Will AI replace Calibration Technologists and Technicians?

Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for Calibration Technologists and Technicians (United States, SOC 17-3028), 27% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 31 out of 100 (range 28–37, 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 “Calibration Technologists and Technicians” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Write and submit reports about the results of calibration tests” (81/100, very high); “Order replacement parts for malfunctioning equipment” (75/100, high); “Analyze test data to identify defects or determine calibration requirements” (66/100, 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 “Calibration Technologists and Technicians” stay human?

About 60% 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: “Verify part dimensions or clearances using precision measuring instruments to ensure conformance to specifications” (0/100, minimal); “Operate metalworking machines to fabricate housings, jigs, fittings, or fixtures” (0/100, minimal); “Maintain or repair measurement devices or equipment used for calibration 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 “Calibration Technologists and Technicians” do about AI?

Start from the ledger rather than the headline: 27% of this job's weighted core work is exposed, and roughly 60% 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 Calibration Technologists and Technicians 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 15 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

Calibration Technologists and Technicians

writing and submitting reports about the results of calibration tests, drawing plans for developing jigs and developing new calibration methods or techniques based on measurement science. If that's your week, this page is about your job.

The honest answer

AI is already taking a real slice of the routine work here: writing and submitting reports about the results of calibration tests. That is a slice of tasks, not of you.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 27%
changing shape: 13%
staying human: 60%

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

Whole-job exposure score 31 out of 100 (28–37 allowing for uncertainty): low exposure, across 15 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 calibration technologists and technicians 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.

That slice is not coming back; the core of the job, disassembling and reassembling equipment for inspection, stays yours. The tools change hands, the accountability doesn't.

Your week, as this page understands it

Execute or adapt procedures and techniques for calibrating measurement devices, by applying knowledge of measurement science, mathematics, physics, chemistry, and electronics, sometimes under the direction of engineering staff. Determine measurement standard suitability for calibrating measurement devices. May perform preventive maintenance on equipment. May perform corrective actions to address identified calibration problems. The job title says “calibration technologists” or “technicians”: officially one job, two names. The real job is the part underneath: disassembling and reassembling equipment for inspection. 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 calibration technologists and technicians is not one task. It is 15 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is disassembling and reassembling equipment for inspection, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 27%
changing shape: 13%
staying human: 60%

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.

O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
2 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

4 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.

Writing and submitting reports about the results of calibration tests
This is reading one thing and writing another: reports in, a record out. That is the shape today's tools are built for.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Write and submit reports about the results of calibration tests.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 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: Calibration reports follow a fixed format and are written from test data already recorded.
The five ratings: output a model can produce 4/4 · 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.
Ordering replacement parts for malfunctioning equipment
This is reading one thing and writing another: replacement parts in, a record out. That is the shape today's tools are built for.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Order replacement parts for malfunctioning equipment.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 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: Finding and ordering the right replacement part from a catalog is routine purchasing software handles.
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.
Analyzing test data to identify defects or determine calibration requirements
This is reading one thing and writing another: test data in, a record out. That is the shape today's tools are built for.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Analyze test data to identify defects or determine calibration requirements.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 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: Analyzing measurement data for defects and calibration needs is number work software does well.
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.
Planning sequences of calibration tests according to equipment specifications and scientific principles
This is reading one thing and writing another: sequences of calibration tests in, a record out. That is the shape today's tools are built for.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Plan sequences of calibration tests according to equipment specifications and scientific principles.” (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: Planning a test sequence from written equipment specifications is document work.
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.

Changing shape

2 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.

Reading blueprints, schematics, diagrams or technical orders
The software now makes the first pass at blueprints, schematics, diagrams or technical orders, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Read blueprints, schematics, diagrams, or technical orders.” (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: Software can read technical documents, but drawings and schematics still get misread often enough to need checking.
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.
Drawing plans for developing jigs
The software now makes the first pass at plans, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Draw plans for developing jigs, fixtures, instruments, or other devices.” (O*NET task statement)
How this row was scored
Exposure score: 50 out of 100 (43–57 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: Drawing up jigs and fixtures gets real help from design software, though the detail needs an engineer's review.
The five ratings: output a model can produce 2/4 · 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.

Staying human

9 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.

Developing new calibration methods or techniques based on measurement science
The ratings behind this row put new calibration methods well outside what today's tools can do on their own.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Develop new calibration methods or techniques based on measurement science, analyses, or calibration requirements.” (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.
The rating behind it: New calibration methods can be drafted from measurement science, but they need proving on real equipment.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Attending conferences, workshops or other training sessions to learn about new tools or methods
This work happens in the physical world: conferences, workshops or other training sessions, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Attend conferences, workshops, or other training sessions to learn about new tools or methods.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (10–18 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Learning from a conference or workshop means taking part in it yourself.
The five ratings: output a model can produce 1/4 · 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 2/4.
Calibrating devices by comparing measurements of pressure
This work happens in the physical world: devices, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Calibrate devices by comparing measurements of pressure, temperature, humidity, or other environmental conditions to known standards.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (5–13 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: Comparing an instrument against a standard means connecting them and handling both.
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.
Conducting calibration tests to determine performance or reliability
This work happens in the physical world: calibration tests, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Conduct calibration tests to determine performance or reliability of mechanical, structural, or electromechanical equipment.” (O*NET task statement)
How this row was scored
Exposure score: 9 out of 100 (5–13 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: Running a calibration test means setting up the equipment physically.
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.

