Quality Control Analysts
In short: today's best AI models could do about 46% 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 53% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 47% of the time, stays with people.
Conduct tests to determine quality of raw materials, bulk intermediate and finished products. May conduct stability sample tests.
$62,280 a year (for the broader BLS group this job sits in).
A typical 40-hour week
Not yet reviewed task by task- AI could take on19 h
- A person checks AI's work0 h
- Desk work AI can't do yet2 h
- Stays with people19 h
Quality Control Analysts, now: of a 40-hour week, AI could take on 19 hours, 0 hours become checking its work, 2 hours are desk work it can't do yet, and 19 hours stay with people.
The largest pieces: Compile laboratory test data and perform appropriate analyses (about 2 h); Participate in out-of-specification and failure investigations and recommend corrective actions (about 2 h); Supply quality control data necessary for regulatory submissions (about 2 h).
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.
- 53%
- 0%
- 47%
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.
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, 0%. With Claude Mythos Preview (early), measured in April 2026, 19%. Today's estimate: 47%.
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, 0.58% went to this job's tasks in May 2026, the 45th largest of the 447 jobs that showed up at all; 4 of its 26 tasks showed up. Within each of Anthropic's methods, never across a change: 0.024% to 0.021% (released February and March 2025); 0.014% to 0.015% (August 2025 to February 2026); 0.7% to 0.58% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.024% | 414 of 708 | 5 of 26 |
| Released March 2025 | 0.021% | 409 of 703 | 3 of 26 |
| The week of Aug 4, 2025 (released September 2025) | 0.014% | 415 of 655 | 4 of 26 |
| The week of Nov 13, 2025 (released January 2026) | 0.013% | 440 of 672 | 4 of 26 |
| The week of Feb 5, 2026 (released March 2026) | 0.015% | 433 of 677 | 3 of 26 |
| April 2026 (released June 2026) | 0.7% | 37 of 434 | 4 of 26 |
| May 2026 (released June 2026) | 0.58% | 45 of 447 | 4 of 26 |
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 49% of this job's working time as physical work. For 47% of the working time, a robot has been shown doing most of the task somewhere: 47% in a purpose-built cell. 0.47 of 3, the 322nd highest of the 923 jobs.
- Not physical 51%
- No robot shown 3%
- In a purpose-built cell 47%
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.
The tasks
Sorted by . 26 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Perform validations or transfers of analytical methods in accordance with applicable policies or guidelines.Done more than yearly by most who do it. Robots: in a purpose-built cell, SOTAX APW automated sample preparation workstation (with APWsoft) (sold). Anthropic's rating. | 15% | 3.1 work days6.7 h to 1.7 work weeks | Stays with people | |
| Develop and qualify new testing methods.Done more than yearly by most who do it.Robots: in a purpose-built cell, ChromSwordAuto Chromeleon Connect + Thermo Scientific Vanquish Core HPLC (switching valves, Split Sampler) (sold). Anthropic's rating. | 11% | 1.7 work weeks1.7 work days to 1.2 work months | Stays with people | |
| Conduct routine and non-routine analyses of in-process materials, raw materials, environmental samples, finished goods, or stability samples.Done daily by most who do it. Robots: in a purpose-built cell, SOTAX TPW Automated Sample Preparation Workstation (sold). Anthropic's rating. | 9% | 1.7 h25 min to 5 h | Stays with people | |
| Participate in out-of-specification and failure investigations and recommend corrective actions.Done more than monthly by most who do it. | 7% | 5 h1.7 h to 2.1 work days | 73%Half by now | |
| Supply quality control data necessary for regulatory submissions.Done daily by most who do it. | 6% | 3.3 h50 min to 1.3 work days | 80%Half by now | |
| Compile laboratory test data and perform appropriate analyses.Done daily by most who do it. AI observed on this task. | 6% | 1.3 h25 min to 3.3 h | 99%Half by now | |
| Investigate or report questionable test results.Done daily by most who do it. | 4% | 2.5 h50 min to 6.7 h | 96%Half by now | |
| Identify quality problems and recommend solutions.Done daily by most who do it. | 4% | 1.7 h38 min to 5 h | 99%Half by now | |
| Write technical reports or documentation, such as deviation reports, testing protocols, and trend analyses.Done daily by most who do it. | 4% | 3.3 h50 min to 1.3 work days | 80%Half by now | |
| Prepare or review required method transfer documentation including technical transfer protocols or reports.Done more than yearly by most who do it. | 3% | 5 h2.5 h to 1.7 work days | 92%Half by now | |
| Identify and troubleshoot equipment problems.Done daily by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 1.3 h25 min to 4.2 h | Stays with people | |
| Interpret test results, compare them to established specifications and control limits, and make recommendations on appropriateness of data for release.Done daily by most who do it. | 3% | 38 min13 min to 1.7 h | 100%Half by now |
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.
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.
- Quality Control Systems Managers72% now, 82% by 2028
- Validation Engineers49% now, 63% by 2028
- Industrial Engineers60% now, 86% by 2028
- Chemical Technicians30% now, 35% by 2028
- Calibration Technologists and Technicians37% now, 55% by 2028
- Industrial Engineering Technologists and Technicians34% now, 69% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025). Counts are for the broader BLS group this job sits in.
Questions about this job
- How much of the work of Quality Control Analysts is within reach of AI now?
- An estimated 47% of the working time is within reach of AI models now and 53% 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 Quality Control Analysts 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: Compile laboratory test data and perform appropriate analyses (99% of the task's time now); Participate in out-of-specification and failure investigations and recommend corrective actions (73% of the task's time now, 100% by the end of 2028); and Supply quality control data necessary for regulatory submissions (80% of the task's time now, 100% by the end of 2028).
- Which tasks of Quality Control Analysts stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Perform validations or transfers of analytical methods in accordance with applicable policies or guidelines; Develop and qualify new testing methods; and Conduct routine and non-routine analyses of in-process materials, raw materials, environmental samples, finished goods, or stability samples. Together such tasks are about 47% of the working time.
- Do people already use AI for the work of Quality Control Analysts?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.58% went to this job's tasks, the 45th largest share of the 447 jobs that showed up; 4 of its 26 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 10%. 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 Quality Control Analysts?
- Anthropic's robot exposure rating (September 2026) finds 49% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 47% of the working time. Its index is 0.47 of 3. One example: SOTAX APW automated sample preparation workstation (with APWsoft) for "perform validations or transfers of analytical methods in accordance with applicable policies or guidelines". 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 26 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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