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# Will packers be replaced by AI?

Updated October 2026

Packers score 19 of 100 for AI exposure. 69% of their task time still needs a person. AI can do 10% today and speed up another 21%.

-   **10%** AI can do it
-   **21%** AI helps
-   **69%** Needs a person

Low exposure

Lower than 82% of the 923 occupations we scored.

## Task by task

We graded 12 tasks, listed here from most to least exposed. AI can do 1 of them today, speeds up 2 and leaves 9 to people.

| Task | AI exposure |
| --- | --- |
| Record product, packaging, and order information on specified forms and records. Recording order and package details is routine digital data entry. | 70% AI can do it |
| Examine and inspect containers, materials, or products to ensure that product quality and packing specifications are met. Vision tools can check specs, but a person physically inspects items. | 30% AI helps |
| Mark and label containers, container tags, or products, using marking tools. Label text can be generated, but applying labels is manual. | 30% AI helps |
| Measure, weigh, and count products and materials. Hands-on weighing and counting of physical items. | 12% Needs a person |
| Load materials and products into package processing equipment. Manually feeding materials into packaging machines, mostly physical. | 10% Needs a person |

## How packers compare

All occupations (923)

Transportation and material moving (52)

**Packers score 19**, 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

$36,280 a year, May 2025

People employed

559,820 in the US, May 2025

Projected change in jobs

\-5.0% from 2024 to 2034

## Skills to build

-   Inspect products against packing specifications on the line
-   Apply labels and tags with marking tools
-   Seal cartons with tape, glue, and fasteners
-   Read packaging drawings in Autodesk AutoCAD
-   Keep stock records in inventory tracking software

## Safer roles nearby

5 related occupations with lower scores.

-   [Warehouse workers17 out of 100](https://www.aigentcy.com/ai-exposure/warehouse-workers/)
-   [Paper goods machine operators16 out of 100](https://www.aigentcy.com/ai-exposure/paper-goods-machine-operators/)
-   [Hand cutters16 out of 100](https://www.aigentcy.com/ai-exposure/hand-cutters/)
-   [Molders15 out of 100](https://www.aigentcy.com/ai-exposure/molders/)
-   [Hand polishers17 out of 100](https://www.aigentcy.com/ai-exposure/hand-polishers/)

## Questions about packers and AI

Will AI replace packers?

Partly. About 2 in 10 working hours go to tasks AI can already do, mostly recording order and package details and marking labels on containers. Hands-on sealing, weighing, and loading stay with people because they need a person at the packing bench.

Which packing tasks is AI taking over?

AI is taking over the paperwork side of packing first. Recording product, packaging, and order details scores 70 on exposure because it is routine digital data entry that software can fill from order records. Label text can also be generated by software, though applying the labels stays manual.

Which packing tasks stay human?

Physical handling stays human. Sealing containers scores 8 on exposure and transporting packages to customers' vehicles scores 3, since both need hands on boxes and products. Measuring, weighing, and counting score 12 because a person must put real items on a scale and count them manually.

How can packers stay valuable?

Move toward the records and tools around the packing line. Keep stock counts in inventory tracking software, enter order details in SAP software, and build packing sheets in Microsoft Excel so the digital record matches the boxes you seal. Learning to read packaging drawings in Autodesk AutoCAD also keeps a packer useful when specifications change.

## Related jobs

-   [Packaging machine operators19 out of 100](https://www.aigentcy.com/ai-exposure/packaging-machine-operators/)
-   [Inventory checkers30 out of 100](https://www.aigentcy.com/ai-exposure/inventory-checkers/)
-   [Production helpers19 out of 100](https://www.aigentcy.com/ai-exposure/production-helpers/)
-   [Forming press operators26 out of 100](https://www.aigentcy.com/ai-exposure/forming-press-operators/)

## Next steps for packers

-   ### 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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-   [**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.
