First-Line Supervisors of Gambling Services Workers
In short: today's best AI models could do about 30% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 32% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 68% of the time, stays with people.
Directly supervise and coordinate activities of workers in assigned gambling areas. May circulate among tables, observe operations, and ensure that stations and games are covered for each shift. May verify and pay off jackpots. May reset slot machines after payoffs and make repairs or adjustments to slot machines or recommend removal of slot machines for repair. May plan and organize activities and services for guests in hotels/casinos.
26,010 people do this job in the US. $63,820 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on12 h
- A person checks AI's work0 h
- Desk work AI can't do yet1 h
- Stays with people27 h
First-Line Supervisors of Gambling Services Workers, now: of a 40-hour week, AI could take on 12 hours, 0 hours become checking its work, 1 hours are desk work it can't do yet, and 27 hours stay with people.
The largest pieces: Determine how many gaming tables to open each day and schedule staff accordingly (about 3 h); Establish and maintain banks and table limits for each game (about 3 h); Maintain familiarity with the games at a facility and with strategies or tricks used by cheaters at such games (about 2 h).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 32%
- 29%
- 39%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 1%. With Claude Mythos Preview (early), measured in April 2026, 21%. Today's estimate: 30%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 30 tasks showed up. Within each of Anthropic's methods, never across a change: 0.012% to 0.023% (released February and March 2025); 0.021% to 0.044% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.012% | 507 of 708 | 3 of 30 |
| Released March 2025 | 0.023% | 394 of 703 | 1 of 30 |
| The week of Aug 4, 2025 (released September 2025) | 0.021% | 367 of 655 | 3 of 30 |
| The week of Nov 13, 2025 (released January 2026) | 0.046% | 247 of 672 | 3 of 30 |
| The week of Feb 5, 2026 (released March 2026) | 0.044% | 266 of 677 | 3 of 30 |
| April 2026 (released June 2026) | none | n/a | 0 of 30 |
| May 2026 (released June 2026) | none | n/a | 0 of 30 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 12% of this job's working time as physical work. For 9% of the working time, a robot has been shown doing most of the task somewhere: 5% in a purpose-built cell, 4% in a structured facility. 0.12 of 3, the 501st highest of the 923 jobs.
- Not physical 88%
- No robot shown 4%
- In a purpose-built cell 5%
- In a structured facility 4%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 30 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Train, supervise, schedule, and evaluate workers. | 13% | 2.5 h50 min to 5 h | Stays with people | |
| Interview and hire workers. | 9% | 1.7 h50 min to 3.3 h | Stays with people | |
| Monitor game operations to ensure that house rules are followed, that tribal, state, and federal regulations are adhered to, and that employees provide prompt and courteous service.Done hourly or more by most who do it. | 9% | 33 min13 min to 50 min | Stays with people | |
| Determine how many gaming tables to open each day and schedule staff accordingly.Done daily by most who do it. | 8% | 2.5 h50 min to 6.7 h | 96%Half by now | |
| Observe gamblers' behavior for signs of cheating, such as marking, switching, or counting cards, and notify security staff of suspected cheating.Done hourly or more by most who do it. | 7% | 25 min8 min to 38 min | Stays with people | |
| Establish and maintain banks and table limits for each game.Done hourly or more by most who do it. | 6% | 38 min13 min to 1.3 h | 100%Half by now | |
| Maintain familiarity with the games at a facility and with strategies or tricks used by cheaters at such games.Done hourly or more by most who do it. | 6% | 38 min13 min to 1.7 h | 100%Half by now | |
| Supervise the distribution of complimentary meals, hotel rooms, discounts, or other items given to players, based on length of play and amount bet.Done daily by most who do it. | 5% | 25 min8 min to 1.3 h | Stays with people | |
| Establish policies on types of gambling offered, odds, or extension of credit.Done daily by most who do it. | 3% | 6.7 h1.7 h to 2.5 work days | 55%Half by now | |
| Direct workers compiling summary sheets for each race or event to record amounts wagered and amounts to be paid to winners.Done hourly or more by most who do it. | 3% | 33 min17 min to 1.1 h | Stays with people | |
| Clean and maintain slot machines and surrounding areas.Done daily by most who do it. Robots: in a purpose-built cell, Duerr EcoRS Clean F / EcoRS Clean Brush / EcoClean (sold). Anthropic's rating. | 3% | 25 min8 min to 50 min | Stays with people | |
| Perform minor repairs or make adjustments to slot machines, resolving problems such as machine tilts and coin jams.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 13 min4 min to 38 min | Stays with people |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Gambling Managers57% now, 74% by 2028
- Gambling Change Persons and Booth Cashiers50% now, 50% by 2028
- Gambling Cage Workers44% now, 44% by 2028
- Gambling and Sports Book Writers and Runners26% now, 26% by 2028
- Gambling Dealers7% now, 7% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of First-Line Supervisors of Gambling Services Workers is within reach of AI now?
- An estimated 30% of the working time is within reach of AI models now and 32% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of First-Line Supervisors of Gambling Services Workers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Determine how many gaming tables to open each day and schedule staff accordingly (96% of the task's time now); Establish and maintain banks and table limits for each game (100% of the task's time now); and Maintain familiarity with the games at a facility and with strategies or tricks used by cheaters at such games (100% of the task's time now).
- Which tasks of First-Line Supervisors of Gambling Services Workers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Train, supervise, schedule, and evaluate workers; Interview and hire workers; and Monitor game operations to ensure that house rules are followed, that tribal, state, and federal regulations are adhered to, and that employees provide prompt and courteous service. Together such tasks are about 68% of the working time.
- Do people already use AI for the work of First-Line Supervisors of Gambling Services Workers?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of First-Line Supervisors of Gambling Services Workers?
- Anthropic's robot exposure rating (September 2026) finds 12% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 9% of the working time, 4% in a structured facility. Its index is 0.12 of 3. One example: Self-Pay Jackpot (Hard Rock Hotel & Casino Atlantic City, slot machines + ticket redemption kiosks) for "record, issue receipts for, and pay off bets". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 30 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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