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Craft and related trades workers · code 7543

Product graders and testers (excluding foods and beverages)

A camera can spot the defect. Deciding what to do about it is still a person's job.

Analysing test data is the one task AI could take a fair chunk of. Recording results is mostly out of its reach, and measuring products and grading fibres it barely touches.

What they actually do (and what else they get called)

Product graders and testers (excluding foods and beverages) inspect, test, sort, sample and weigh raw materials, manufactured components and non-comestible goods produced or sold, to ensure compliance with quality standards, to identify defects, wear and deviations from specifications, and to grade and classify them according to their quality. Tasks include - (a) inspecting and testing products, parts and materials for conformity with specifications and standards; (b) grading and classifying natural textile fibres for spinning and winding; (c) discarding or rejecting products, materials and equipment not meeting specifications; (d) analysing and interpreting blueprints, data, manuals and other materials to determine specifications, inspection and testing procedures; (e) notifying supervisors and other personnel of production problems, and assisting in identifying and correcting these problems; (f) recording inspection or test data such as weights, temperatures, grades or moisture content, and quantities inspected or graded; (g) marking items with details such as grade and acceptance or rejection status; (h) measuring dimensions of products using instruments such as rulers, calipers, gauges or micrometers; (i) analysing test data and making computations as necessary to determine test results. Examples of the occupations classified here: - Product grader - Quality inspector - Wool classer Some related occupations classified elsewhere: - Product safety inspector - 3257 - Food grader - 7515 - Fur grader - 7531 - Pelt grader - 7535

  • non-destructive testing specialist
  • product quality controller
  • printed circuit board test technician
  • veneer grader
  • product assembly inspector
  • battery test technician
  • product grader
  • automated optical inspection operator
  • automotive test driver
  • product quality inspector
  • control panel tester

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

69 / 100

Mostly holds up against AI

AI can take a few chores off your plate, but most of the day is still yours.

Not the odds you keep your job. It's how much of the everyday work still needs a person, out of 100.

← Robot's turf Human's turf →

The ILO's official verdict: Minimal Exposure

249 of 427 for holding up against AI

Why this score?

The ILO rated each of this job's 9 tasks for how much of it AI could do. They average 30.9 out of 100, so it holds up at 100 − 30.9 = 69.1.

That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Minimal Exposure”: A few tasks are affected, but the heart of the job isn't.

This job rates 58.3 out of 100 for how hands-on it is. The score above only looks at AI tools, not robots, and for work like this robots are the bigger question.

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Man v Bot · compare

Who holds up better?

Product graders and testers (excluding foods and beverages) 69

v

Go on, try your partner's job. Or your sibling's. We won't tell.

Man v Bot

Where the bot helps, and where the human wins

Bot

What AI takes

The routine stuff. You may not miss it.

  • Analysing test data.
  • Automated visual inspection.
  • Recording and marking results.

Man

What people still do better

Judgement, trust and skilled hands. Hard to download.

  • Judging borderline cases.
  • Finding the cause of production problems.
  • Hands-on measurement and testing.

Both

What's arriving

New work that only exists because the AI does.

  • Running machine vision systems.
  • Battery and electronics testing.
  • Non-destructive testing with new sensors.

Written by a human, from the ILO's task ratings below. Yes, we see the irony. Read it as one person's take.

Meet your two rivals

They're not the same machine. AI software can only reach the parts of a job done on a screen or in words. A chatbot can't climb a ladder. A robot might, one day, if it doesn't fall off.

The AI

Lives in a screen. Never had to fix a boiler.

Threat level: Medium

37 could do without you

It could take over some of the work, and help with more. It could help with 65 of 100.

The robot

The wildcard. Has hands, still working out stairs.

How much it matters here: Some

58 how hands-on

A fair part of this job is hands-on, so robots would be needed for that part, not just software.

So could a robot do the physical part?

More fine handwork, and more time in cramped or awkward spots, than a typical hands-on job. That is exactly what machines find hardest: they do best in tidy, predictable places.

Robots hate fiddly work in awkward spaces. On that measure, this job scores 43 out of 100. The higher it is, the longer the robot waits.

58 How
hands-on
43 How fiddly
and cramped

Kind of hands-on work Hands-on, fiddly work in tight spaces

The small print

They aren't a robot score, and nothing on this page is. Nobody measures how far robots have got well enough to put a number on it. These are the closest thing we have: how hands-on the job is, and how much fiddly, cramped work it takes, which is what Frey and Osborne found hardest for machines.

From O*NET, matched to one US job .

finger skill 44.6 · hand skill 42.9 · cramped spaces 41.3 · averaged · rule: hands-on 50+ · fiddly 39.4+

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.8-observed-use measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

The job, task by task

Every job is really a bundle of tasks. Here's this one unpacked, with how much of each AI could do, out of 100. The score is the average, and averages can hide a lot.

AI's favourite task here scores 56, against an average of 31. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.

  1. 56

    Analysing test data and making computations as necessary to determine test results.

    Medium
  2. 37

    Recording inspection or test data, such as weights, temperatures, grades or moisture content, and quantities inspected or graded

    Low
  3. 32

    Analysing and interpreting blueprints, data, manuals, and other materials to determine specifications, inspection and testing procedures

    Low
  4. 32

    Marking items with details such as grade and acceptance or rejection status

    Low
  5. 28

    Discarding or rejecting products, materials and equipment not meeting specifications

    Low
  6. 28

    Notifying supervisors and other personnel of production problems, and assisting in identifying and correcting these problems

    Low
  7. 27

    Inspecting and testing products, parts and materials for conformity with specifications and standards

    Low
  8. 24

    Measuring dimensions of products using instruments such as rulers, callipers, gauges, or micrometers

    Very Low
  9. 16

    Grading and classifying natural textile fibres for spinning and winding

    Very Low

9 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use

Sidekick or replacement?

A tool that makes you faster is a very different thing from one that does the task while you watch. Jobs and Skills Australia measured the two separately, which is handy.

AI helps you
65
AI does it for you
37

Sidekick wins, by 29 points.

How good a match is this?

2 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 3633, 3999, 8393

So, should quality inspectors be worried?

Short answer: not much. Some of the chores will change, and good riddance.

Parts of it are changing. Analysing test data is rated Medium, and recording data, reading specifications, marking and rejecting items and inspecting are Low; measuring and grading fibres rate Very Low. Machine vision already handles a lot of inspection, so people handle judgement and problem-solving.

Worth remembering: we score tasks, not jobs. When AI takes on a task, the job usually reshuffles around it rather than vanishing.

Where this job could lead

None of the new jobs we've written up start from here yet. Could be you're the first. See the jobs AI is creating →

How are the neighbours doing?

There are 65 jobs in the “Craft and related trades workers” family, averaging 84. This one is below the family average.

Pit this against any other job →