Chemical Equipment Operators and Tenders
In short: today's best AI models could do about 22% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 78% of the time, stays with people.
Operate or tend equipment to control chemical changes or reactions in the processing of industrial or consumer products. Equipment used includes devulcanizers, steam-jacketed kettles, and reactor vessels.
139,630 people do this job in the US. $58,040 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work9 h
- Desk work AI can't do yet0 h
- Stays with people31 h
Chemical Equipment Operators and Tenders, now: of a 40-hour week, AI could take on 0 hours, 9 hours become checking its work, 0 hours are desk work it can't do yet, and 31 hours stay with people.
The largest pieces: Operate reaction equipment (about 4 h, a person checks); Estimate materials required (about 2 h, a person checks); Record operational data (about 1 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 6%
- 16%
- 1%
- 3%
- 74%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 22% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 2%. With Claude Mythos Preview (early), measured in April 2026, 17%. Today's estimate: 22%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 24 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0058% to 0.004% (released February and March 2025).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0058% | 589 of 708 | 1 of 24 |
| Released March 2025 | 0.004% | 601 of 703 | 2 of 24 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 24 |
| The week of Nov 13, 2025 (released January 2026) | none | n/a | 0 of 24 |
| The week of Feb 5, 2026 (released March 2026) | none | n/a | 0 of 24 |
| April 2026 (released June 2026) | none | n/a | 0 of 24 |
| May 2026 (released June 2026) | none | n/a | 0 of 24 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 71% of this job's working time as physical work. For 70% of the working time, a robot has been shown doing most of the task somewhere: 45% in a purpose-built cell, 24% in a structured facility. 0.94 of 3, the 153rd highest of the 923 jobs.
- Not physical 29%
- No robot shown 1%
- In a purpose-built cell 45%
- In a structured facility 24%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
78% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Operate reaction equipment, the hands-on work, 9%
- Patrol for leaks, the hands-on work, 7%
- Drain and flush equipment, the hands-on work, 6%
- Measure and mix chemicals, the hands-on work, 6%
- Load tanks for shipment, the hands-on work, 6%
- Clean equipment with steam, the hands-on work, 6%
What becomes checking the machine
21% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it.
- Operate reaction equipment, severe if wrong, 9%
- Estimate materials required, costly if wrong, 4%
- Record operational data, costly if wrong, 3%
- Adjust process controls, severe if wrong, 2%
- Monitor gauges and instruments, severe if wrong, 2%
- Read plant specifications, costly if wrong, 0.8%
What to learn
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- The hands-on craft. About 74% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Running AI inside the business systems. About 16% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 24 tasks from .
| Task | ||||
|---|---|---|---|---|
| Control or operate equipment in which chemical changes or reactions take place during the processing of industrial or consumer products.Running the reactors at the equipment and from the console.Done several times a day by most who do it. Robots: in a purpose-built cell, Emerson DeltaV Batch / DeltaV Live on Synthomer R7500 and R8000 polymer reactors (deployed). Anthropic's rating. | 18% | 1.7 h25 min to 3.3 h | Systems 50%, hands-on 50% | 49%Desk part half by now |
| Patrol work areas to detect leaks or equipment malfunctions or to monitor operating conditions.Walking the area to find leaks and faults.Done daily by most who do it. Robots: in a structured facility, Boston Dynamics Spot (deployed). Anthropic's rating. | 7% | 25 min8 min to 50 min | Hands-on 100% | Stays with people |
| Drain equipment, and pump water or other solutions through to flush and clean tanks or equipment.Equipment drained and flushed.Done daily by most who do it. Robots: in a purpose-built cell, Agidens Pharma CIP skid (sold). Anthropic's rating. | 6% | 50 min25 min to 2.1 h | Hands-on 100% | Stays with people |
| Measure, weigh, and mix chemical ingredients, according to specifications.Weighing and mixing to specification.Done daily by most who do it. Robots: in a purpose-built cell, Coperion K-Tron automated batch dispensing / LIW-GIW dispensary systems (sold). Anthropic's rating. | 6% | 38 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Load products into tanks for shipment.Products loaded into tanks.Done daily by most who do it. | 6% | 50 min25 min to 1.7 h | Hands-on 100% | Stays with people |
