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Shoe and Leather Workers and Repairers

Occupation · SOC 51-6041.00

Construct, decorate, or repair leather and leather-like products, such as luggage, shoes, and saddles. May use hand tools.

Also called: Boot Maker · Cobbler · Shoe Maker · Shoe Repairer · Leather Worker · Saddle and Harness Maker · Shoe Cutter · Shoe Repairman · Stitcher · Back Shoe Cutter · Bench Hand · Boot Repairer

Job family: Production Occupations

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Download .md

A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch /roles/role-51-6041-00/context.md directly.

AI work map

A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.

10th-percentile task overlap — yet about 900 openings a year (-3.8% projected, BLS) . What exposure means →

AI & job outlook

What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.

Exposure to current AI

Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.

Measure Rank vs all occupations Percentile Score
Overall AI exposure (Felten et al.) Low 18th -1.0
LLM task exposure, γ (OpenAI / Eloundou) Low 16th 0.1
AI assistant applicability (Microsoft) Low 9th 0.0

OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.0), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.

This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.

Historical automation estimate (2013)

A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.

Frey–Osborne probability 0.5 · 47th percentile among occupations · Moderate

Job outlook

Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.

Outlook Declining · -3.8% by 2034
Projected annual openings 900
Employment 2024 → 2034 9,500 → 9,100

“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.

Where this work sits on the global GenAI gradient

The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 3 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.

14% mean task exposure (2025)
15th percentile of 427 placed occupations
+1 pts shift 2023 → 2025
International occupation (ISCO-08) Task exposure (2025) Most tasks fall in
Shoemakers and Related Workers · 7536 17% Not exposed
Handicraft Workers in Textile, Leather and Related Materials · 7318 13% Not exposed
Sewing, Embroidery and Related Workers · 7533 12% Not exposed

Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.

Tasks

All 27 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.

Work activities

Knowledge, skills & abilities

O*NET importance rating, from 1 (not important) to 5 (extremely important).

Abilities

Near Vision 3.5
Arm-Hand Steadiness 3.3
Finger Dexterity 3.3
Problem Sensitivity 3.1
Oral Comprehension 3.0
Deductive Reasoning 3.0
Inductive Reasoning 3.0
Information Ordering 3.0
Category Flexibility 3.0
Visualization 3.0
Selective Attention 3.0
Manual Dexterity 3.0
Control Precision 3.0
Speech Recognition 3.0
Speech Clarity 3.0
Oral Expression 2.9
Multilimb Coordination 2.9
Written Comprehension 2.8
Reaction Time 2.8
Far Vision 2.8
Visual Color Discrimination 2.8
Trunk Strength 2.6

Knowledge

Production and Processing 3.2
Customer and Personal Service 3.0
Mechanical 2.9
Sales and Marketing 2.6
Administration and Management 2.4

Essential skills

Active Listening 3.0
Speaking 3.0
Critical Thinking 3.0
Monitoring 3.0
Reading Comprehension 2.9
Active Learning 2.4

Transferable skills

Social Perceptiveness 2.9
Coordination 2.9
Service Orientation 2.9
Operations Monitoring 2.9
Judgment and Decision Making 2.9
Time Management 2.8
Quality Control Analysis 2.5

Skills in demand

Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.

Tools & technology

Example Category
Microsoft Excel Spreadsheet software Hot technology
Bookkeeping software Accounting software
Financial accounting software Accounting software
Inventory tracking software Inventory management software
Sale processing software Point of sale POS software

Work context

How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.

Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls 5.0
Face-to-Face Discussions with Individuals and Within Teams 4.7
Exposed to Contaminants 4.5
Exposed to Hazardous Equipment 4.4
Freedom to Make Decisions 4.3
Indoors, Environmentally Controlled 4.3
Spend Time Standing 4.3
Spend Time Making Repetitive Motions 4.3
Determine Tasks, Priorities and Goals 4.3
Contact With Others 4.3
Importance of Being Exact or Accurate 4.2
Exposed to Sounds, Noise Levels that are Distracting or Uncomfortable 4.1
Time Pressure 4.0
Telephone Conversations 3.9
Frequency of Decision Making 3.6
Deal With External Customers or the Public in General 3.5
Impact of Decisions on Co-workers or Company Results 3.4
Spend Time Walking or Running 3.1
Level of Competition 3.0
Physical Proximity 3.0
Pace Determined by Speed of Equipment 2.8
Dealing With Unpleasant, Angry, or Discourteous People 2.8
Exposed to Minor Burns, Cuts, Bites, or Stings 2.7
Consequence of Error 2.7
Work Outcomes and Results of Other Workers 2.6
Spend Time Bending or Twisting Your Body 2.5
Work With or Contribute to a Work Group or Team 2.5
Health and Safety of Other Workers 2.5
Importance of Repeating Same Tasks 2.4
Coordinate or Lead Others in Accomplishing Work Activities 2.3
E-Mail 2.2
Conflict Situations 2.2
Wear Common Protective or Safety Equipment such as Safety Shoes, Glasses, Gloves, Hearing Protection, Hard Hats, or Life Jackets 2.2
Spend Time Sitting 2.0
Degree of Automation 2.0
Exposed to Cramped Work Space, Awkward Positions 1.8
Indoors, Not Environmentally Controlled 1.8
Written Letters and Memos 1.6
Exposed to Hazardous Conditions 1.6
Wear Specialized Protective or Safety Equipment such as Breathing Apparatus, Safety Harness, Full Protection Suits, or Radiation Protection 1.5

How to get in

Job zone
Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
Education
Usually requires a high school diploma or GED, though some occupations may not.
Typical entry-level education
High school diploma or equivalent · BLS, the typical path — not a requirement
Related experience
Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
Preparation level
SVP (Below 6.0) — total schooling plus on-the-job experience.

