operation and Control, Monitoring, Reading Comprehension
• Get strong at the parts of the job that stay with people (listed above), which take 4h 54m of a typical shift
• Tools employers list: Microsoft Excel, Microsoft Outlook, Microsoft Word
• Learn to use AI well on the tasks where it already shows up in this job (listed above)

These use similar skills, with less of a typical shift touched by AI or robots. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Adhesive Bonding Machine Operators and Tenders (1h 8m touched, $46k median pay)
• Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic (18m touched, $49k median pay)
• Chemical Plant and System Operators (1h 1m touched, $78k median pay)
• Molding, Coremaking, and Casting Machine Setters, Operators, and Tenders, Metal and Plastic (2h 12m touched, $44k median pay)
• Extruding and Forming Machine Setters, Operators, and Tenders, Synthetic and Glass Fibers (2h 36m touched, $46k median pay)

Each task carries its own evidence label. For this job: 1 observed in real AI use, 4 with robots in real deployments, 19 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.