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# Will stockers be replaced by AI?

Updated October 2026

Stockers score 30 of 100 for AI exposure. 44% of their task time still needs a person. AI can do 21% today and speed up another 35%.

-   **21%** AI can do it
-   **35%** AI helps
-   **44%** Needs a person

Moderate exposure

Lower than 63% of the 923 occupations we scored.

## Task by task

We graded 30 tasks, listed here from most to least exposed. AI can do 7 of them today, speeds up 10 and leaves 13 to people.

| Task | AI exposure |
| --- | --- |
| Keep records of out-going orders. Logging outgoing order records is routine data entry. | 80% AI can do it |
| Compute prices of items or groups of items. Price calculations are simple arithmetic AI and spreadsheets handle easily. | 80% AI can do it |
| Complete order receipts. Order receipt paperwork is routine document work AI handles well. | 72% AI can do it |
| Keep records on the use or damage of stock or stock-handling equipment. Damage and equipment use logs are routine record keeping. | 70% AI can do it |
| Compare merchandise invoices to items actually received to ensure that shipments are correct. Invoice matching against receipts is document comparison AI does well. | 70% AI can do it |

## How stockers compare

All occupations (923)

Transportation and material moving (52)

**Stockers score 30**, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 25 for transportation and material moving.

## Pay and outlook in the US

Median pay

$37,330 a year, May 2025

People employed

2.8 million in the US, May 2025

Projected change in jobs

+8.9% from 2024 to 2034

## Skills to build

-   Operate forklifts and power equipment on the warehouse floor
-   Check invoices against received goods in SAP software
-   Stock shelves and bins with transferred merchandise manually
-   Build pricing sheets in Microsoft Excel with formulas
-   Set up sales displays and mark prices on merchandise

## Safer roles nearby

5 related occupations with lower scores.

-   [Warehouse workers17 out of 100](https://www.aigentcy.com/ai-exposure/warehouse-workers/)
-   [Mail sorters20 out of 100](https://www.aigentcy.com/ai-exposure/mail-sorters/)
-   [Mail clerks25 out of 100](https://www.aigentcy.com/ai-exposure/mail-clerks/)
-   [Packers19 out of 100](https://www.aigentcy.com/ai-exposure/packers/)
-   [Recycling workers12 out of 100](https://www.aigentcy.com/ai-exposure/recycling-workers/)

## Questions about stockers and AI

Will AI replace stockers?

Partly. About 3 in 10 working hours go to tasks AI can already do, mostly keeping records of outgoing orders and computing prices. Lifting, stocking, unloading, and picking stay with people because they need hands, balance, and movement across a floor. Most of the day still needs a person on the dock and on the shelves.

Which stocker tasks is AI taking over?

Record keeping and paperwork lead the list. Logging outgoing order records scores 80 on exposure because it is routine data entry. Computing prices also scores 80, since simple arithmetic is what spreadsheets handle well. Completing order receipts scores 72, and comparing merchandise invoices to items received scores 70 because document matching is work AI does well.

Which stocker tasks stay human?

Physical handling stays with people. Operating equipment such as forklifts scores just 3 on exposure, since it is hands-on work on a moving floor. Stocking shelves, racks, and bins scores 5 because it needs hands and movement. Obtaining merchandise from bins and unloading shipments also score 5, since picking and unpacking are physical labor.

How do stockers stay valuable?

Move toward the work that sits between the paperwork and the floor. Learn SAP software goods receipts so you can catch invoice mismatches before a shipment is shelved. Build pricing and damage logs in Microsoft Excel and Access, then train others on forklift safety. Hold a forklift operator certificate, since equipment work stays physical.

## Related jobs

-   [Shipping clerks47 out of 100](https://www.aigentcy.com/ai-exposure/shipping-clerks/)
-   [Rental clerks57 out of 100](https://www.aigentcy.com/ai-exposure/rental-clerks/)
-   [Inventory checkers30 out of 100](https://www.aigentcy.com/ai-exposure/inventory-checkers/)
-   [Retail salespeople48 out of 100](https://www.aigentcy.com/ai-exposure/retail-salespeople/)

## Next steps for stockers

-   ### Check your job
    
    Your job title is a rough guide. Your actual tasks decide your score. Paste your job description or CV and see which of your tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

## Related topics

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-   [**Jobs most at risk from AI**Proofreaders score highest, at 76.](https://www.aigentcy.com/ai-exposure/jobs-most-exposed-to-ai/)
-   [**High-paying jobs with low AI exposure**Radiologists earn a median $420,860 and score 46.](https://www.aigentcy.com/ai-exposure/high-paying-jobs-low-ai-exposure/)
-   [**Entry-level jobs with low AI exposure**Cement masons need little prior training and score 8.](https://www.aigentcy.com/ai-exposure/entry-level-jobs-low-ai-exposure/)
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-   [**Jobs A to Z**Every job we publish, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/)
-   [**AI exposure by industry**Average scores for 22 occupation groups.](https://www.aigentcy.com/ai-exposure/industries/)
-   [**Write a CV screening software can read**How applicant tracking systems read a CV, and what to change.](https://www.aigentcy.com/ai-exposure/cv-screening-guide/)
-   [**AI for businesses**The tasks to automate first in each team and industry.](https://www.aigentcy.com/ai-for/)
-   [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/)

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
