AI Delegation Index

AI Delegation Index

What work could you hand off to an AI agent?

Gambling Dealers

Low

AI agents have a narrow supporting role here, mainly helping with preparation or documentation rather than doing the physical work.

Where agents can help most

  1. 1

    Monitor table play and answer questions

    Use an agent to keep a running note of common rule questions, house policy references, and table coverage details so you can answer patrons more consistently during a shift.

  2. 2

    Train a new dealer at table

    Use an agent to build a simple training checklist from your table procedures, shift notes, and supervisor guidance for a new dealer.

  3. 3

    Prepare service records and follow-up notes

    Use an agent to turn the notes, forms, readings, and completion details you provide into a clear service record and follow-up note.

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O*NET-SOC 39-3011.00 · #712 of 923

Result context

How to read this result

Operate table games. Stand or sit behind table and operate games of chance by dispensing the appropriate number of cards or blocks to players, or operating other gambling equipment. Distribute winnings or collect players' money or chips. May compare the house's hand against players' hands.

National position
#712 of 923 occupations
Top 78% of occupations
Overall AI delegation potential
Low
Potential of score-contributing workflows
Low · 54/100
Meaningful work covered
34%

The overall rating combines how useful the best agent workflows are with how much of the occupation they address. It is not an estimate of job automation or replacement.

Recommended agent uses

3 workflows you could delegate to AI

1

Monitor table play and answer questions

How you could use an agent

Use an agent to keep a running note of common rule questions, house policy references, and table coverage details so you can answer patrons more consistently during a shift. It can also help you summarize any table problems or security concerns for the floor supervisor after the game.

Where you stay involved

You watch the table, answer routine questions, and decide when a question or behavior needs a supervisor or security staff. You keep the game moving, but you do not let the agent make calls about enforcement or game outcomes.

Review level: High

2

Train a new dealer at table

How you could use an agent

Use an agent to build a simple training checklist from your table procedures, shift notes, and supervisor guidance for a new dealer. It can help you outline the dealing order, wager handling, payout steps, and common mistakes to watch for while you coach the trainee at the table.

Where you stay involved

You show the steps, watch the trainee practice, and decide whether the person is ready for more responsibility. You stop the lesson and get help if the trainee keeps making unsafe or game-affecting mistakes.

Review level: High

3

Prepare service records and follow-up notes

Documentation support · not included in the score

How you could use an agent

Use an agent to turn the notes, forms, readings, and completion details you provide into a clear service record and follow-up note. It can organize the entries, check required fields, and flag gaps before you submit or store the record.

Where you stay involved

You perform the hands-on or in-person work, confirm that the source details are accurate, and approve the final record before it is used.

Review level: Medium

Supporting analysis

Why this occupation's AI delegation potential is Low

Underlying methodology score

47 / 100

This technical score determines the qualitative rating; it is not an estimate of the share of the occupation that can be automated.

Importance & frequency84
AI capability63
Digital actionability24
End-to-end leverage31
Safety & reversibility67
Meaningful-work coverage
34%
Physical-work modifier
Material
Safety modifier
Limited
Qualitative judgment
No material constraint
O*NET task evidence
21 tasks

O*NET 31.0 · methodology 3.3.0. Every workflow passes an action-level physical-execution and protected human-and-veterinary clinical-action gate. Documentation workflows must own a complete digital loop and use digital task evidence only; support-only workflows are disclosed separately and excluded from scoring. Artistic, editorial, normative, and policy-dependent work receives a transparent human-judgment constraint. National ranking within 923 scored O*NET occupations under methodology 3.3.0.

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