Medium AI Risk Declining

Sewers, hand

SOC Code: 51-6051

Sewers, hand carries a 29% AI exposure score (Medium automation risk), with a median annual wage of $33,760 and -7.0% projected employment growth from 2024 to 2034 (BLS), affecting approximately 5,400 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
29% Medium
Typical exposure

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

Projected Growth
-7.0%
Bottom 10% growth
2024–2034 (BLS)
-400 jobs
Median Annual Wage
$33,760
Bottom 10% pay
BLS May 2024
How wage figures are sourced →
The verdict

At 29% AI exposure, Sewers, hand sits 8 points below the 37.2% average across 832 U.S. occupations - more exposed than 27% of them. Most of its core tasks still require human judgment.

29%
AI exposure
27th
percentile
-7.0%
Job growth 2024–34
$33,760
Median wage
F

Career outlook score

26/100

Sewers, hand, 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 $33,760

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -7.0%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) B 29% 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 Sewers, hand in the Medium band.

Credential × growth standing

Open entry on a declining BLS line

Typical entry is No credential (109/832) 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 Sewers, hand sits among all occupations

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

Where Sewers, hand sits by AI exposure

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

29% Lower than most lower than 73% 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.

Sewers, hand vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Sewers, hand 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 (%) →Sewers, AI exposure (%) →: 29% · Projected growth (%) →: -7%SewersMiscellaneous 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

5,400
Employment 2024
5,000
Projected 2034
-7.0%
Change (%)
-400
Change (jobs)

Where This Score Comes From

Sewers, hand's Medium 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 below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.

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 51-6051) 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 Sewers, hand 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 Sewers, hand. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Moderate-term on-the-job training

Top Tasks (O*NET)

  1. 1. Fit garments on clients, altering as needed.
  2. 2. Select thread, twine, cord, or yarn to be used, and thread needles.
  3. 3. Measure and align parts, fasteners, or trimmings, following seams, edges, or markings on parts.
  4. 4. Trim excess threads or edges of parts, using scissors or knives.
  5. 5. Smooth seams with heated irons, flat bones, or rubbing sticks.
  6. 6. Sew, join, reinforce, or finish parts of articles, such as garments, books, mattresses, toys, and wigs, using needles and thread or other materials.
  7. 7. Use different sewing techniques such as felling, tacking, basting, embroidery, and fagoting.
  8. 8. Draw and cut patterns according to specifications.
  9. 9. Fold, twist, stretch, or drape material, and secure articles in preparation for sewing.
  10. 10. Sew buttonholes, or add lace or other trimming.

Key Skills Required

  • Judgment and Decision Making
  • Time Management
  • Active Listening
  • Speaking
  • Monitoring
  • Complex Problem Solving
  • Reading Comprehension
  • Critical Thinking
  • Active Learning
  • Operations Monitoring

Knowledge Areas

  • Customer and Personal Service
  • Administration and Management
  • English Language
  • Mechanical
  • Education and Training
  • Mathematics
  • Design
  • Production and Processing
  • Economics and Accounting
  • Sales and Marketing

Frequently Asked Questions

Will AI replace Sewers, hand?

Sewers, hand has an AI exposure score of 29%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.

What is the job outlook for Sewers, hand?

According to BLS Employment Projections 2024-2034, Sewers, hand is projected to decline by 7.0% over the decade. Current employment stands at approximately 5,400 workers.

What skills are needed for Sewers, hand?

Key skills for Sewers, hand include Judgment and Decision Making, Time Management, Active Listening, and others. Typical entry-level education is No formal educational credential.

How much do Sewers, hand earn?

The median annual wage for Sewers, hand is $33,760, 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 Sewers, hand?

The typical entry-level education for Sewers, hand is No formal educational credential. 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 Sewers, hand?

Sewers, hand 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

1.4
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Sewers, hand: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (29% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-7.0% 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 Sewers, hand'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.