High AI Risk Slow Growth

Gambling cage workers

SOC Code: 43-3041

Gambling cage workers carries a 60% AI exposure score (High automation risk), with a median annual wage of $36,990 and -5.0% projected employment growth from 2024 to 2034 (BLS), affecting approximately 14,100 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
60% High
High exposure

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

Projected Growth
-5.0%
Below typical growth
2024–2034 (BLS)
-700 jobs
Median Annual Wage
$36,990
Bottom 10% pay
BLS May 2024
How wage figures are sourced →
The verdict

At 60% AI exposure, Gambling cage workers sits 23 points above the 37.2% average across 832 U.S. occupations - more exposed than 94% of them. Most of its core tasks still require human judgment.

60%
AI exposure
Top 6%
most exposed
-5.0%
Job growth 2024–34
$36,990
Median wage
F

Career outlook score

10/100

Gambling cage workers, 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 $36,990

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -5.0%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) F 60% exposure

    Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure

Employment vs AI 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).

4.3M
Home health and personal care aides employment (#1)
#392
Home health and personal care aides AI rank
95%
Bookkeeping, accounting, and auditing clerks AI exposure (#1)
#17
Bookkeeping, accounting, and auditing clerks employment rank

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 cage workers in the High band.

Credential × growth standing

Open entry with non-declining BLS pace

Gambling cage workers keeps an HS / some college bar (333 of 832) and sits in Slow growth (245 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.

Where Gambling cage workers 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 cage workers sits by AI exposure

AI-exposure score distribution across U.S. occupations (O*NET task analysis)

60% Higher than most higher than 94% 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 cage workers vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Gambling cage workers is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk34.1%50.1%66%82.0%97.9%-8.3%-5.0%-1.8%1.5%4.8%AI exposure (%) →Projected growth (%) →Gambling cage worker, AI exposure (%) →: 60% · Projected growth (%) →: -5%Gambling cage workerCustomer service rep, AI exposure (%) →: 56% · Projected growth (%) →: -5.5%Customer service repOffice clerks, AI exposure (%) →: 84% · Projected growth (%) →: -6.7%Office clerksSecretaries, AI exposure (%) →: 77% · Projected growth (%) →: -1.6%SecretariesBookkeeping, AI exposure (%) →: 95% · Projected growth (%) →: -5.8%BookkeepingFirst-line superviso, AI exposure (%) →: 55% · Projected growth (%) →: -0.3%First-line supervisoReceptionists, AI exposure (%) →: 76% · Projected growth (%) →: 0%ReceptionistsShipping, AI exposure (%) →: 60% · Projected growth (%) →: -7.7%ShippingMedical secretaries, AI exposure (%) →: 80% · Projected growth (%) →: 4.2%Medical secretariesExecutive secretarie, AI exposure (%) →: 83% · Projected growth (%) →: -1.6%Executive secretarieBilling, AI exposure (%) →: 88% · Projected growth (%) →: -0.4%BillingProduction, AI exposure (%) →: 69% · Projected growth (%) →: -1.8%Production

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

Employment Projections

14,100
Employment 2024
13,400
Projected 2034
-5.0%
Change (%)
-700
Change (jobs)

Where This Score Comes From

Gambling cage workers'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 43-3041) 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 cage workers 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 cage workers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.

Education & Entry Requirements

Typical Education
High school diploma or equivalent
Work Experience
None
On-the-Job Training
Short-term on-the-job training

Top Tasks (O*NET)

  1. 1. Maintain confidentiality of customers' transactions.
  2. 2. Follow all gaming regulations.
  3. 3. Prepare bank deposits, balancing assigned funds as necessary.
  4. 4. Maintain cage security.
  5. 5. Cash checks and process credit card advances for patrons.
  6. 6. Supply currency, coins, chips, or gaming checks to other departments as needed.
  7. 7. Prepare reports, including assignment of company funds or recording of department revenues.
  8. 8. Convert gaming checks, coupons, tokens, or coins to currency for gaming patrons.
  9. 9. Record casino exchange transactions, using cash registers.
  10. 10. Count funds and reconcile daily summaries of transactions to balance books.

Key Skills Required

  • Speaking
  • Active Listening
  • Mathematics
  • Reading Comprehension
  • Writing
  • Critical Thinking
  • Monitoring
  • Social Perceptiveness
  • Service Orientation
  • Time Management

Knowledge Areas

  • Customer and Personal Service
  • Mathematics
  • English Language
  • Administration and Management
  • Administrative
  • Economics and Accounting
  • Computers and Electronics
  • Public Safety and Security
  • Sales and Marketing
  • Personnel and Human Resources

Frequently Asked Questions

Will AI replace Gambling cage workers?

Gambling cage workers has an AI exposure score of 60%, 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 cage workers?

According to BLS Employment Projections 2024-2034, Gambling cage workers is projected to decline by 5.0% over the decade. Current employment stands at approximately 14,100 workers.

What skills are needed for Gambling cage workers?

Key skills for Gambling cage workers include Speaking, Active Listening, Mathematics, and others. Typical entry-level education is High school diploma or equivalent.

How much do Gambling cage workers earn?

The median annual wage for Gambling cage workers is $36,990, 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 cage workers?

The typical entry-level education for Gambling cage workers is High school diploma or equivalent. 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 cage workers?

Gambling cage workers 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

3.0
out of 5.0

High automation risk based on 10 analyzed tasks. A majority of tasks in this occupation are susceptible to AI automation.

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Gambling cage workers: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (60% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-5.0% here).

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.

What to do with this

Use Gambling cage workers' numbers above to compare, not just read in isolation.

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).

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.

Sources: BLS Employment Projections 2024-2034, O*NET Database 30.0.