Evolving

Last Update: 2/17/2026

Your role’s AI Resilience Score is

35.6%

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

Paper Goods Machine Setters, Operators, and Tenders

They operate and adjust machines to make paper products like napkins or bags, ensuring everything runs smoothly and the products are made correctly.

This role is evolving

This career is labeled as "Evolving" because AI and automation are gradually being integrated into many routine tasks, such as lifting heavy rolls and monitoring production processes. While machines make these tasks easier and more efficient, skilled operators are still essential for handling unexpected situations and making fine adjustments that AI can't manage.

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Learn more about how you can thrive in this position

View analysis
Chat with Coach
Latest news
More career info
Analysis
Chat
News
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This role is evolving

This career is labeled as "Evolving" because AI and automation are gradually being integrated into many routine tasks, such as lifting heavy rolls and monitoring production processes. While machines make these tasks easier and more efficient, skilled operators are still essential for handling unexpected situations and making fine adjustments that AI can't manage.

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
Evolving iconEvolving

31.7%

31.7%

Microsoft's Working with AI

AI Applicability

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Stable iconStable

73.7%

73.7%

Will Robots Take My Job

Automation Resilience

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Changing fast iconChanging fast

8.5%

8.5%

Low 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):

-6.3%

Growth Percentile:

8.8%

Annual Openings:

8,100

Annual Openings Pct:

49.0%

Analysis of Current AI Resilience

Paper Goods Machine Ops

Updated Quarterly • Last Update: 2/17/2026

Analysis
Suggested Actions
State of Automation

What's changing and what's not

Paper‐goods machine operators still do many tasks by hand, but some parts are automated. For example, machines already use conveyor belts and robotic arms to place heavy rolls onto feeders [1]. Modern presses have sensors and controllers so tension, speed, and glue temperatures can be set automatically.

In fact, some factories use AI-driven control systems to fine-tune glue or coating processes and cut waste [2] [2]. Likewise, high-speed cameras and vision systems can flag damaged cartons. Even so, people usually inspect and fix problems when a computer alerts them.

Other tasks – like taking machines apart for repairs or making fine mechanical adjustments – remain very hands-on. Those still require a skilled operator’s judgment and tool‐skills. In short, robotics and AI handle many routine parts of the job (lifting, threading paper, steady control loops), but human workers continue to oversee the line and solve issues when machines see unexpected situations [1] [2].

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AI Adoption

AI in the real world

Packaging and paper-product companies are showing growing interest in automation. A McKinsey survey found that consumer-goods manufacturers expect a big push into robotics and automation investment [3]. Many plant managers turn to robots when labor is expensive or hard to find [4], or to boost output and cut defects (one factory cut scrap by 56% using smarter controls [2]).

However, new robots and AI systems cost a lot of money and need trained technicians to run them [3]. For a small plant, it can be cheaper to hire a few people than buy an expensive robot. As a result, change is gradual.

Generally, industry accepts automating the toughest or dullest parts of the job (making the work safer and more efficient). At the same time, operators’ skills – like troubleshooting, setting up machines, and quality judgment – stay very important. In a balanced future, AI helps with heavy lifting and constant monitoring, and people focus on creative problem-solving and machine oversight [3] [4].

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More Career Info

Task-Level AI Resilience Scores

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

1

70% ResilienceCore Task

Adjust guide assemblies, forming bars, and folding mechanisms according to specifications, using hand tools.

2

65% ResilienceSupplemental

Disassemble machines to maintain, repair, or replace broken or worn parts, using hand or power tools.

3

60% ResilienceCore Task

Examine completed work to detect defects and verify conformance to work orders, and adjust machinery as necessary to correct production problems.

4

60% ResilienceSupplemental

Remove finished cores, and stack or place them on conveyors for transfer to other work areas.

5

55% ResilienceSupplemental

Measure, space, and set saw blades, cutters, and perforators, according to product specifications.

6

50% ResilienceSupplemental

Install attachments to machines for gluing, folding, printing, or cutting.

7

50% ResilienceSupplemental

Monitor finished cartons as they drop from forming machines into rotating hoppers and into gravity feed chutes to prevent jamming.

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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