Will AI replace Timing Device Assemblers and Adjusters?

Not as a job, but it is already doing parts of the work. Across the 17 official task statements scored for Timing Device Assemblers and Adjusters (United States, SOC 51-2061), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 6 out of 100 (range 4–11, 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 “Timing Device Assemblers and Adjusters” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Review blueprints, sketches, or work orders to gather information about tasks to be completed” (75/100, high); “Observe operation of timepiece parts and subassemblies to determine accuracy of movement, and to diagnose causes of defects” (8/100, minimal); “Test operation and fit of timepiece parts and subassemblies, using electronic testing equipment, tweezers, watchmakers' tools, and loupes” (8/100, minimal). 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 “Timing Device Assemblers and Adjusters” stay human?

About 95% 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: “Tighten or replace loose jewels, using watchmakers' tools” (0/100, minimal); “Examine and adjust hairspring assemblies to ensure horizontal and circular alignment of hairsprings, using calipers, loupes, and watchmakers' tools” (0/100, minimal); “Bend inner coils of springs away from or toward collets, using tweezers, to locate centers of collets in centers of springs, and to correct errors resulting…” (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 “Timing Device Assemblers and Adjusters” do about AI?

Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 95% 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 Timing Device Assemblers and Adjusters 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 17 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

Timing Device Assemblers and Adjusters

changing timing weights on balance wheels to correct deficient timing, mounting hairsprings and balancing wheel assemblies between jaws of truing calipers and replacing specified parts to repair malfunctioning timepieces. If that's your week, this page is about your job.

The honest answer

AI changes the edges of this job, not the middle: observing operation of timepiece parts and subassemblies to determine accuracy of movement 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: 5%
changing shape: 0%
staying human: 95%

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

Whole-job exposure score 6 out of 100 (4–11 allowing for uncertainty): minimal exposure, across 17 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 timing device assemblers and adjusters 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 reviewing blueprints, sketches or work orders to gather information about tasks: the overhead at the edges, not the middle you trained for.

Your week, as this page understands it

Perform precision assembling or adjusting, within narrow tolerances, of timing devices such as digital clocks or timing devices with electrical or electronic components. The job title says “timing device assemblers” or “adjusters”: officially one job, two names. The real job is the part underneath: observing operation of timepiece parts and subassemblies to determine accuracy of movement. 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 timing device assemblers and adjusters is not one task. It is 17 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is observing operation of timepiece parts and subassemblies to determine accuracy of movement, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 5%
changing shape: 0%
staying human: 95%

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.

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.

Reviewing blueprints, sketches or work orders to gather information about tasks
This is reading one thing and writing another: blueprints, sketches or work orders in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Review blueprints, sketches, or work orders to gather information about tasks to be completed.” (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 the needed details out of work orders, sketches and blueprints is document reading 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 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

0 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.

Nothing in this job’s scored task list landed in this group. That is the measurement, not an editorial choice, and it is worth knowing either way.

Staying human

16 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.

