Evolving

Last Update: 2/17/2026

Your role’s AI Resilience Score is

45.3%

Median Score

Changing Fast

Evolving

Stable

Our confidence in this score:
Low-medium

What does this resilience result mean?

These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.

AI Resilience Report for

Packaging and Filling Machine Operators and Tenders

They operate machines to pack or fill products like food or liquids into containers, ensuring everything is sealed and labeled correctly.

This role is evolving

The career of Packaging and Filling Machine Operators and Tenders is labeled as "Evolving" because AI and robots are taking over many routine tasks like filling and stacking, but humans are still crucial for overseeing these machines and solving unexpected problems. While some tasks are automated, workers are needed to start machines, clear jams, and ensure everything runs smoothly.

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Learn more about how you can thrive in this position

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Chat with Coach
Latest news
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This role is evolving

The career of Packaging and Filling Machine Operators and Tenders is labeled as "Evolving" because AI and robots are taking over many routine tasks like filling and stacking, but humans are still crucial for overseeing these machines and solving unexpected problems. While some tasks are automated, workers are needed to start machines, clear jams, and ensure everything runs smoothly.

Read full analysis

Contributing Sources

We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.

AI Resilience

AI Resilience Model v1.0

AI Task Resilience

Learn about this score
Changing fast iconChanging fast

2.1%

2.1%

Microsoft's Working with AI

AI Applicability

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Stable iconStable

97.4%

97.4%

Will Robots Take My Job

Automation Resilience

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Changing fast iconChanging fast

3.7%

3.7%

High Demand

Labor Market Outlook

We use BLS employment projections to complement the AI-focused assessments from other sources.

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Growth Rate (2024-34):

4.5%

Growth Percentile:

68.7%

Annual Openings:

45,300

Annual Openings Pct:

80.6%

Analysis of Current AI Resilience

Packaging Machine Operator

Updated Quarterly • Last Update: 2/17/2026

Analysis
Suggested Actions
State of Automation

What's changing and what's not

In packaging plants, many routine tasks are already done by machines and robots. For example, robotic arms and conveyors can now pick up products, fill bags or boxes, and stack pallets with little human help [1] [2]. These “cobots” (collaborative robots) work safely next to people and can even sense package sizes or handle different packing tasks [2] [1].

AI is also helping with quality checks: smart vision systems can automatically inspect seals, labels or product defects, catching errors faster than a person might [1] [3]. Even simple jobs like counting finished items are often done by sensors or software today. Still, people play a key role.

Workers typically load and start the machines, clear jams, and handle any unusual problems. In other words, machines do the heavy, repetitive work, but humans still oversee the process and make sure everything runs smoothly [3] [1].

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AI Adoption

AI in the real world

Packing companies face mixed factors that affect how fast they adopt AI. On one hand, there’s strong motivation to automate. Labor is hard to find – the U.S. has hundreds of thousands of factory jobs unfilled – so companies invest in robots and AI to keep production going [4] [5].

In fact, a recent industry survey found most manufacturing leaders rank AI as a top priority, planning big budget increases for it [3]. New machines on the market often come with built-in AI or smart controls, so the tech is available now. Automation can boost output and ensure consistent quality, which is especially important for food, medicine, and other safety-critical products [1] [5].

On the other hand, there are reasons adoption can be slow. High-tech packaging equipment can cost a lot, and small companies worry about the price and lack of skilled staff to run it [1] [5]. For example, industry experts note that many firms see automation as expensive especially for smaller operations, even though prices are gradually falling [1].

Packaging machines also need trained people to program and maintain them [5] [2]. In short, big-budget firms or those desperate for workers tend to automate faster, while others wait until costs drop or staff are trained. Importantly, experts stress that automation doesn’t just eliminate jobs – it shifts them.

Workers can be retrained to supervise robots, solve problems, and improve the process [3] [3]. In this way, human skills like attention to detail, troubleshooting, and creativity remain very valuable even as AI takes on more of the routine packaging work.

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More Career Info

Career: Packaging and Filling Machine Operators and Tenders

Employment & Wage Data

Median Wage

$40,900

Jobs (2024)

381,200

Growth (2024-34)

+4.5%

Annual Openings

45,300

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2024-2034

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

40% ResilienceCore Task

Stock and sort product for packaging or filling machine operation, and replenish packaging supplies, such as wrapping paper, plastic sheet, boxes, cartons, glue, ink, or labels.

2

38% ResilienceSupplemental

Clean, oil, and make minor adjustments or repairs to machinery and equipment, such as opening valves or setting guides.

3

37% ResilienceSupplemental

Clean packaging containers, line and pad crates, or assemble cartons to prepare for product packing.

4

36% ResilienceSupplemental

Clean and remove damaged or otherwise inferior materials to prepare raw products for processing.

5

35% ResilienceCore Task

Stop or reset machines when malfunctions occur, clear machine jams, and report malfunctions to a supervisor.

6

34% ResilienceCore Task

Monitor the production line, watching for problems such as pile-ups, jams, or glue that isn't sticking properly.

7

32% ResilienceCore Task

Inspect and remove defective products and packaging material.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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