Industries associated with Shoe and leather workers and repairers in Maryland sent mixed signals in January to March 2026. Employment in these industries fell 1.0% year over year, compared with a 1.1% decline nationally. The number of establishments rose 0.2% year over year, compared with a 1.3% increase nationally. Average weekly wages across these industries rose 2.2% year over year, compared with a 5.4% increase nationally.
BLS QCEW data for January to March 2026 covers at least 21.05% of the published industry mix for Shoe and leather workers and repairers in Maryland. These are weighted industry-level signals, not direct measures of Shoe and leather workers and repairers jobs, current openings, or pay.
Limited local data: at least one local trend covers only 21.05% of this occupation's industry mix. These figures describe the industries with published data. Read each trend alongside its state data coverage.
Limited industry data for shoe and leather workers and repairers in Maryland
In early 2026, employment in the available industry data was down 1.0% from a year earlier, compared with a 1.1% decline nationwide.
These are industry-wide trends, not a count of jobs in this occupation or current openings.
Recent statewide layoff-notice context alongside the published BLS figures below. This signal does not feed the Job Market Health score.
Statewide layoff-notice filings
Maryland statewide
31 notices in this source
Notice dates from Aug 5, 2026 to Nov 2, 2026 (UTC), a rolling 90-calendar-day period.
What this means: These are statewide totals from notices dated in this period in Maryland’s official tracking system. Reported positions are the counts published in those notices, not a count of people confirmed to have lost their jobs. No employer is identified.
Notices describe planned workforce changes, not confirmed job losses. Notices may be amended or withdrawn. This statewide context is not occupation-specific and does not affect the Job Market Health score. Maryland’s state tracking system also records smaller Rapid Response events that fall below federal WARN thresholds, so it is not a list of federal WARN filings only.
Recent hiring-demand context · separate from the health score
89.0Postings index · February 1, 2020 = 100Observation: Oct 23, 2026
-11.0%Versus the February 2020 baseline
+1.8%Change over about four weeksSep 25, 2026 to Oct 23, 2026
This is statewide demand across all occupations, not demand for this specific job. Postings are not a count of vacancies or hires, and Indeed does not cover the entire labor market.
Source: Indeed Hiring Lab · CC BY 4.0. Seven-day average, seasonally adjusted; publisher refreshes weekly and may revise history. Retrieved Nov 1, 2026 · saved source copy. JobMarketHealth calculates the displayed changes and samples weekly observations for the chart.
-1.0%Industry employmentU.S. -1.1%State data coverage: 21.05%
+0.2%EstablishmentsU.S. +1.3%State data coverage: 21.05%
+2.2%Avg. weekly industry wageU.S. +5.4%State data coverage: 21.05%
35,826Represented establishmentsEstablishments in the industries that employ this occupation, not employers hiring itIndustry mix share 90.8%, separate from the data coverage on the trend cards
Industry employment change over time
Year-over-year change for the industries that employ Shoe and leather workers and repairers in Maryland · percentage change
Year-over-year employment change (%) by reference quarter
Latest published values
Maryland · 2026 Q1Not published
The chart will load automatically. Published values remain available in this report.
Every published quarter
BLS does not publish a national quarterly series for this occupation’s industry mix, so only the Maryland series is shown. The U.S. figure on the cards above is the latest quarter benchmark.
Quarterly year-over-year industry employment change for Shoe and leather workers and repairers in Maryland, with the published state data coverage for each quarter
Quarter
Maryland
State data coverage
2024 Q2
-0.2%
100%
2024 Q3
-0.5%
100%
2024 Q4
-0.2%
100%
2025 Q1
-0.6% Below coverage floor
21.05%
2025 Q2
+0.5%
100%
2025 Q3
-0.6%
100%
2025 Q4
+0.1%
100%
2026 Q1
-1.0% Below coverage floor
21.05%
Industry mix behind this view
Which industries are weighted into this view. Not a ranking of employers or of job quality.
Industries weighted into the local context for Shoe and leather workers and repairers in Maryland
The publication date above is the official BLS news release date for this reference quarter, linked to the notice. The values match the snapshot independently checked against BLS sources on September 17, 2026. The publication date identifies the quarterly news release, not the exact revision date. The data period above is the quarter the figures describe.
QCEW describes the industries that employ this occupation, not the occupation itself. It is not a count of job openings and is not part of the 0-100 Job Market Health score.
Evidence record
Derived by JobMarketHealth from BLS QCEW + published occupation industry mix. This is occupation-weighted industry context, not direct occupation employment and not a count of current job openings.
Occupation
Shoe and leather workers and repairers
SOC code
51-6041
State
Maryland
QCEW release label
QCEW 2026 Q1
Data period
2026 Q1
State industry employment, year over year
-1.0%State data coverage 21.05%
U.S. benchmark, year over year
-1.1%
Difference from U.S. benchmark
+0.1 percentage pointsPercentage-point gaps use the original published values and are rounded once; subtracting the rounded percentages can give a slightly different result.
