Will AI replace Inspectors, Testers, Sorters, Samplers, and Weighers?

Not as a job, but it is already doing parts of the work. Across the 31 official task statements scored for Inspectors, Testers, Sorters, Samplers, and Weighers (United States, SOC 51-9061), 14% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 23 out of 100 (range 19–28, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

What should someone working in “Inspectors, Testers, Sorters, Samplers, and Weighers” do about AI?

Start from the ledger rather than the headline: 14% of this job's weighted core work is exposed, and roughly 72% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Inspectors, Testers, Sorters, Samplers, and Weighers calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 31 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Inspectors, Testers, Sorters, Samplers, and Weighers

discarding or rejecting products, materials or equipment not meeting specifications, reading dials or meters to verify that equipment is functioning at specified levels, analyzing test data and comparing colors, shapes. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: discarding or rejecting products, materials or equipment not meeting specifications is work software can't reach.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 14%
changing shape: 14%
staying human: 72%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 23 out of 100 (19–28 allowing for uncertainty): low exposure, across 31 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for inspectors, testers, sorters, samplers, and weighers is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

What shifts is reading blueprints, data, manuals or other materials to determine specifications: the paper around the work, not the work.

Your week, as this page understands it

Inspect, test, sort, sample, or weigh nonagricultural raw materials or processed, machined, fabricated, or assembled parts or products for defects, wear, and deviations from specifications. May use precision measuring instruments and complex test equipment. The job title says “inspectors”, “testers”, “sorters”, “samplers” or “weighers”: officially one job, several names. The real job is the part underneath: discarding or rejecting products, materials or equipment not meeting specifications. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But inspectors, testers, sorters, samplers, and weighers is not one task. It is 31 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is discarding or rejecting products, materials or equipment not meeting specifications, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 14%
changing shape: 14%
staying human: 72%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

5 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Reading blueprints, data, manuals or other materials to determine specifications
This is reading one thing and writing another: blueprints, data, manuals or other materials in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Read blueprints, data, manuals, or other materials to determine specifications, inspection and testing procedures, adjustment methods, certification processes, formulas, or measuring instruments required.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pulling specifications and procedures out of drawings and manuals is document reading, a real strength of software.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing test or inspection reports describing results
This is reading one thing and writing another: test in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Write test or inspection reports describing results, recommendations, or needed repairs.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing up what an inspection found is document work from results already recorded, which tools draft to a usable standard.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing test data, making computations as necessary, to determine test results
This is reading one thing and writing another: test data, making computations in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Analyze test data, making computations as necessary, to determine test results.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out results from test figures is calculation, which software does faster and more consistently than people.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Computing defect percentages or averages
This is reading one thing and writing another: defect percentages in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Compute defect percentages or averages, using formulas and calculators.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Calculating defect rates and averages from counts is exactly what software is built for.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

4 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Notifying supervisors or other personnel of production problems
The software now makes the first pass at supervisors, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Notify supervisors or other personnel of production problems.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Raising an alert about a production problem is a short message that systems can send automatically.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Recommending necessary corrective actions, based on inspection results
The software now makes the first pass at necessary corrective actions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Recommend necessary corrective actions, based on inspection results.” (O*NET task statement)
How this row was scored
Exposure score: 58 out of 100 (51–65 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Suggesting a fix from test results is a judgement software can draft, though plant-specific knowledge matters.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recording inspection or testing data
The software now makes the first pass at inspection, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Record inspection or test data, such as weights, temperatures, grades, or moisture content, and quantities inspected or graded.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Logging weights, temperatures and counts is data entry that systems can capture and store automatically.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

22 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Discarding or rejecting products, materials or equipment not meeting specifications
This work happens in the physical world: products, materials or equipment not meeting specifications, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Discard or reject products, materials, or equipment not meeting specifications.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Taking faulty items off the line is physical handling, whatever flagged them in the first place.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Inspecting, testing or measuring materials, products, installations or work for conformance to specifications
This work happens in the physical world: materials, products, installations or work, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Inspect, test, or measure materials, products, installations, or work for conformance to specifications.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Checking materials and products against a specification means handling and looking at them in person.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Measuring dimensions of products to verify conformance
This work happens in the physical world: dimensions of products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Measure dimensions of products to verify conformance to specifications, using measuring instruments, such as rulers, calipers, gauges, or micrometers.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (4–12 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Reading a caliper or micrometer means holding the part and the instrument.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.

