Will AI replace Weighers, Measurers, Checkers, and Samplers, Recordkeeping?

Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Weighers, Measurers, Checkers, and Samplers, Recordkeeping (United States, SOC 43-5111), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 19 out of 100 (range 15–25, band: minimal). 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 “Weighers, Measurers, Checkers, and Samplers, Recordkeeping” do about AI?

Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 76% 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 Weighers, Measurers, Checkers, and Samplers, Recordkeeping 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 18 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

Weighers, Measurers, Checkers, and Samplers, Recordkeeping

comparing product labels, tags or tickets, removing from stock products or loads not meeting quality standards, signaling or instructing other workers and communicating with customers and vendors to exchange information regarding products. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: weighing or measuring materials, equipment or products to maintain relevant records 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: 4%
changing shape: 20%
staying human: 76%

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

Whole-job exposure score 19 out of 100 (15–25 allowing for uncertainty): minimal exposure, across 18 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 weighers, measurers, checkers, and samplers, recordkeeping 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 2026-08-05. Read the full method.

What shifts is communicating with customers and vendors to exchange information regarding products: the paper around the work, not the work.

Your week, as this page understands it

Weigh, measure, and check materials, supplies, and equipment for the purpose of keeping relevant records. Duties are primarily clerical by nature. Includes workers who collect and keep record of samples of products or materials. The job title says “weighers”, “measurers”, “checkers”, “samplers” or “recordkeeping”: officially one job, several names. The real job is the part underneath: weighing or measuring materials, equipment or products to maintain relevant records, using volume meters, scales, rules or calipers. 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 weighers, measurers, checkers, and samplers, recordkeeping is not one task. It is 18 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is weighing or measuring materials, equipment or products to maintain relevant records, using volume meters, scales, rules or calipers, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 4%
changing shape: 20%
staying human: 76%

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 2026-08-05. 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

1 task

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.

Communicating with customers and vendors to exchange information regarding products
This is reading one thing and writing another: customers in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Communicate with customers and vendors to exchange information regarding products, materials, and services.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 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: Routine emails and calls about products and orders are the kind of exchange AI drafts and answers well.
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 1/4 · how much data exists 3/4.

Changing shape

3 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.

Documenting quantity, quality, type, weight
The software now makes the first pass at quantity, quality, type, weight, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Document quantity, quality, type, weight, test result data, and value of materials or products to maintain shipping, receiving, and production records and files.” (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 quantities, weights and test results into records is structured data work software handles reliably.
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.
Comparing product labels, tags or tickets, shipping manifests, purchase orders and bills of lading to verify accuracy of shipment contents, quality specifications or weights
The software now makes the first pass at product labels, tags or tickets, shipping manifests, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Compare product labels, tags, or tickets, shipping manifests, purchase orders, and bills of lading to verify accuracy of shipment contents, quality specifications, or weights.” (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: 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 tickets, manifests and purchase orders is classic document checking, though paperwork and goods sit at the dock.
The five ratings: output a model can produce 4/4 · 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.
Inspecting products and examination records to determine the number of defects per worker and the reasons for examiners' rejections
The software now makes the first pass at products, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Inspect products and examination records to determine the number of defects per worker and the reasons for examiners' rejections.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial 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: Counting defects per worker and finding patterns in rejection records is straightforward data analysis.
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

14 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.

Weighing or measuring materials, equipment or products to maintain relevant records
This work happens in the physical world: materials, equipment or products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Weigh or measure materials, equipment, or products to maintain relevant records, using volume meters, scales, rules, or calipers.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Putting material on a scale or a caliper on a part 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 3/4.
Signaling or instructing other workers
This work happens in the physical world: other workers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Signal or instruct other workers to weigh, move, or check products.” (O*NET task statement)
How this row was scored
Exposure score: 11 out of 100 (4–18 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Directing coworkers on the floor happens where the goods are, in the moment.
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 1/4 · how much data exists 2/4.
Examining products or materials, parts, subassemblies and packaging for damage, defects or shortages
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine products or materials, parts, subassemblies, and packaging for damage, defects, or shortages, using specification sheets, gauges, and standards charts.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Spotting damage and shortages means handling the goods and gauges, even though the specifications are written down.
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 2/4.
Collecting or preparing measurement, weight or identification labels and attaching them to products
This work happens in the physical world: measurement, weight or identification labels and attaching them, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect or prepare measurement, weight, or identification labels and attach them to products.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 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: The label content is easy to generate, but someone has to physically attach it to the product.
The five ratings: output a model can produce 3/4 · 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.
Collecting product samples and preparing them for laboratory analysis or testing
This work happens in the physical world: product samples, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Collect product samples and prepare them for laboratory analysis or 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: Taking and preparing physical samples is hands-on work at the material.
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.
Maintaining, monitoring and cleaning work areas, such as recycling collection sites, drop boxes
This work happens in the physical world: work areas, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Maintain, monitor, and clean work areas, such as recycling collection sites, drop boxes, counters and windows, and areas around scale houses.” (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 and tidying the scale house and collection areas is physical work on site.
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.