Establishments, year over year
+0.2%State data coverage 21.05%
Average weekly industry wage, year over year
+2.2%State data coverage 21.05%
Industry mix vintage
EP-2025-2035
BLS publication date
Aug 28, 2026
Source verification
Verified against the committed source snapshotVerified Sep 17, 2026
How AI relates to Shoe and leather workers and repairers work
Across 4 research exposure measures, Shoe and leather workers and repairers is in the lower technical AI exposure band based on the mean of the available source-specific percentile ranks. Exposure describes how much of the work the studied AI capabilities could technically assist with; it is not a forecast of job loss.
The saved Anthropic task-exposure benchmark records a zero index for this occupation. This is not proof of no AI use; the observation window is not recorded in this saved release.
JobMarketHealth has not measured an AI effect on this occupation's employment or wages, and these figures do not enter its scores; there is no clear evidence of displacement in the data shown here.
Technical AI exposureLower exposureMean of 4 available source-specific percentile ranks (4 measures checked); fixed exposure bands, not a national rank of the compositeDated Claude task exposureLower thirdObserved task-exposure benchmark 0.000; observation window not recordedBusiness AI use (BTOS Core)24.6%U.S. businesses using AI, two weeks ending 2026-10-04; all industries, not this occupationHistorical task mix (2025)Not enough tasksFewer than 3 observed tasksMeasured labor-market effectNot estimatedJobMarketHealth does not attribute employment or wage changes to AI
Exposure measures (kept separate)
GPTs are GPTs exposure (β, GPT-4 rated): 0.06 of 1, national percentile 13 (lower third)
Microsoft AI applicability: 0.05 of 1, national percentile 11 (lower third)
OECD AI Capability Gap (lower gap = higher potential exposure): gap 1.9 of 23, national percentile 74 (higher third)
OECD capability gap by domain
As published by the OECD: the gap between what the occupation demands (0-5) and current AI capability in each domain. A lower gap means AI is closer to the requirement (higher potential exposure); 0 means AI already meets it or the domain is not relevant.
Language: gap 0.00 (demand 1.75 of 5)
Social interaction: gap 0.00 (demand 2.00 of 5)
Problem solving: gap 0.00 (demand 2.00 of 5)
Creativity: gap 0.00 (demand 2.00 of 5)
Metacognition & critical thinking: gap 0.00 (demand 2.00 of 5)
Knowledge, learning & memory: gap 0.00 (demand 2.70 of 5)
Vision: gap 0.70 (demand 3.70 of 5)
Manipulation: gap 1.85 (demand 3.85 of 5)
Robotic intelligence: gap 0.75 (demand 2.75 of 5)
National context: what businesses used generative AI for
From the Census 2025-26 BTOS AI Supplement (all industries; businesses whose employees used generative AI). Census did not measure Shoe and leather workers and repairers specifically.
Writing or editing documents, emails, or communications: 85.4%
Searching for information or technical help: 49.9%
Interpreting, analyzing, translating, or summarizing documents: 44.6%
Information processing, paperwork, or filing: 34.7%
Maryland context
In the Census BTOS core AI-use question, an estimated 29.4% of Maryland employer businesses reported using AI in the two weeks ending 2026-10-04 (U.S.: 24.6%).
Separately, the one-time 2025-26 BTOS AI Supplement (collected 2025-11-17 to 2026-02-08) found 19.9% of Maryland businesses using AI at that time, and 22.2% reporting that employees used generative AI for work tasks in the prior six months. It describes how AI was being used then, not a trend.
Using each occupation's exposure band and Maryland employment weights (OEWS May 2025), 32.4% of covered jobs are in occupations in the higher-exposure band. This describes the state's occupation mix, not a measured AI effect.
Exposure and observed usage are separate measures and neither equals job loss. Census BTOS figures are business-level surveys and are not occupation-specific. Sources: GPTs are GPTs occupation exposure; Microsoft Working with AI: AI applicability; AI Occupational Exposure (AIOE); OECD AI Exposure Measure (AI Capability Gap); Anthropic Economic Index; Census BTOS Core AI Use; Census BTOS AI Supplement 2025-26. These figures do not affect Job Market Health scores. Explore AI & Jobs · How we use AI data.
How to read this page
QCEW measures employment and wages by industry, not by occupation. We weight those industry conditions using the published industry mix for Shoe and leather workers and repairers. These figures describe the industries that employ Shoe and leather workers and repairers; they are not direct counts of people working in the occupation or of jobs currently open. This page is not part of the national 0 to 100 Job Market Health score.
Compare Maryland with other statesPublished industry employment, business locations and average weekly industry wages for up to three states, with the national benchmark in percentage points.
Shoe and leather workers and repairers in other states
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