Show the other 21 tasks

Computing usable amounts of items in shipments
shifting to AI
This is reading one thing and writing another: usable amounts of items in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Compute usable amounts of items in shipments.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Working out usable quantities from shipment figures is straightforward arithmetic for software.
The five ratings: output a model can produce 4/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Interpreting legal requirements, provide safety information or recommending compliance procedures to contractors, craft workers, engineers or property owners
changing shape
The software now makes the first pass at legal requirements, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Interpret legal requirements, provide safety information, or recommend compliance procedures to contractors, craft workers, engineers, or property owners.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Explaining what the regulations require is document work software handles well, though people want a person answering.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Checking arriving materials to ensure that they match purchase orders
staying human
This work happens in the physical world: materials, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Check arriving materials to ensure that they match purchase orders, submitting discrepancy reports as necessary.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Matching a delivery against the purchase order is document checking software does well; the goods still need looking at.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Administering tests to assess whether engineers or operators are qualified to use equipment
staying human
This work happens in the physical world: tests, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Administer tests to assess whether engineers or operators are qualified to use equipment.” (O*NET task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Written test papers can be produced and marked by software, but practical checks happen at the equipment.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Monitoring machines that automatically measure
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Monitor machines that automatically measure, sort, or inspect products.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Watching machines on the floor needs someone present, even though the readings themselves are straightforward data.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reading dials or meters to verify that equipment is functioning at specified levels
staying human
This work happens in the physical world: dials, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Read dials or meters to verify that equipment is functioning at specified levels.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Reading dials on the machines means being on the floor beside them.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Monitoring production operations or equipment to ensure conformance
staying human
This work happens in the physical world: production operations, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Monitor production operations or equipment to ensure conformance to specifications, making necessary process or assembly adjustments.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Watching the line and correcting the process means being present at the machinery.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Weighing materials, products, containers or samples to verify packaging weights or ingredient quantities
staying human
This work happens in the physical world: materials, products, containers or samples, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Weigh materials, products, containers, or samples to verify packaging weights or ingredient quantities.” (O*NET task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Weighing goods means putting them on the scale yourself.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Inspecting or testing raw materials
staying human
This work happens in the physical world: raw materials, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Inspect or test raw materials, parts, or products to determine compliance with environmental standards.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (2–16 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Environmental compliance testing means taking and handling actual materials at the site.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Collecting or selecting samples for testing or for use as models
staying human
This work happens in the physical world: samples, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect or select samples for testing or for use as models.” (O*NET task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Choosing where to sample can follow a written plan, but collecting the sample is physical.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Comparing colors, shapes, textures or grades of products or materials with color charts, templates or samples to verify conformance
staying human
This work happens in the physical world: colors, shapes, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Compare colors, shapes, textures, or grades of products or materials with color charts, templates, or samples to verify conformance to standards.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (2–10 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging colour, texture and grade against a sample relies on trained eyes and hands.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Marking items with details, such as grade or acceptance-rejection status
staying human
This work happens in the physical world: items, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Mark items with details, such as grade or acceptance-rejection status.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Marking or stamping an item is something done by hand to a real object.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Removing defects, such as chips, burrs or lap corroded or pitted surfaces
staying human
This work happens in the physical world: defects, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Remove defects, such as chips, burrs, or lap corroded or pitted surfaces.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Removing burrs and corrosion is hands-on work on the item itself.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Adjusting, cleaning or repairing products or processing equipment to correct defects found during inspections
staying human
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Adjust, clean, or repair products or processing equipment to correct defects found during inspections.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Adjusting or repairing equipment to clear a defect is done with tools in hand.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Fabricating, installing, positioning or connecting components, parts, finished products or instruments for testing or operational purposes
staying human
This work happens in the physical world: components, parts, finished products or instruments, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Fabricate, install, position, or connect components, parts, finished products, or instruments for testing or operational purposes.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Building and connecting test set-ups is physical assembly.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Grading, classifying or sorting products according to sizes, weights, colors or other specifications
staying human
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Grade, classify, or sort products according to sizes, weights, colors, or other specifications.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–7 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Sorting products by size, weight or colour means physically moving them into groups.
The five ratings: output a model can produce 1/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Making minor adjustments
staying human
This work happens in the physical world: minor adjustments, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Make minor adjustments to equipment, such as turning setscrews to calibrate instruments to required tolerances.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Turning screws to bring an instrument into tolerance is done with your hands.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Cleaning, maintaining, calibrating or repairing measuring instruments or testing equipment
staying human
This work happens in the physical world: instruments, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Clean, maintain, calibrate, or repair measuring instruments or test equipment, such as dial indicators, fixed gauges, or height gauges.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Cleaning, calibrating and repairing instruments is hands-on bench work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Positioning products, components or parts for testing
staying human
This work happens in the physical world: products, components or parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Position products, components, or parts for testing.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Placing parts into a test rig is physical handling.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Stacking or arranging tested products for further processing
staying human
This work happens in the physical world: tested products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Stack or arrange tested products for further processing, shipping, or packaging.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Stacking and arranging finished goods is manual handling.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Disassembling defective parts or components
staying human
This work happens in the physical world: defective parts, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Disassemble defective parts or components, such as inaccurate or worn gauges or measuring instruments.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Taking a worn gauge apart is manual work with tools.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.