Observing operation of timepiece parts and subassemblies to determine accuracy of movement
This work happens in the physical world: operation of timepiece parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Observe operation of timepiece parts and subassemblies to determine accuracy of movement, and to diagnose causes of defects.” (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: Data can hint at a fault, but watching a movement run and spotting what is wrong needs eyes and hands on it.
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.
Testing operation and fit of timepiece parts and subassemblies
This work happens in the physical world: operation, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Test operation and fit of timepiece parts and subassemblies, using electronic testing equipment, tweezers, watchmakers' tools, and loupes.” (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: Test equipment gives readings, but setting the piece up and checking the fit is done at the bench.
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.
Replacing specified parts to repair malfunctioning timepieces
This work happens in the physical world: specified parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Replace specified parts to repair malfunctioning timepieces, using watchmakers' tools, loupes, and holding 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: Swapping out a faulty part inside a watch is fine handwork with tweezers and a loupe.
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.
Disassembling timepieces, watches, clocks and chronometers so that repairs can be made
This work happens in the physical world: timepieces, watches, clocks and chronometers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Disassemble timepieces such as watches, clocks, and chronometers so that repairs can be made.” (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 watch or clock apart without damaging it is skilled handwork.
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.
Examining components of timepieces, watches, clocks or chronometers for defects, using loupes or microscopes
This work happens in the physical world: components of timepieces, watches, clocks or chronometers, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Examine components of timepieces such as watches, clocks, or chronometers for defects, using loupes or microscopes.” (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: Image analysis can flag defects, but the part still has to be placed under the loupe or microscope by hand.
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.
Assembling and installing components of timepieces to complete mechanisms
This work happens in the physical world: components of timepieces, in a real place. Software cannot follow it there.
importance 5 · Core
Source: “Assemble and install components of timepieces to complete mechanisms, using watchmakers' tools and loupes.” (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: Fitting tiny watch parts together under a loupe is precise handwork at the bench.
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 and lubricating timepiece parts and assemblies
This work happens in the physical world: timepiece parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Clean and lubricate timepiece parts and assemblies, using solvents, buff sticks, and oil.” (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 oiling watch parts is close physical work with solvents and 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.
Adjusting sizes or positioning of timepiece parts to achieve specified fit or function
This work happens in the physical world: sizes, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Adjust sizes or positioning of timepiece parts to achieve specified fit or function, using calipers, fixtures, and loupes.” (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 the size and position of tiny parts with calipers and fixtures is precise handwork.
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.
Bending inner coils of springs away from or toward collets
This work happens in the physical world: inner coils of springs away, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Bend inner coils of springs away from or toward collets, using tweezers, to locate centers of collets in centers of springs, and to correct errors resulting from faulty colleting of coils.” (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: Bending inner coils with tweezers to center a spring is delicate handwork.
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.

Show the other 7 tasks

Estimating spaces between collets and first inner coils to determine if spaces are within acceptable limits
staying human
This work happens in the physical world: spaces, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Estimate spaces between collets and first inner coils to determine if spaces are within acceptable limits.” (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: The acceptable limits are written down, but judging the gap under magnification is done by eye at the bench.
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.
Turning wheels of calipers and examining springs
staying human
This work happens in the physical world: wheels of calipers, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Turn wheels of calipers and examine springs, using loupes, to determine if center coils appear as perfect circles.” (O*NET task statement)
How this row was scored
Exposure score: 6 out of 100 (0–13 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Turning the calipers and judging whether the coils run true is a look-and-feel check at the bench.
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.
Bending parts, such as hairsprings, pallets, barrel covers and bridges
staying human
This work happens in the physical world: parts, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Bend parts, such as hairsprings, pallets, barrel covers, and bridges, to correct deficiencies in truing or endshake, using tweezers.” (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: Bending a hairspring or bridge with tweezers to correct it is delicate handwork.
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.
Changing timing weights on balance wheels to correct deficient timing
staying human
This work happens in the physical world: weights, in a real place. Software cannot follow it there.
importance 5 · Supplemental
Source: “Change timing weights on balance wheels to correct deficient timing.” (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: Changing timing weights on a balance wheel is done with tools at the bench.
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.
Mounting hairsprings and balancing wheel assemblies between jaws of truing calipers
staying human
This work happens in the physical world: hairsprings, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Mount hairsprings and balance wheel assemblies between jaws of truing 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: work that happens in the physical world.
The rating behind it: Mounting a hairspring and balance wheel in truing calipers is fine manual 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 1/4.
Examining and adjusting hairspring assemblies to ensure horizontal and circular alignment of hairsprings
staying human
This work happens in the physical world: assemblies, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Examine and adjust hairspring assemblies to ensure horizontal and circular alignment of hairsprings, using calipers, loupes, and watchmakers' tools.” (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: Checking and truing a hairspring assembly is fine handwork under magnification.
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.
Tightening or replacing loose jewels
staying human
This work happens in the physical world: loose jewels, in a real place. Software cannot follow it there.
importance 4 · Supplemental
Source: “Tighten or replace loose jewels, using watchmakers' tools.” (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: Tightening or replacing a loose jewel is precise work with watchmakers’ 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: $62,620a 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: 250in 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, sketches or work orders in, a record out. The rows above are exactly that shape: reviewing blueprints, sketches or work orders to gather information about tasks. What it cannot do is be there in the room, and that is still where operation of timepiece parts 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

Start with what does not change: observing operation of timepiece parts and subassemblies to determine accuracy of movement is the middle of this job, and the evidence on this page says it stays with a person.