| Flush or clean equipment, using steam hoses or mechanical reamers.Steam hoses and reamers on the equipment.Done daily by most who do it. Robots: in a purpose-built cell, Clean-in-place (CIP) skids with installed spray devices (bioreactor/fermenter CIP) (CRB / industry standard practice) (deployed). Anthropic's rating. | 6% | 50 min25 min to 2.1 h | Hands-on 100% | Stays with people |
| Add treating or neutralizing agents to products, and pump products through filters or centrifuges to remove impurities or to precipitate products.Agents added and products pumped through filters.Done several times a day by most who do it. Robots: in a purpose-built cell, Yokogawa batch neutralization pH control system (pH analyzer plus controlled reagent feed) (sold). Anthropic's rating. | 6% | 38 min17 min to 1.3 h | Hands-on 100% | Stays with people |
| Inspect equipment or units to detect leaks or malfunctions, shutting equipment down, if necessary.Checking the units and shutting them down on a fault.Done daily by most who do it. Robots: in a structured facility, Spot with Spot CAM+IR, FLIR MUVE C360 and Enhanced Autonomy Payload (Boston Dynamics / MFE Inspection Solutions) (deployed). Anthropic's rating. | 5% | 25 min13 min to 1.3 h | Hands-on 100% | Stays with people |
| Estimate materials required for production and manufacturing of products.Quantities worked out on paper.Done daily by most who do it. | 4% | 38 min13 min to 1.3 h | Documents 100% | 100%Half by now |
| Adjust controls to regulate temperature, pressure, feed, or flow of liquids or gases and times of prescribed reactions, according to knowledge of equipment and processes.Controls adjusted at the equipment and on the console.Done several times a day by most who do it. Robots: in a structured facility, ISA-88 batch control system (Rockwell FactoryTalk Batch + Ignition) on a chemical plant reactor train (DSI Innovations / Rockwell Automation) (deployed). Anthropic's rating. | 4% | 17 min8 min to 38 min | Systems 50%, hands-on 50% | 50%Desk part half by now |
| Test product samples for specific gravity, chemical characteristics, pH levels, concentrations, or viscosities, or send them to laboratories for testing.Gravity, pH and viscosity tests run or sent out.Done daily by most who do it. Robots: in a purpose-built cell, Metrohm 2060 TI Process Analyzer (sold). Anthropic's rating. | 4% | 25 min8 min to 1.3 h | Hands-on 100% | Stays with people |
| Open valves or start pumps, agitators, reactors, blowers, or automatic feed of materials.Valves and pumps at the equipment.Done several times a day by most who do it. Robots: in a purpose-built cell, Yokogawa FKDPP autonomous control AI driving plant control valves (deployed). Anthropic's rating. | 3% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Chemical Plant and System Operators22% now, 22% by 2028
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders5% now, 5% by 2028
- Water and Wastewater Treatment Plant and System Operators33% now, 33% by 2028
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders5% now, 5% by 2028
- Heat Treating Equipment Setters, Operators, and Tenders, Metal and Plastic20% now, 20% by 2028
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders10% now, 10% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Chemical Equipment Operators and Tenders is within reach of AI now?
- An estimated 22% of the working time is within reach of AI models now and 22% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Chemical Equipment Operators and Tenders come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Operate reaction equipment (49% of the task's time now); Estimate materials required (100% of the task's time now); and Record operational data (100% of the task's time now).
- Which tasks of Chemical Equipment Operators and Tenders stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Patrol for leaks; Drain and flush equipment; and Measure and mix chemicals. Together such tasks are about 62% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Chemical Equipment Operators and Tenders learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are judgment where errors are severe; the hands-on craft; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 78% of the working time stays with people, 21% becomes checking a model's work and 0% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Chemical Equipment Operators and Tenders?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Chemical Equipment Operators and Tenders?
- Anthropic's robot exposure rating (September 2026) finds 71% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 70% of the working time, 24% in a structured facility. Its index is 0.94 of 3. One example: Boston Dynamics Spot for "patrol for leaks". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 24 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on September 30, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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