Show the other 8 tasks

Operating scalehouse computers to obtain weight information about incoming shipments
staying human
This work happens in the physical world: scalehouse computers, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Operate scalehouse computers to obtain weight information about incoming shipments such as those from waste haulers.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 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: The weighing computer does the work, but someone sits in the scale house dealing with arriving trucks.
The five ratings: output a model can produce 4/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Storing samples of finished products in labeled cartons and recording their location
staying human
This work happens in the physical world: samples of finished products, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Store samples of finished products in labeled cartons and record their location.” (O*NET task statement)
How this row was scored
Exposure score: 19 out of 100 (12–26 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: Recording where a sample went is simple, but boxing and shelving it is physical handling.
The five ratings: output a model can produce 3/4 · 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.
Counting or estimating quantities of materials
staying human
This work happens in the physical world: quantities of materials, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Count or estimate quantities of materials, parts, or products received or shipped.” (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: Counting or estimating goods requires being at the pallet, even though the arithmetic is trivial.
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.
Removing from stock products or loads not meeting quality standards
staying human
This work happens in the physical world: stock products, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Remove from stock products or loads not meeting quality standards, and notify supervisors or appropriate departments of discrepancies or shortages.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 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: Flagging a discrepancy is easy to write up, but pulling bad stock off the line is physical work.
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 1/4 · how much data exists 3/4.
Unloading or unpacking incoming shipments
staying human
This work happens in the physical world: shipments, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Unload or unpack incoming shipments.” (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: Unloading and unpacking shipments is manual work at the loading bay.
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.
Filling orders for products and samples
staying human
This work happens in the physical world: orders, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Fill orders for products and samples, following order tickets, and forward or mail items.” (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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Picking items and getting them into the post is physical order fulfillment.
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 3/4.
Sorting products or materials into predetermined sequences or groupings
staying human
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Sort products or materials into predetermined sequences or groupings for display, packing, shipping, or storage.” (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: Sorting physical items into groups 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 2/4.
Transporting materials, products or samples to processing, shipping or storage areas
staying human
This work happens in the physical world: materials, products or samples, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Transport materials, products, or samples to processing, shipping, or storage areas, manually or using conveyors, pumps, or hand trucks.” (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: Moving materials around the site is physical transport.
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.

What this job pays, and how many people do it

Median pay: $46,380a 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: 53,300in 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: quantity, quality, type, weight in, a record out. The rows above are exactly that shape: communicating with customers and vendors to exchange information regarding products and documenting quantity, quality, type, weight. What it cannot do is be there in the room, and that is still where materials, equipment or products 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: weighing or measuring materials, equipment or products to maintain relevant records is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 4% of this job's task weight sits in rows the software is already learning, 20% in rows that change shape rather than disappear, and 76% in rows it is nowhere near. That is the position, measured across 18 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. Communicating with customers and vendors to exchange information regarding products 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 quantity, quality, type, weight, 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 materials, equipment or products 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 documenting quantity, quality, type, weight. 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 weighers, measurers, checkers, and samplers, recordkeeping (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was furnace, kiln, oven, drier, and kettle operators and tenders: only about 7% of its durable work is work you already do. And on the numbers you do not need one. This job scores 19/100 here, with only 4% of the task list in the top band, and “weigh or measure materials, equipment, or products to maintain relevant records, using…” 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.

Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already collect product samples and prepare them for laboratory analysis or testing, and their equivalent is to examine or test samples of processed substances, or collect samples for laboratory testing…. 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.
Look at that job’s page anyway →
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 collect product samples and prepare them for laboratory analysis or testing, and their equivalent is to collect samples of materials or products for laboratory testing. 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.
Look at that job’s page anyway →
Shipping, Receiving, and Inventory Clerks
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already compare product labels, tags, or tickets, shipping manifests, purchase orders, and bills of…, and their equivalent is to examine shipment contents and compare with records. 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.
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: 4% of its task weight, across 18 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 weighing or measuring materials, equipment or products to maintain relevant records 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 Stock control clerks and assistants 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

In UK official statistics this job is counted as Stock control clerks and assistants. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

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

Why there is no community here

Collab365, who build this site, run paid Spaces for a small number of subjects, and none of them is built for this job. We are not going to point you at the nearest one and call it a fit.

So the free services listed on this page are the whole answer, and it is the same answer we would give a friend.

Noted, and thank you. We’ll email you if a Space for weighers / measurers / checkers / samplers / recordkeeping launches. Nothing else.

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No Space for weighers / measurers / checkers / samplers / recordkeeping 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 weighers / measurers / checkers / samplers / recordkeeping existed, with researched problems, courses and people in the same boat, would you want in?

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Questions people ask about this job

Will AI replace Weighers, Measurers, Checkers, and Samplers, Recordkeeping?: Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Weighers, Measurers, Checkers, and Samplers, Recordkeeping (United States, SOC 43-5111), 4% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 19 out of 100 (range 15–25, band: minimal). 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 “Weighers, Measurers, Checkers, and Samplers, Recordkeeping” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Communicate with customers and vendors to exchange information regarding products, materials, and services” (64/100, high); “Document quantity, quality, type, weight, test result data, and value of materials or products to maintain shipping, receiving, and production records and files” (56/100, partial); “Inspect products and examination records to determine the number of defects per worker and the reasons for examiners' rejections” (56/100, partial). 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 “Weighers, Measurers, Checkers, and Samplers, Recordkeeping” stay human?: About 76% 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: “Transport materials, products, or samples to processing, shipping, or storage areas, manually or using conveyors, pumps, or hand trucks” (0/100, minimal); “Maintain, monitor, and clean work areas, such as recycling collection sites, drop boxes, counters and windows, and areas around scale houses” (0/100, minimal); “Sort products or materials into predetermined sequences or groupings for display, packing, shipping, or storage” (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 “Weighers, Measurers, Checkers, and Samplers, Recordkeeping” do about AI?: Start from the ledger rather than the headline: 4% of this job's weighted core work is exposed, and roughly 76% 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 Weighers, Measurers, Checkers, and Samplers, Recordkeeping 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 18 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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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.