So, given all that: 5% of this job's task weight sits in rows the software is already learning, 0% in rows that change shape rather than disappear, and 95% in rows it is nowhere near. That is the position, measured across 17 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. Reviewing blueprints, sketches or work orders to gather information about tasks 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, sketches or work orders, 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 operation of timepiece parts is 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 observing operation of timepiece parts and subassemblies to determine accuracy of movement. 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 timing device assemblers and adjusters (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was watch and clock repairers: only about 8% of its durable work is work you already do. And on the numbers you do not need one. This job scores 6/100 here, with only 5% of the task list in the top band, and “observe operation of timepiece parts and subassemblies to determine accuracy of movement…” 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.

Watch and Clock Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already disassemble timepieces such as watches, clocks, and chronometers so that repairs can be…, and their equivalent is to perform regular adjustment and maintenance on timepieces, watch cases, and watch bands. 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.
Look at that job’s page anyway →
Electric Motor, Power Tool, and Related Repairers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already clean and lubricate timepiece parts and assemblies, using solvents, buff sticks, and oil, and their equivalent is to scrape and clean units or parts, using cleaning solvents and equipment. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $56,210 against your $62,620, 10.2% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Aircraft Structure, Surfaces, Rigging, and Systems Assemblers
Why it looked obvious: It came up as a near neighbour on the overall shape of the two task lists, but nothing in your day matched a specific piece of theirs closely enough to name.
Why I am not recommending it: The two task lists look alike from a distance and share almost nothing close up: no single piece of their work matched a piece of yours. That is a resemblance, not a route.
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: 5% of its task weight, across 17 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 observing operation of timepiece parts and subassemblies to determine accuracy of movement 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 Assemblers (electrical and electronic products) 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:

Precision instrument makers and repairers

In UK official statistics this job is counted as Assemblers (electrical and electronic products) and Precision instrument makers and repairers. 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 timing device assemblers / adjusters, 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 5% 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 timing device assemblers / adjusters. 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 timing device assemblers / adjusters 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 timing device assemblers / adjusters 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.

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Questions people ask about this job

Will AI replace Timing Device Assemblers and Adjusters?: Not as a job, but it is already doing parts of the work. Across the 17 official task statements scored for Timing Device Assemblers and Adjusters (United States, SOC 51-2061), 5% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 6 out of 100 (range 4–11, 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 “Timing Device Assemblers and Adjusters” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Review blueprints, sketches, or work orders to gather information about tasks to be completed” (75/100, high); “Observe operation of timepiece parts and subassemblies to determine accuracy of movement, and to diagnose causes of defects” (8/100, minimal); “Test operation and fit of timepiece parts and subassemblies, using electronic testing equipment, tweezers, watchmakers' tools, and loupes” (8/100, minimal). 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 “Timing Device Assemblers and Adjusters” stay human?: About 95% 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: “Tighten or replace loose jewels, using watchmakers' tools” (0/100, minimal); “Examine and adjust hairspring assemblies to ensure horizontal and circular alignment of hairsprings, using calipers, loupes, and watchmakers' tools” (0/100, minimal); “Bend inner coils of springs away from or toward collets, using tweezers, to locate centers of collets in centers of springs, and to correct errors resulting…” (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 “Timing Device Assemblers and Adjusters” do about AI?: Start from the ledger rather than the headline: 5% of this job's weighted core work is exposed, and roughly 95% 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 Timing Device Assemblers and Adjusters 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 17 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.
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.