What this job pays, and how many people do it

Median pay: $48,570a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 597,370in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: blueprints, data, manuals or other materials in, a record out. The rows above are exactly that shape: reading blueprints, data, manuals or other materials to determine specifications and writing test or inspection reports describing results. What it cannot do is be there in the room, and that is still where products, materials or equipment not meeting specifications get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

Start with what does not change: discarding or rejecting products, materials or equipment not meeting specifications is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 14% of this job's task weight sits in rows the software is already learning, 14% in rows that change shape rather than disappear, and 72% in rows it is nowhere near. That is the position, measured across 31 scored tasks. It is not a forecast about you.

So the thing worth your attention is not the job going away. It is the layer around it. Reading blueprints, data, manuals or other materials to determine specifications is the part turning into software, and being the person who understands that layer is worth money.

This week: one thing

Ask the one question. Find whoever is bringing new software into your workplace (the manager, the office, whoever runs the system) and ask them what it is meant to do to blueprints, data, manuals or other materials, and what it is not meant to touch. Ten minutes, this week, before anyone decides it for you.

What you end up holding: a straight answer about what is actually being rolled out, and when
How long it takes: ten minutes

If there’s nobody obvious to ask, or you’d rather not ask your manager: Put the same question to your union rep, your shift lead or the person who has been there longest, in person, over a break. Same ten minutes, same answer, and you will usually get a straighter one. Write down what they say. The note is the artifact, and it tells you whether products, materials or equipment not meeting specifications are in scope or not. Nothing to log into, no license needed.

Over the next 90 days

Get inside the tool rollout rather than waiting for it. Over the next ninety days, ask to be in the group that tests, checks or signs off whatever new system arrives near notifying supervisors or other personnel of production problems. It is usually an unglamorous seat that nobody fights for, and it is the one that decides how the software is used on your job rather than to it.

