Somewhat Resilient

Last Update: 10/7/2026

AI Resilience Score for Cutting & Slicing Machine Ops:

39.0%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Low

Sustained economic opportunity

Low

Our confidence in this score:
Low-medium

Methodology and Scoring Rationale

To score how resilient cutting and slicing machine operation is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For cutting and slicing machine ops, six of eight sources had data. Three AI exposure sources (AI Resilience Model, Anthropic, and Microsoft) agreed this work stays largely human, but Will Robots Take My Job disagreed, pulling confidence to low-medium. Weak hiring and pay signals dragged the score down, landing this role at "Somewhat Resilient."

AI Resilience Report forCutting and Slicing Machine Setters, Operators, and Tenders

$46,570 median salary•5,400 annual openings•SOC Code: 51-9032.00

Cutting and Slicing Machine Setters, Operators, and Tenders are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.

This career sits in the "Somewhat Resilient" category because AI is genuinely changing how cutting and slicing machines operate, with systems now handling tasks like nesting, inspection, and record-keeping that humans used to manage manually. At the same time, robots and AI still struggle with the hands-on, dexterous work that operators do every day, like installing blades, cleaning equipment, and managing changeovers, so human workers are not disappearing anytime soon.

Learn more about how you can thrive in this position

This role is somewhat resilient

This career sits in the "Somewhat Resilient" category because AI is genuinely changing how cutting and slicing machines operate, with systems now handling tasks like nesting, inspection, and record-keeping that humans used to manage manually. At the same time, robots and AI still struggle with the hands-on, dexterous work that operators do every day, like installing blades, cleaning equipment, and managing changeovers, so human workers are not disappearing anytime soon.

Read full analysis

Analysis of current AI resilience

Cutting & Slicing Machine Ops

Updated quarterly

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How can Cutting & Slicing Machine Ops prepare for AI?

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Latest AI news for Cutting & Slicing Machine Ops

The articles highlight that while AI poses a notable replacement risk for Cutting and Slicing Machine Setters, Operators, and Tenders, it also offers opportunities for adaptation. The first article indicates a high risk score of 88, emphasizing the need for workers to upskill in areas where human oversight remains crucial. Meanwhile, the second article points out that while automation is transforming the role, it is unlikely to fully replace it, suggesting that workers can focus on enhancing their technical and problem-solving skills to remain relevant in this evolving landscape.

More Career Info

Career: Cutting and Slicing Machine Setters, Operators, and Tenders

They operate machines to cut and slice materials like metal or food, ensuring products are made to the right size and shape.

Parent Careers

Employment & Wage Data

Median Wage

$46,570

Jobs (2025)

45,900

Growth (2025-35)

-0.9%

Annual Openings

5,400

Education

High school diploma or equivalent

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

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

1

82% ResilienceSupplemental

Direct workers on cutting teams.

2

80% ResilienceSupplemental

Position width gauge blocks between blades, and level blades and insert wedges into frames to secure blades to frames.

3

80% ResilienceSupplemental

Cut stock manually to prepare for machine cutting, using tools such as knives, cleavers, handsaws, or hammers and chisels.

4

78% ResilienceCore Task

Change or replace saw blades, cables, cutter heads, and grinding wheels, using hand tools.

5

78% ResilienceSupplemental

Sharpen cutting blades, knives, or saws, using files, bench grinders, or honing stones.

6

75% ResilienceCore Task

Select and install machine components, such as cutting blades, rollers, and templates, according to specifications, using hand tools.

7

72% ResilienceSupplemental

Wash stones, using water hoses.

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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