High AI Risk Slow Growth

Cutting and slicing machine setters, operators, and tenders

SOC Code: 51-9032

Cutting and slicing machine setters, operators, and tenders carries a 47% AI exposure score (High automation risk), with a median annual wage of $45,700 and -2.3% projected employment growth from 2024 to 2034 (BLS), affecting approximately 49,000 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
47% High
Above-average exposure

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
-2.3%
Below typical growth
2024–2034 (BLS)
-1,100 jobs
Median Annual Wage
$45,700
Typical pay
BLS May 2024
How wage figures are sourced →
The verdict

At 47% AI exposure, Cutting and slicing machine setters, operators, and tenders sits 10 points above the 37.2% average across 832 U.S. occupations - more exposed than 83% of them. Most of its core tasks still require human judgment.

47%
AI exposure
Top 17%
most exposed
-2.3%
Job growth 2024–34
$45,700
Median wage
F

Career outlook score

21/100

Cutting and slicing machine setters, operators, and tenders, weighted across 3 of 3 tracked dimensions

A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.

  • Median wage F $45,700

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -2.3%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) F 47% exposure

    Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure

Employment vs AI exposure

Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).

4.3M
Home health and personal care aides employment (#1)
#392
Home health and personal care aides AI rank
95%
Bookkeeping, accounting, and auditing clerks AI exposure (#1)
#17
Bookkeeping, accounting, and auditing clerks employment rank

Automation-risk inventory

Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Cutting and slicing machine setters, operators, and tenders in the High band.

Credential × growth standing

Open entry with non-declining BLS pace

Cutting and slicing machine setters, operators, and tenders keeps an HS / some college bar (333 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.

Where Cutting and slicing machine setters, operators, and tenders sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

Where Cutting and slicing machine setters, operators, and tenders sits by AI exposure

AI-exposure score distribution across U.S. occupations (O*NET task analysis)

47% Higher than most higher than 83% of 832 occupations

Occupations, banded by AI-exposure score

Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.

Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034

Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.

Cutting and slicing machine setters, operators, and tenders vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Cutting and slicing machine setters, operators, and tenders is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk28.1%33.0%38%43.0%47.9%-11.5%-7.0%-2.5%1.9%6.4%AI exposure (%) →Projected growth (%) →Cutting, AI exposure (%) →: 47% · Projected growth (%) →: -2.3%CuttingMiscellaneous assemb, AI exposure (%) →: 35% · Projected growth (%) →: -0.1%Miscellaneous assembFirst-line superviso, AI exposure (%) →: 35% · Projected growth (%) →: 1.2%First-line supervisoInspectors, AI exposure (%) →: 47% · Projected growth (%) →: 0%InspectorsWelders, AI exposure (%) →: 29% · Projected growth (%) →: 2.2%WeldersPackaging, AI exposure (%) →: 42% · Projected growth (%) →: 4.5%PackagingMachinists, AI exposure (%) →: 30% · Projected growth (%) →: 0%MachinistsProduction workers, AI exposure (%) →: 35% · Projected growth (%) →: 0.5%Production workersElectrical, AI exposure (%) →: 35% · Projected growth (%) →: 4.6%ElectricalBakers, AI exposure (%) →: 37% · Projected growth (%) →: 5.6%BakersLaundry, AI exposure (%) →: 31% · Projected growth (%) →: 5.4%LaundryComputer numerically, AI exposure (%) →: 36% · Projected growth (%) →: -10.7%Computer numerically

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

49,000
Employment 2024
47,900
Projected 2034
-2.3%
Change (%)
-1,100
Change (jobs)

Where This Score Comes From

Cutting and slicing machine setters, operators, and tenders's High automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score in the 40–70% range indicates meaningful automation pressure on specific task categories, but the role as a whole still requires human judgment for coordination, exception handling, or client interaction.

The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 51-9032) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Cutting and slicing machine setters, operators, and tenders be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Cutting and slicing machine setters, operators, and tenders. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.

Education & Entry Requirements

Typical Education
High school diploma or equivalent
Work Experience
None
On-the-Job Training
Moderate-term on-the-job training

Top Tasks (O*NET)

  1. 1. Set up, operate, or tend machines that cut or slice materials, such as glass, stone, cork, rubber, tobacco, food, paper, or insulating material.
  2. 2. Review work orders, blueprints, specifications, or job samples to determine components, settings, and adjustments for cutting and slicing machines.
  3. 3. Examine, measure, and weigh materials or products to verify conformance to specifications, using measuring devices, such as rulers, micrometers, or scales.
  4. 4. Press buttons, pull levers, or depress pedals to start and operate cutting and slicing machines.
  5. 5. Start machines to verify setups, and make any necessary adjustments.
  6. 6. Feed stock into cutting machines, onto conveyors, or under cutting blades, by threading, guiding, pushing, or turning handwheels.
  7. 7. Mark cutting lines or identifying information on stock, using marking pencils, rulers, or scribes.
  8. 8. Monitor operation of cutting or slicing machines to detect malfunctions or to determine whether supplies need replenishment.
  9. 9. Stack and sort cut material for packaging, further processing, or shipping, according to types and sizes of material.
  10. 10. Adjust machine controls to alter position, alignment, speed, or pressure.

Key Skills Required

  • Operations Monitoring
  • Operation and Control
  • Quality Control Analysis
  • Monitoring
  • Reading Comprehension
  • Critical Thinking
  • Coordination
  • Equipment Maintenance
  • Troubleshooting
  • Active Listening

Knowledge Areas

  • Production and Processing
  • Mathematics
  • Mechanical
  • English Language
  • Administration and Management
  • Education and Training
  • Customer and Personal Service
  • Public Safety and Security
  • Computers and Electronics
  • Engineering and Technology

Frequently Asked Questions

Will AI replace Cutting and slicing machine setters, operators, and tenders?

Cutting and slicing machine setters, operators, and tenders has an AI exposure score of 47%, indicating a high level of automation risk. Some tasks in this role can be augmented or partially automated by AI, but core responsibilities require human judgment.

What is the job outlook for Cutting and slicing machine setters, operators, and tenders?

According to BLS Employment Projections 2024-2034, Cutting and slicing machine setters, operators, and tenders is projected to decline by 2.3% over the decade. Current employment stands at approximately 49,000 workers.

What skills are needed for Cutting and slicing machine setters, operators, and tenders?

Key skills for Cutting and slicing machine setters, operators, and tenders include Operations Monitoring, Operation and Control, Quality Control Analysis, and others. Typical entry-level education is High school diploma or equivalent.

How much do Cutting and slicing machine setters, operators, and tenders earn?

The median annual wage for Cutting and slicing machine setters, operators, and tenders is $45,700, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Cutting and slicing machine setters, operators, and tenders?

The typical entry-level education for Cutting and slicing machine setters, operators, and tenders is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.

Which companies employ Cutting and slicing machine setters, operators, and tenders?

Cutting and slicing machine setters, operators, and tenders roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

2.4
out of 5.0

High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Cutting and slicing machine setters, operators, and tenders: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (47% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-2.3% here).

Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.

What to do with this

Use Cutting and slicing machine setters, operators, and tenders' numbers above to compare, not just read in isolation.

AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.

Sources: BLS Employment Projections 2024-2034, O*NET Database 30.0.