Over the next 12 months

On this evidence I would not retrain out of this job, and I will say that plainly rather than hedge it. The task list here is dominated by work that stays with a person. What I would do with a year is get formally recognised for the layer around it (the systems, the compliance, the planning), so you are the one who understands the software instead of the one it is done to. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to inspectors, testers, sorters, samplers, and weighers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was crushing, grinding, and polishing machine setters, operators, and tenders: only about 8% of its durable work is work you already do and there are far fewer of those jobs than of yours. And on the numbers you do not need one. This job scores 23/100 here, with only 14% of the task list in the top band, and “discard or reject products, materials, or equipment not meeting specifications” is not work that hands over cleanly. None of them beats deepening what you already have.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Crushing, Grinding, and Polishing Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already notify supervisors or other personnel of production problems, and their equivalent is to notify supervisors of needed repairs. Across both published task lists that is about 8% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 8% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 26,000 of those jobs against 597,370 of yours (OEWS May 2025), 4% as many seats.
Look at that job’s page anyway →
Machine Feeders and Offbearers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect, test, or measure materials, products, installations, or work for conformance to specifications, and their equivalent is to weigh or measure materials or products to ensure conformance to specifications. Across both published task lists that is about 7% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $41,220 against your $48,570, 15.1% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 42,330 of those jobs against 597,370 of yours (OEWS May 2025), 7% as many seats.
Look at that job’s page anyway →
Mixing and Blending Machine Setters, Operators, and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already inspect, test, or measure materials, products, installations, or work for conformance to specifications, and their equivalent is to weigh or measure materials, ingredients, or products to ensure conformance to requirements. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. And it is a narrow door: about 94,920 of those jobs against 597,370 of yours (OEWS May 2025), 16% as many seats.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 14% of its task weight, across 31 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The headlines about your trade disappearing
They are usually about the technology, not the timetable. Changes to work like discarding or rejecting products, materials or equipment not meeting specifications arrive through rules, insurance and money, slowly and visibly. This page tracks the task evidence and will move when it moves.
Retraining out of a job that is holding up
On this evidence I would not spend money leaving. Spend it on the layer around the job instead: the tools, the paperwork, the planning. That is where the change actually is.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Routine inspectors and testers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

The other groups this work is counted across:

Weighers, graders and sorters

In UK official statistics this job is counted as Routine inspectors and testers and Weighers, graders and sorters. Pay is shown separately for each of those groups (medians cannot be averaged together), while the task list and the scores on this page are for this group only.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
American Job Center locator
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
- CareerOneStop local help hub
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
CareerOneStop
Free

No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for inspectors / testers / sorters / samplers / weighers, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 14% of the work on this page is already inside what they can do.

Try The AI Authority free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for inspectors / testers / sorters / samplers / weighers. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

Noted, and thank you. We’ll email you if a Space for inspectors / testers / sorters / samplers / weighers launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

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No Space for inspectors / testers / sorters / samplers / weighers yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

Collab365 launches new communities where the need is real. If one for inspectors / testers / sorters / samplers / weighers existed, with researched problems, courses and people in the same boat, would you want in?

Your email

We use your email address for one thing: to tell you if a Space for inspectors / testers / sorters / samplers / weighers launches. We never sell it, never use it for unrelated marketing, and every email has a one-click unsubscribe. Our privacy policy has the full version.

This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Inspectors, Testers, Sorters, Samplers, and Weighers?: Not as a job, but it is already doing parts of the work. Across the 31 official task statements scored for Inspectors, Testers, Sorters, Samplers, and Weighers (United States, SOC 51-9061), 14% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 23 out of 100 (range 19–28, band: low). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Inspectors, Testers, Sorters, Samplers, and Weighers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Analyze test data, making computations as necessary, to determine test results” (93/100, very high); “Compute defect percentages or averages, using formulas and calculators” (93/100, very high); “Read blueprints, data, manuals, or other materials to determine specifications, inspection and testing procedures, adjustment methods, certification processe…” (75/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Inspectors, Testers, Sorters, Samplers, and Weighers” stay human?: About 72% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Disassemble defective parts or components, such as inaccurate or worn gauges or measuring instruments” (0/100, minimal); “Stack or arrange tested products for further processing, shipping, or packaging” (0/100, minimal); “Position products, components, or parts for testing” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Inspectors, Testers, Sorters, Samplers, and Weighers” do about AI?: Start from the ledger rather than the headline: 14% of this job's weighted core work is exposed, and roughly 72% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Inspectors, Testers, Sorters, Samplers, and Weighers calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 31 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
1 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Using these figures?

Cite this

Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.