High AI Risk Declining

Rolling machine setters, operators, and tenders, metal and plastic

SOC Code: 51-4023

Rolling machine setters, operators, and tenders, metal and plastic carries a 45% AI exposure score (High automation risk), with a median annual wage of $48,630 and -8.3% projected employment growth from 2024 to 2034 (BLS), affecting approximately 22,500 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
45% High
Above-average exposure

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

Projected Growth
-8.3%
Bottom 10% growth
2024–2034 (BLS)
-1,900 jobs
Median Annual Wage
$48,630
Typical pay
BLS May 2024
How wage figures are sourced →
The verdict

At 45% AI exposure, Rolling machine setters, operators, and tenders, metal and plastic sits 8 points above the 37.2% average across 832 U.S. occupations - more exposed than 81% of them. Most of its core tasks still require human judgment.

45%
AI exposure
Top 19%
most exposed
-8.3%
Job growth 2024–34
$48,630
Median wage
F

Career outlook score

20/100

Rolling machine setters, operators, and tenders, metal and plastic, 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 $48,630

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -8.3%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) F 45% 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 Rolling machine setters, operators, and tenders, metal and plastic in the High band.

Credential × growth standing

Open entry on a declining BLS line

Typical entry is HS / some college (333/832) while growth is Declining (111/832). This is the crowded high-risk corner of the map - automation and headcount pressure compound without a degree moat.

Where Rolling machine setters, operators, and tenders, metal and plastic sits among all occupations

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

Where Rolling machine setters, operators, and tenders, metal and plastic sits by AI exposure

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

45% Higher than most higher than 81% 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.

Rolling machine setters, operators, and tenders, metal and plastic vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Rolling machine setters, operators, and tenders, metal and plastic 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 (%) →Rolling machine sett, AI exposure (%) →: 45% · Projected growth (%) →: -8.3%Rolling machine settMiscellaneous 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

22,500
Employment 2024
20,600
Projected 2034
-8.3%
Change (%)
-1,900
Change (jobs)

Where This Score Comes From

Rolling machine setters, operators, and tenders, metal and plastic'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 51-4023) 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 Rolling machine setters, operators, and tenders, metal and plastic 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 Rolling machine setters, operators, and tenders, metal and plastic. 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. Monitor machine cycles and mill operation to detect jamming and to ensure that products conform to specifications.
  2. 2. Adjust and correct machine set-ups to reduce thicknesses, reshape products, and eliminate product defects.
  3. 3. Start operation of rolling and milling machines to flatten, temper, form, and reduce sheet metal sections and to produce steel strips.
  4. 4. Examine, inspect, and measure raw materials and finished products to verify conformance to specifications.
  5. 5. Read rolling orders, blueprints, and mill schedules to determine setup specifications, work sequences, product dimensions, and installation procedures.
  6. 6. Thread or feed sheets or rods through rolling mechanisms, or start and control mechanisms that automatically feed steel into rollers.
  7. 7. Manipulate controls and observe dial indicators to monitor, adjust, and regulate speeds of machine mechanisms.
  8. 8. Set distance points between rolls, guides, meters, and stops, according to specifications.
  9. 9. Calculate draft space and roll speed for each mill stand to plan rolling sequences and specified dimensions and tempers.
  10. 10. Install equipment such as guides, guards, gears, cooling equipment, and rolls, using hand tools.

Key Skills Required

  • Operations Monitoring
  • Operation and Control
  • Quality Control Analysis
  • Monitoring
  • Speaking
  • Active Listening
  • Critical Thinking
  • Reading Comprehension
  • Active Learning
  • Coordination

Knowledge Areas

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

Frequently Asked Questions

Will AI replace Rolling machine setters, operators, and tenders, metal and plastic?

Rolling machine setters, operators, and tenders, metal and plastic has an AI exposure score of 45%, 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 Rolling machine setters, operators, and tenders, metal and plastic?

According to BLS Employment Projections 2024-2034, Rolling machine setters, operators, and tenders, metal and plastic is projected to decline by 8.3% over the decade. Current employment stands at approximately 22,500 workers.

What skills are needed for Rolling machine setters, operators, and tenders, metal and plastic?

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

How much do Rolling machine setters, operators, and tenders, metal and plastic earn?

The median annual wage for Rolling machine setters, operators, and tenders, metal and plastic is $48,630, 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 Rolling machine setters, operators, and tenders, metal and plastic?

The typical entry-level education for Rolling machine setters, operators, and tenders, metal and plastic 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 Rolling machine setters, operators, and tenders, metal and plastic?

Rolling machine setters, operators, and tenders, metal and plastic 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

2.3
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 Rolling machine setters, operators, and tenders, metal and plastic: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (45% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-8.3% 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 Rolling machine setters, operators, and tenders, metal and plastic's 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.