Show the other 5 tasks

Visuallying inspect equipment to detect surface defects
staying human
This work happens in the physical world: inspect equipment, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Visually inspect equipment to detect surface defects.” (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: Spotting surface defects means having the equipment in front of you.
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.
Disassembling and reassembling equipment for inspection
staying human
This work happens in the physical world: equipment, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Disassemble and reassemble equipment for inspection.” (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 equipment apart and putting it back together is hand 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.
Maintaining or repairing measurement devices or equipment used for calibration testing
staying human
This work happens in the physical world: measurement devices, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Maintain or repair measurement devices or equipment used for calibration 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: Fixing measuring equipment means working on it 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 2/4.
Operating metalworking machines to fabricate housings
staying human
This work happens in the physical world: machines, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Operate metalworking machines to fabricate housings, jigs, fittings, or fixtures.” (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: Machining housings and fixtures is workshop 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.
Verifying part dimensions or clearances using precision measuring instruments to ensure conformance to specifications
staying human
This work happens in the physical world: part dimensions, in a real place. Software cannot follow it there.
importance not published
O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Verify part dimensions or clearances using precision measuring instruments to ensure conformance to 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: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Checking dimensions with precision instruments means handling the part and the gauge.
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.

What this job pays, and how many people do it

Median pay: $67,820a 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: 16,540in 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: replacement parts in, a record out. The rows above are exactly that shape: writing and submitting reports about the results of calibration tests and ordering replacement parts for malfunctioning equipment. What it cannot do is be there in the room, and that is still where equipment gets 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

Your week is splitting in two, and which half fills it is the whole question. Writing and submitting reports about the results of calibration tests is going; disassembling and reassembling equipment for inspection is not.

So, given all that: 27% of this job's task weight sits in rows the software is already learning, 13% in rows that change shape rather than disappear, and 60% in rows it is nowhere near. That is the position, measured across 15 scored tasks. It is not a forecast about you.

The occupation is an average and you are not, so the first job below is finding out where your own week actually sits.

This week: one thing

Print the task ledger above and put your own hours next to each row. Roughly, in pen, in one sitting. Then look at which group your hours actually pile up in. Twenty minutes, this week.

What you end up holding: your own week, on one page, sorted into what is shifting and what is not
How long it takes: about twenty minutes

If printing it isn’t practical: Read the rows off this page and write the same list on the back of an envelope. Same twenty minutes, same page, and it works just as well said out loud to someone who knows the job. The point is your hours next to the rows, not the paper it is on.

Over the next 90 days

Volunteer toward the durable end, visibly. Over the next ninety days put your hand up for the work in the bottom group (disassembling and reassembling equipment for inspection) and let people see you doing it. Not a new project: the same job, with your mix deliberately tilted. The point is that when the rota or the reorganisation comes, the version of you people picture is the one doing the part that stays.

Over the next 12 months

Claim a specialism at the durable end and let the other end go. Over a year, deliberately become the person who handles disassembling and reassembling equipment for inspection, and deliberately stop being the first choice for the rows in the top group. That trade costs something, because the exposed work is often the comfortable work. Decide it on purpose rather than by drift. 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 calibration technologists and technicians (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was industrial machinery mechanics: only about 13% of its durable work is work you already do. And on the numbers you do not need one. This job scores 31/100 here, with only 27% of the task list in the top band, and “attend conferences, workshops, or other training sessions to learn about new tools…” 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.

Industrial Machinery Mechanics
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already disassemble and reassemble equipment for inspection, and their equivalent is to reassemble equipment after completion of inspections, testing, or repairs. Across both published task lists that is about 13% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 13% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Electro-Mechanical and Mechatronics Technologists and Technicians
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already verify part dimensions or clearances using precision measuring instruments to ensure conformance to…, and their equivalent is to verify part dimensions or clearances to ensure conformance to specifications, using precision measuring…. Across both published task lists that is about 11% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 11% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Mobile Heavy Equipment Mechanics, Except Engines
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already order replacement parts for malfunctioning equipment, and their equivalent is to repair and replace damaged or worn parts. Across both published task lists that is about 9% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 9% 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: 27% of its task weight, across 15 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
The whole-job doom story
Nothing on this page says this job ends. It says the mix inside it moves. Half the rows above are unchanged or changing shape, and the plan is about which half your week sits in. That is a very different problem, and a solvable one.
Panic-buying a course
Do the twenty-minute sorting exercise first. Most people who buy a course before they have done it buy the wrong one, and the free services listed below will tell you the same thing without charging for it.
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 Quality assurance technicians 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:

In UK official statistics this job is counted as Quality assurance technicians, Science, engineering and production technicians n.e.c. and Engineering technicians. 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 calibration technologists / technicians, 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 27% 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 calibration technologists / technicians. 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 calibration technologists / technicians launches. Nothing else.

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No Space for calibration technologists / technicians 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 calibration technologists / technicians 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 calibration technologists / technicians 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 Calibration Technologists and Technicians?: Not as a job, but it is already doing parts of the work. Across the 15 official task statements scored for Calibration Technologists and Technicians (United States, SOC 17-3028), 27% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 31 out of 100 (range 28–37, 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 “Calibration Technologists and Technicians” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Write and submit reports about the results of calibration tests” (81/100, very high); “Order replacement parts for malfunctioning equipment” (75/100, high); “Analyze test data to identify defects or determine calibration requirements” (66/100, 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 “Calibration Technologists and Technicians” stay human?: About 60% 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: “Verify part dimensions or clearances using precision measuring instruments to ensure conformance to specifications” (0/100, minimal); “Operate metalworking machines to fabricate housings, jigs, fittings, or fixtures” (0/100, minimal); “Maintain or repair measurement devices or equipment used for calibration 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 “Calibration Technologists and Technicians” do about AI?: Start from the ledger rather than the headline: 27% of this job's weighted core work is exposed, and roughly 60% 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 Calibration Technologists and Technicians 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 15 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

About the data on this page

O*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
2 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-with-imputed)
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.