High AI Risk Declining

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.

AI Exposure Score
52% High

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

Projected Growth
-6.4%
2024–2034 (BLS)
-1,500 jobs
Median Annual Wage
$34,810
BLS May 2024
How wage figures are sourced →
The verdict

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.

52%
AI exposure
Top 12%
most exposed
-6.4%
Job growth 2024–34
$34,810
Median wage

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.

AI exposure distribution - Gambling change persons and booth cashiers marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 12% by AI exposure Higher AI exposure than 88% of all 832 occupations.

Gambling change persons and booth cashiers has ai exposure of 52%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

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.

Future-proofGrowing but exposedStable, lower-AIMost at risk27.4%36.2%45%53.8%62.6%-10.6%-6.8%-3.1%0.6%4.4%AI exposure (%) →Projected growth (%) →Gambling change persRetail salespersonsCashiersFirst-line supervisoSales representativeSales representativeInsurance sales agenSecuritiesReal estate sales agCounterFirst-line supervisoSales representative

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

22,600
Employment 2024
21,100
Projected 2034
-6.4%
Change (%)
-1,500
Change (jobs)

Occupation Insight

Gambling change persons and booth cashiers (SOC 41-2012) carries an AI exposure score of 52%, placing it in the High 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 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 economic context matters alongside the risk score. BLS counted approximately 22,600 workers in this occupation in 2024, and projects a -6.4% change through 2034 - a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $34,810, 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 Gambling change persons and booth cashiers. 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

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

Top Tasks (O*NET)

  1. 1. Keep accurate records of monetary exchanges, authorization forms, and transaction reconciliations.
  2. 2. Obtain customers' signatures on receipts when winnings exceed the amount held in a slot machine.
  3. 3. Calculate the value of chips won or lost by players.
  4. 4. Exchange money, credit, tickets, or casino chips and make change for customers.
  5. 5. Count money and audit money drawers.
  6. 6. Check identifications to verify age of players.
  7. 7. Maintain cage security according to rules.
  8. 8. Reconcile daily summaries of transactions to balance books.
  9. 9. Accept credit applications and verify credit references to provide check-cashing authorization or to establish house credit accounts.
  10. 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

2.6
out of 5.0

High automation risk based on 10 analyzed tasks. A moderate share of tasks may be augmented by AI tools.

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).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

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.