Will AI replace Packaging and Filling Machine Operators and Tenders?
AI reaches little of this job’s work.
8/100
Low exposure
More exposed to AI than 17% of US workers.
- AI already used in
- 0% of the work
- As AI tools mature: up to
- 16% of the work
What the job involves
Operate or tend machines to prepare industrial or consumer products for storage or shipment. Includes cannery workers who pack food products.
Where AI reaches the work
The job’s main tasks, heaviest first, by how far AI reaches them.
Within reach(3)
- Attach identification labels to finished packaged items, or cut stencils and stencil information on containers, such as lot numbers or shipping destinations.
- Stop or reset machines when malfunctions occur, clear machine jams, and report malfunctions to a supervisor.
- Count and record finished and rejected packaged items.
Out of reach(17)
- Remove finished packaged items from machine and separate rejected items.
- Inspect and remove defective products and packaging material.
- Observe machine operations to ensure quality and conformity of filled or packaged products to standards.
- Start machine by engaging controls.
- Sort, grade, weigh, and inspect products, verifying and adjusting product weight or measurement to meet specifications.
and 12 more
Also called
Filler Operator · Packaging Machine Operator · Packing Machine Operator · Ampoule Filler · Bottle Packer · Bunch Maker · Carder · Cylinder Filler
Related jobs
What these numbers mean
The score is the share of this job’s work, weighted by how important and frequent each task is, that AI could do in half the time: tasks an AI model could do alone count in full, tasks that need software built on AI count half.
“AI already used” is the share of the work in tasks where people are recorded using AI today. “As AI tools mature” counts every task AI could halve, with or without extra software.
The percentile compares the score with every job’s, weighted by how many people in the US do each one. Exposure means AI could change how the work is done, not that the job goes away. These are estimates for the typical job, not predictions.
Sources
- O*NET 31.0 Database, U.S. Department of Labor, Employment and Training Administration
- GPTs are GPTs: Labor market impact potential of LLMs (task labels), Eloundou, Manning, Mishkin & Rock (2023), OpenAI and University of Pennsylvania
- Anthropic Economic Index: labor market impacts (task penetration), Anthropic
- Occupational Employment and Wage Statistics, May 2025 (national and metropolitan areas), U.S. Bureau of Labor Statistics