Elementary occupations · code 9334
Shelf fillers
An app can tell customers which aisle. Keeping the shelves full is still legwork.
Pointing customers the right way and noting what needs restocking are mostly out of AI's reach. Filling shelves and clearing out-of-date stock it barely touches.
What they actually do (and what else they get called)
Shelf fillers stock shelves and display areas and keep stock clean and in order in supermarkets and other retail and wholesale shops. Tasks include - (a) placing goods neatly in bins and on racks, and stacking bulky goods on floors; (b) filling shelves with goods and ensuring that goods with the earliest use-by dates are at the front of shelves; (c) removing goods with past due use-by dates; (d) maintaining shelf order by removing stock belonging in a different location; (e) noting what has been sold and collecting goods needed from the stockroom; (f) obtaining articles for customers from shelf or stockroom; (g) directing customers to location of articles sought; (h) receiving, opening, unpacking and inspecting for damage merchandise from manufacturer or distributor. Examples of the occupations classified here: - Night filler - Stock filler - Stock handler
- shelf filler
Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.
80 / 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.
The ILO's official verdict: Not Exposed
149 of 427 for holding up against AI
Not quite your week? Make it yours ↓
Why this score?
The ILO rated each of this job's 8 tasks for how much of it AI could do. They average 20.5 out of 100, so it holds up at 100 − 20.5 = 79.5.
That's the whole sum. No black box, no secret sauce: you can check it against the ILO's study. ILO group “Not Exposed”: None of this job's tasks scored high enough to count.
from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.8-observed-use
Pinch of salt: this number is probably too rosy
It only asks what AI software could do, and this job is 56 out of 100 hands-on. A chatbot can't do that part. A robot might, one day, and nobody measures how close that is.
Man v Bot · compare
Who holds up better?
Shelf fillers 80
vGo 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.
- Tracking stock automatically at the till.
- Store maps and product finders.
- Shelf-scanning cameras and robots.
Man
What people still do better
Judgement, trust and skilled hands. Hard to download.
- Stacking and rotating stock.
- Unpacking and checking deliveries.
- Helping customers in person.
Both
What's arriving
New work that only exists because the AI does.
- Picking online orders in store.
- Electronic shelf labels.
- Working alongside shelf-scanning robots.
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: Low
22 could do without you
It could take over very little of the work on its own. It could help with 47 of 100.
The robot
The wildcard. Has hands, still working out stairs.
How much it matters here: Some
56 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?
Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.
Robots hate fiddly work in awkward spaces. On that measure, this job scores 34 out of 100. The higher it is, the longer the robot waits.
hands-on
and cramped
Kind of hands-on work Hands-on, less fiddly work
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 34 · hand skill 41.1 · cramped spaces 25.5 · averaged · rule: hands-on 50+ · fiddly under 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 44, against an average of 21. The bigger the gap, the more lopsided the job: some of it wide open to AI, some of it barely touched.
- 44
Directing customers to location of articles sought
Low - 27
Noting what has been sold and collecting goods needed from the stockroom
Low - 17
Placing goods neatly in bins and on racks, and stacking bulky goods on floors
Very Low - 16
Obtaining articles for customers from shelf or stockroom
Very Low - 15
Maintaining shelf order by removing stock belonging in a different location
Very Low - 15
Receiving, opening, unpacking, and inspecting for damage merchandise from manufacturer or distributor.
Very Low - 15
Filling shelves with goods ensuring goods with the earliest use-by dates are at the front of shelves
Very Low - 15
Removing goods with past due use-by dates
Very Low
8 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
New · the weekly task audit
Your week, your score
The score above assumes shelf fillers spend the same time on every task. You don't. Slide each task to how much of your week it takes, and we'll re-weight the same ILO ratings to fit your job.
- Some
- Some
- Some
- Some
- Some
- Some
- Some
- Some
Your score
80 / 100
Same as the job as a whole, so far.
Move the sliders to make it yours.
The job as a whole: 80 / 100
Link copied.
Nothing you enter leaves your browser. The link just carries your slider positions.
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
- 47
- AI does it for you
- 22
Sidekick wins, by 25 points.
How good a match is this?
One Australian job matches this one closely, so this is about as reliable as it gets here.
estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.8-observed-use matched to Australian jobs 8912
Meanwhile, in real life…
Everything else here is about what AI could do. This is what people actually did. When they asked Claude for help with this kind of work, did they hand the whole task over, or roll their sleeves up and work through it together?
Tiny sample alert This job makes up 0.06% of all the conversations: a tiny slice, mostly the paperwork rather than the work. People using AI for a job isn't the same as AI being able to do it.
Out of every 100 conversations
worked through it together handed it over
The small print
Anthropic publishes this about its own product, and it doesn't feed into any score here. These are people who use Claude, not workers in general, so little use here doesn't mean AI can't reach the job.
These two add up to 100. The bars elsewhere on the page don't, because each is scored on its own, so we don't put them side by side.
observed use Anthropic Economic Index release 2026-06-26, period beginning 2026-05-01 data 0.8-observed-use 2026-05-01 · Anthropic, about its own product
So, should shelf fillers be worried?
Short answer: not much. Some of the chores will change, and good riddance.
Somewhat. Directing customers and noting what's sold are the most exposed tasks, both Low; stacking, rotating and unpacking stock rate Very Low. Stock systems and shelf-scanning robots are arriving in some stores, but restocking is still mostly done by people.
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 33 jobs in the “Elementary occupations” family, averaging 85. This one is below the family average.
- Vehicle cleaners 91
- Water and firewood collectors 91
- Crop farm labourers 91
- Garbage and recycling collectors 91
- Civil engineering labourers 91
- Forestry labourers 91
- Building construction labourers 91
- Sweepers and related labourers 91
- Other cleaning workers 90
- Mining and quarrying labourers 89
- Odd job persons 89
- Window cleaners 89
- Fishery and aquaculture labourers 89
- Mixed crop and livestock farm laboure… 89
- Garden and horticultural labourers 88
- Cleaners and helpers in offices, hote… 88
- Livestock farm labourers 88
- Manufacturing labourers not elsewhere… 88
- Kitchen helpers 87
- Drivers of animal-drawn vehicles and … 87
- Freight handlers 86
- Domestic cleaners and helpers 86
- Hand launderers and pressers 86
- Street and related service workers 82
- Refuse sorters 82
- Fast food preparers 82
- Hand packers 80
- Street vendors (excluding food) 80