Gambling Dealers
Gambling Dealers — AI exposure, safer roles, and a pivot plan.
Also known as: Card Dealer · Card Grader · Crap Shooter · Casino Dealer · Casino Worker · Big Six Dealer
This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.
Most exposed tasks
Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.
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Compute amounts of players' wins or losses, or scan winning tickets presented by patrons to calculate the amount of money won.69
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Refer patrons to gaming cashiers to collect winnings.64
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Receive, verify, and record patrons' cash wagers.63
Augmentable tasks
Work where AI assists rather than replaces — the productivity frontier of this role.
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Greet customers and make them feel welcome.49
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Pay winnings or collect losing bets as established by the rules and procedures of a specific game.46
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Exchange paper currency for playing chips or coin money.46
Most durable tasks
Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.
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Prepare collection reports for submission to supervisors.26
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Seat patrons at gaming tables.30
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Supervise staff and monitor gambling tables to ensure security of the game.32
Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.
What this means
A score of 45 puts Gambling Dealers in the second quartile of analyzed occupations. In practice, exposure this level is about the mix: 3 of 20 analyzed tasks lean automatable, 14 augmentable, and 3 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.
One next move: adopt AI deliberately on the augmentable tasks and build visible evidence of the durable ones.
Lower-exposure adjacent roles
No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.
Labor-market context
- $34,320median wage
- 83,910employed
- 14,100annual openings
- -0.7%projected growth
Context only — labor statistics are not inputs to the exposure score. See methodology.
Your week probably doesn’t match the average
This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.
Personalize my result — $9Related roles
Adjacent by skills or family — no exposure claim implied.
FAQ — Gambling Dealers
- What does a score of 45 mean for a Gambling Dealers?
- It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 45 on a 0–100 exposure scale — in the second quartile of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
- Which tasks in this role are most exposed to AI?
- The highest-exposure tasks are: Compute amounts of players' wins or losses, or scan winning tickets presented by patrons to calculate the amount of money won; Refer patrons to gaming cashiers to collect winnings; Receive, verify, and record patrons' cash wagers. Exposure is scored per task from structured data, not generated by a language model.
- Which parts of this job are most durable?
- The most durable responsibilities are: Prepare collection reports for submission to supervisors; Seat patrons at gaming tables; Supervise staff and monitor gambling tables to ensure security of the game. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
- Is this score personalized to me?
- No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.
Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology