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STRATUSWORKFORCE SCAN

Validation Engineers

In short: today's best AI models could do about 49% 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 63% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 37% of the time, stays with people.

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Design or plan protocols for equipment or processes to produce products meeting internal and external purity, safety, and quality requirements.

$102,440 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 on20 h
  • A person checks AI's work0 h
  • Desk work AI can't do yet5 h
  • Stays with people15 h

Validation Engineers, now: of a 40-hour week, AI could take on 20 hours, 0 hours become checking its work, 5 hours are desk work it can't do yet, and 15 hours stay with people.

The largest pieces: Study product characteristics or customer requirements to determine validation objectives and standards (about 3 h); Develop validation master plans, process flow diagrams, test cases, or standard operating procedures (about 3 h); Analyze validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems (about 3 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.

now
49%

of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

Kinds of work
  • 63%
  • 5%
  • 31%
4%

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.

Half the desk work within reach
Already

On the chosen pace and reliability. Estimate.

Share of the working time within reach, now to 2030

0%25%50%75%100%2027202820292030NowDesk work: 63% of the time
Chosen to Ceiling: the share
DateNow
NowEnd of 2030
Change 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, 8%. Today's estimate: 49%.

0%25%50%2023202420252026GPT-4, March 2023: 0% within reachGPT-4 Turbo (Nov 2023), November 2023: 0% within reachGPT-4o, May 2024: 0% within reachClaude 3.5 Sonnet (June 2024), June 2024: 0% within reacho1-preview, September 2024: 0% within reachClaude 3.5 Sonnet (Oct 2024), October 2024: 0% within reacho1, December 2024: 0% within reachClaude 3.7 Sonnet, February 2025: 0% within reacho3, April 2025: 0% within reachGPT-5, August 2025: 0% within reachGemini 3 Pro, November 2025: 0% within reachClaude Opus 4.5, November 2025: 0% within reachGPT-5.2, December 2025: 1% within reachClaude Opus 4.6, February 2026: 1% within reachClaude Mythos Preview (early), April 2026: 8% within reachToday (estimate), November 2026: 49% within reach
Each step is a new best model measured by METR, four in five; the dashed end is today's estimate. Point at a dot for the model.

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, 0.021% went to this job's tasks in May 2026, the 329th largest of the 447 jobs that showed up at all; 2 of its 21 tasks showed up. Within each of Anthropic's methods, never across a change: 0.032% to 0.021% (released February and March 2025); 0.012% to 0.0054% (August 2025 to February 2026); 0.034% to 0.021% (April to May 2026).

0%0.025%0.05%20252026released February 2025: 0.032%released March 2025: 0.021%the week of Aug 4, 2025: 0.012%the week of Nov 13, 2025: 0.0057%the week of Feb 5, 2026: 0.0054%April 2026: 0.034%May 2026: 0.021%
Each dot is one release's sample. A line joins releases made by the same method; a change of method starts a new line. Point at a dot for its window.
Each release
ConversationsShareRankTasks seen
Released February 20250.032%353 of 7081 of 21
Released March 20250.021%414 of 7032 of 21
The week of Aug 4, 20250.012%439 of 6551 of 21
The week of Nov 13, 20250.0057%562 of 6721 of 21
The week of Feb 5, 20260.0054%565 of 6772 of 21
April 20260.034%282 of 4342 of 21
May 20260.021%329 of 4472 of 21

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 18% of this job's working time as physical work. For 18% of the working time, a robot has been shown doing most of the task somewhere: 18% in a purpose-built cell. 0.18 of 3, the 452nd highest of the 923 jobs.

  • Not physical 82%
  • In a purpose-built cell 18%

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 . 21 tasks from .

TaskKind
Validate or characterize sustainable or environmentally friendly products, using electronic testing platforms.Done more than yearly by most who do it. 14%1.7 work days3.3 h to 4.2 work daysStays with people
Develop validation master plans, process flow diagrams, test cases, or standard operating procedures.Done more than yearly by most who do it. 13%1.3 work days3.3 h to 3.1 work days52%Half by now
Conduct audits of validation or performance qualification processes to ensure compliance with internal or regulatory requirements.Done more than yearly by most who do it. 8%1.3 work days3.3 h to 3.1 work daysStays with people
Analyze validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems.Done more than weekly by most who do it. 8%5 h1.7 h to 1.7 work days80%Half by now
Design validation study features, such as sampling, testing, or analytical methodologies.Done more than monthly by most who do it. 8%1 work day3.3 h to 2.6 work days68%Half by now
Study product characteristics or customer requirements to determine validation objectives and standards.Done more than monthly by most who do it. 7%3.3 h1.7 h to 6.7 h100%Half by now
Prepare detailed reports or design statements, based on results of validation and qualification tests or reviews of procedures and protocols.Done more than yearly by most who do it. 7%6.7 h2.5 h to 2.1 work days76%Half by now
Conduct validation or qualification tests of new or existing processes, equipment, or software in accordance with internal protocols or external standards.Done more than yearly by most who do it. Robots: in a purpose-built cell, Instron AT6 Automated Testing System (sold). Anthropic's rating.6%6.7 h2.5 h to 2.5 work daysStays with people
Direct validation activities, such as protocol creation or testing.Done more than yearly by most who do it. 5%6.7 h1.7 h to 2.1 work daysStays with people
Recommend resolution of identified deviations from established product or process standards.Done more than monthly by most who do it. 5%3.3 h1.3 h to 1.3 work days91%Half by now
Participate in internal or external training programs to maintain knowledge of validation principles, industry trends, or novel technologies.Done more than yearly by most who do it. 5%3.3 h50 min to 6.7 h91%Half by now
Prepare, maintain, or review validation and compliance documentation, such as engineering change notices, schematics, or protocols.Done more than monthly by most who do it. 4%3.3 h1.3 h to 1.3 work days91%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.

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 Validation Engineers is within reach of AI now?
An estimated 49% of the working time is within reach of AI models now and 63% 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 Validation Engineers 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: Study product characteristics or customer requirements to determine validation objectives and standards (100% of the task's time now); Develop validation master plans, process flow diagrams, test cases, or standard operating procedures (52% of the task's time now, 100% by the end of 2028); and Analyze validation test data to determine whether systems or processes have met validation criteria or to identify root causes of production problems (80% of the task's time now, 100% by the end of 2028).
Which tasks of Validation Engineers stay with people?
Tasks that are people work or body work are not counted as within reach at any date. The largest: Validate or characterize sustainable or environmentally friendly products, using electronic testing platforms; Conduct audits of validation or performance qualification processes to ensure compliance with internal or regulatory requirements; and Conduct validation or qualification tests of new or existing processes, equipment, or software in accordance with internal protocols or external standards. Together such tasks are about 37% of the working time.
Do people already use AI for the work of Validation Engineers?
In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 329th largest share of the 447 jobs that showed up; 2 of its 21 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 4%. 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 Validation Engineers?
Anthropic's robot exposure rating (September 2026) finds 18% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 18% of the working time. Its index is 0.18 of 3. One example: Instron AT6 Automated Testing System for "conduct validation or qualification tests of new or existing processes, equipment, or software in accordance with internal protocols or external standards". 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 21 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.

How the estimates are made

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