Will AI replace Stockers and Order Fillers?
Most of the work in Stockers and Order Fillers still leans on things AI struggles with — research rates its theoretical AI reach at only ~18%, and real-world use lower still.
O*NET-SOC 53-7065
How your 25 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a relatively low share of this job's tasks (~18%). By late 2025, real-world AI use had reached about 0% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~18%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 25 tasks, ratedBased on real task-level AI scores — click to collapse
- Complete order receipts.
- Keep records of out-going orders.
- Keep records on the use or damage of stock or stock-handling equipment.
- Read orders to ascertain catalog numbers, sizes, colors, and quantities of merchandise.
- Take inventory or examine merchandise to identify items to be reordered or replenished.
- Design and set up advertising signs and displays of merchandise on shelves, counters, or tables to attract customers and promote sales.
- Answer customers' questions about merchandise and advise customers on merchandise selection.
- Issue or distribute materials, products, parts, and supplies to customers or coworkers, based on information from incoming requisitions.
- Stock shelves, racks, cases, bins, and tables with new or transferred merchandise.
- Operate equipment such as forklifts.
- Stamp, attach, or change price tags on merchandise, referring to price list.
- Obtain merchandise from bins or shelves.
- Receive and count stock items, and record data manually or on computer.
- Receive, unload, open, unpack, or issue sales floor merchandise.
- Pack customer purchases in bags or cartons.
- Store items in an orderly and accessible manner in warehouses, tool rooms, supply rooms, or other areas.
- Mark stock items, using identification tags, stamps, electric marking tools, or other labeling equipment.
- Pack and unpack items to be stocked on shelves in stockrooms, warehouses, or storage yards.
- Clean display cases, shelves, and aisles.
- Clean and maintain supplies, tools, equipment, and storage areas to ensure compliance with safety regulations.
- Determine proper storage methods, identification, and stock location, based on turnover, environmental factors, and physical capabilities of facilities.
- Dispose of damaged or defective items, or return them to vendors.
- Recommend disposal of excess, defective, or obsolete stock.
- Provide assistance or direction to other stockroom, warehouse, or storage yard workers.
- Examine and inspect stock items for wear or defects, reporting any damage to supervisors.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.