Gambling change persons and booth cashiers
SOC Code: 41-2012
Gambling change persons and booth cashiers carries a 52% AI exposure score (High automation risk), with a median annual wage of $34,810 and -6.4% projected employment growth from 2024 to 2034 (BLS), affecting approximately 22,600 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 52% AI exposure, Gambling change persons and booth cashiers sits 15 points above the 37.2% average across 832 U.S. occupations - more exposed than 88% of them. Most of its core tasks still require human judgment.
Career outlook score
9/100
Gambling change persons and booth cashiers, 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 $34,810
Annual median wage, percentile rank vs all tracked occupations
- Projected growth F -6.4%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) F 52% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not 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).
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 Gambling change persons and booth cashiers in the High 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 Gambling change persons and booth cashiers sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Gambling change persons and booth cashiers sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
52% Higher than most higher than 88% 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.
Gambling change persons and booth cashiers vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Gambling change persons and booth cashiers is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Gambling change persons and booth cashiers'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 41-2012) 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 Gambling change persons and booth cashiers 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 Gambling change persons and booth cashiers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Keep accurate records of monetary exchanges, authorization forms, and transaction reconciliations.
- 2. Obtain customers' signatures on receipts when winnings exceed the amount held in a slot machine.
- 3. Calculate the value of chips won or lost by players.
- 4. Exchange money, credit, tickets, or casino chips and make change for customers.
- 5. Count money and audit money drawers.
- 6. Check identifications to verify age of players.
- 7. Maintain cage security according to rules.
- 8. Reconcile daily summaries of transactions to balance books.
- 9. Accept credit applications and verify credit references to provide check-cashing authorization or to establish house credit accounts.
- 10. Furnish change persons with a money bank at the start of each shift.
Key Skills Required
- Reading Comprehension
- Active Listening
- Speaking
- Social Perceptiveness
- Coordination
- Service Orientation
- Mathematics
- Critical Thinking
- Monitoring
- Complex Problem Solving
Knowledge Areas
- Customer and Personal Service
- Mathematics
- English Language
- Public Safety and Security
- Administrative
- Computers and Electronics
- Law and Government
- Psychology
- Economics and Accounting
- Telecommunications
Frequently Asked Questions
Will AI replace Gambling change persons and booth cashiers?
Gambling change persons and booth cashiers has an AI exposure score of 52%, 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 Gambling change persons and booth cashiers?
According to BLS Employment Projections 2024-2034, Gambling change persons and booth cashiers is projected to decline by 6.4% over the decade. Current employment stands at approximately 22,600 workers.
What skills are needed for Gambling change persons and booth cashiers?
Key skills for Gambling change persons and booth cashiers include Reading Comprehension, Active Listening, Speaking, and others. Typical entry-level education is No formal educational credential.
How much do Gambling change persons and booth cashiers earn?
The median annual wage for Gambling change persons and booth cashiers is $34,810, 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 Gambling change persons and booth cashiers?
The typical entry-level education for Gambling change persons and booth cashiers 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 Gambling change persons and booth cashiers?
Gambling change persons and booth cashiers 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
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 Gambling change persons and booth cashiers: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (52% here).
- Gambling dealers · AI exposure 52%
- Logisticians · AI exposure 52%
- Public safety telecommunicators · AI exposure 52%
- Baggage porters and bellhops · AI exposure 53%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (-6.4% here).
- Advertising sales agents · growth -6.4%
- Mechanical drafters · growth -6.5%
- Water and wastewater treatment plant and system operators · growth -6.5%
- Coil winders, tapers, and finishers · growth -6.3%
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.
Related Occupations
Showing 6 of 12 occupations with a comparable automation-risk profile.
What to do with this
Use Gambling change persons and booth cashiers' numbers above to compare, not just read in isolation.
- Compare Gambling change persons and booth cashiers side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
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).