Helpers, construction trades, all other
SOC Code: 47-3019
Helpers, construction trades, all other carries a 35% AI exposure score (Medium automation risk), with a median annual wage of $40,760 and +4.4% projected employment growth from 2024 to 2034 (BLS), affecting approximately 26,300 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
AI Exposure vs Industry Growth
Total occupations tracked
832
Covering all SOC major groups
Data currency
2024
BLS Employment Projections
AI exposure avg
40%
Fleet-wide median across all roles
Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.
Employment Projections
Occupation Insight
Helpers, construction trades, all other (SOC 47-3019) carries an AI exposure score of 35%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 26,300 workers in this occupation in 2024, and projects a +4.4% change through 2034 — modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $40,760, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires No formal educational credential, plus None of related experience.
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 Helpers, construction trades, all other. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.
Education & Entry Requirements
Frequently Asked Questions
Will AI replace Helpers, construction trades, all other?
Helpers, construction trades, all other has an AI exposure score of 35%, 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 Helpers, construction trades, all other?
According to BLS Employment Projections 2024-2034, Helpers, construction trades, all other is projected to grow by 4.4% over the decade. Current employment stands at approximately 26,300 workers.
What skills are needed for Helpers, construction trades, all other?
Helpers, construction trades, all other requires a combination of technical knowledge and interpersonal skills. Typical education requirement: No formal educational credential.
How much do Helpers, construction trades, all other earn?
The median annual wage for Helpers, construction trades, all other is $40,760, 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 Helpers, construction trades, all other?
The typical entry-level education for Helpers, construction trades, all other is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Helpers, construction trades, all other?
Helpers, construction trades, all other 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
Medium automation risk based on O*NET task analysis. Most tasks require human judgment and are resistant to automation.
Related Occupations
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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).