AI Automation Index

Will AI Replace Gambling Change Persons and Booth Cashiers?

Analyze the automation vulnerability, task-level AI risk, salary, and demand projection for Gambling Change Persons and Booth Cashiers. Run the upskilling simulator.

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• Developed & audited by Gini Loh

AI Vulnerability

54% risk score

Median Salary

$36,220 / year

Growth Demand

Low

Constituent Task Mix

We parsed O*NET's 13 constituent tasks for this occupation and classified them by AI threat risk.

High Automation Risk (Routine Tasks) 15%
Medium Automation Risk (Cognitive/Technical) 77%
Low Automation Risk (Strategy/Leadership) 8%

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constituent Tasks

Keep accurate records of monetary exchanges, authorization forms, and transaction reconciliations.

Routine cognitive or manual task with high vulnerability to automation.

Exchange money, credit, tickets, or casino chips and make change for customers.

Semi-structured task combining routine and non-routine responsibilities.

Count money and audit money drawers.

Semi-structured cognitive task involving analysis, inspection, or monitoring.

Check identifications to verify age of players.

Semi-structured task combining routine and non-routine responsibilities.

Maintain cage security according to rules.

Semi-structured task combining routine and non-routine responsibilities.

Reconcile daily summaries of transactions to balance books.

Semi-structured task combining routine and non-routine responsibilities.

Obtain customers' signatures on receipts when winnings exceed the amount held in a slot machine.

Routine cognitive or manual task with high vulnerability to automation.

Calculate the value of chips won or lost by players.

Semi-structured task combining routine and non-routine responsibilities.

Accept credit applications and verify credit references to provide check-cashing authorization or to establish house credit accounts.

Complex problem-solving, strategic leadership, or high-empathy task requiring human judgment.

Furnish change persons with a money bank at the start of each shift.

Semi-structured task combining routine and non-routine responsibilities.

Listen for jackpot alarm bells and issue payoffs to winners.

Semi-structured task combining routine and non-routine responsibilities.

Sell gambling chips, tokens, or tickets to patrons, or to other workers for resale to patrons.

Semi-structured task combining routine and non-routine responsibilities.

Clean casino areas.

Semi-structured task combining routine and non-routine responsibilities.

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O*NET Methodology

O*NET Data Source

This page dynamically extracts data structures sponsored by the U.S. Department of Labor. Our AI classification applies cognitive task automation risk models to individual tasks.

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