What to study: Precision Production . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.

Education of current workers

Share of people in this occupation at each level of education.

High School Diploma 56.4%
Less than a High School Diploma 43.6%

Interests & work styles

The interests and personal qualities O*NET associates with people who do this work.

Career interests (Holland / RIASEC)

Realistic 6.9
Conventional 3.2
Artistic 3.1
Investigative 1.6
Enterprising 1.5
Social 1.3

Interest areas

Physical/Manual Labor 3.4
Visual Arts 3.1
Applied Arts and Design 3.1
Construction/Woodwork 2.6
Mechanics/Electronics 1.5
Personal Service 1.3
Engineering 1.3

Work styles

Attention to Detail 2.3
Dependability 2.0
Cautiousness 1.5

Wages & employment

U.S. · annual wages (BLS OEWS)

$25k10th$29k25th$36kMedian$41k75th$48k90th
Annual wages by percentile — U.S. (BLS OEWS). The light band spans the 10th–90th percentile; the darker band is the middle half (25th–75th); the line is the median.
10k20249k2034 (proj.)-3.8% · Declining
Projected U.S. employment, 2024–2034 (BLS Employment Projections). A labor-market forecast for the occupation, not an AI-impact forecast.
10th percentile $25,170
25th percentile $29,400
Median (50th) $35,950
75th percentile $41,400
90th percentile $48,090
People employed 7,640

Industries that employ this occupation

Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.

Industry Workers National median pay
Manufacturing · Sector 5,870 $35,040
Other Services (except Public Administration) · Sector 690 $39,580
Retail Trade · Sector 570 $39,310
Wholesale Trade · Sector 460 $38,990
Sporting Goods Retailers · National industry 150 $40,830
Administrative and Support and Waste Management and Remediation Services · Sector $28,420
Temporary Help Services · National industry $28,420

Where this work is most concentrated

Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).

Industry Concentration Workers
Sporting Goods Retailers · National industry 10.17× 150
Manufacturing · Sector 9.28× 5,870
Other Services (except Public Administration) · Sector 3.15× 690
Wholesale Trade · Sector 1.54× 460
Retail Trade · Sector 0.74× 570

Part of the Advanced Manufacturing career cluster.

Exposure quadrant: AI task-overlap percentile vs Median pay Shoe and Leather Workers and Repairers sits at the 10th percentile of AI task-overlap and the 5th percentile of median pay, placed here against 12 adjacent occupations on the same two axes. Lower overlap · higher pay Higher overlap · higher pay Higher overlap · lower pay Lower overlap · lower pay Shoe and Leather Workers and Repairers Cutters and Trimmers, Hand Furniture Finishers Molders, Shapers, and Casters, Except Metal and Plastic Jewelers and Precious Stone and Metal Workers AI task-overlap percentile → ↑ Median pay
AI task-overlap percentile (horizontal) vs. median-pay percentile (vertical), across all scored occupations. This occupation is highlighted; related occupations are plotted alongside it. Overlap measures shared tasks with AI, not automation.

Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.

What you can do with this

Options the data surfaces for Shoe and Leather Workers and Repairers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.

Skills that travel

Capabilities this work builds that are used across many other occupations.

Paths in

How people typically prepare for this work.

Zoom out

On the global GenAI exposure gradient this work sits around the 15th percentile of 427 international occupations.

Write a report on thisheadline · factoids · citation

Shoe and Leather Workers and Repairers show 10th-percentile AI task overlap — and about 900 annual U.S. openings

  • Shoe and Leather Workers and Repairers rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
  • The occupation is projected to see about 900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
  • BLS projects employment to be declining (-3.8%) from 2024 to 2034.BLS Employment Projections 2024–34
  • Median annual pay is $35,950, across about 7,640 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Shoe and Leather Workers and Repairers show 10th-percentile AI task overlap — and about 900 annual U.S. openings

• Shoe and Leather Workers and Repairers rank in the 10th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE)
• The occupation is projected to see about 900 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34)
• BLS projects employment to be declining (-3.8%) from 2024 to 2034. (BLS Employment Projections 2024–34)
• Median annual pay is $35,950, across about 7,640 U.S. workers. (BLS OEWS (May 2024))

Source: Singulariki — "Shoe and Leather Workers and Repairers". https://singulariki.com/roles/role-51-6041-00
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.

AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom

Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

Data compiled June 2, 2026. Figures are estimates, not advice.

Cite this page
Plain

Singulariki. "Shoe and Leather Workers and Repairers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-51-6041-00

APA

Singulariki. (2026). Shoe and Leather Workers and Repairers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-6041-00

BibTeX
@misc{singulariki-role-51-6041-00,
  title  = {Shoe and Leather Workers and Repairers},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
  url    = {https://singulariki.com/roles/role-51-6041-00}
}

Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.

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