Gambling Managers
In short: today's best AI models could do about 57% 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 74% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 26% of the time, stays with people.
Plan, direct, or coordinate gambling operations in a casino. May formulate house rules.
5,030 people do this job in the US. $93,220 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on23 h
- A person checks AI's work0 h
- Desk work AI can't do yet7 h
- Stays with people10 h
Gambling Managers, now: of a 40-hour week, AI could take on 23 hours, 0 hours become checking its work, 7 hours are desk work it can't do yet, and 10 hours stay with people.
The largest pieces: Establish policies on issues, such as the type of gambling offered and the odds, the extension of credit, or the serving of food and beverages (about 6 h); Market or promote the casino to bring in business (about 4 h); Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games (about 4 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.
- 74%
- 11%
- 15%
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, 25%. Today's estimate: 57%.
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 19 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0086% to 0.0092% (released February and March 2025); none to 0.0068% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0086% | 548 of 708 | 1 of 19 |
| Released March 2025 | 0.0092% | 521 of 703 | 2 of 19 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 19 |
| The week of Nov 13, 2025 (released January 2026) | 0.0064% | 542 of 672 | 2 of 19 |
| The week of Feb 5, 2026 (released March 2026) | 0.0068% | 539 of 677 | 2 of 19 |
| April 2026 (released June 2026) | none | n/a | 0 of 19 |
| May 2026 (released June 2026) | none | n/a | 0 of 19 |
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 2% of this job's working time as physical work. For 2% of the working time, a robot has been shown doing most of the task somewhere: 2% in a structured facility. 0.05 of 3, the 589th highest of the 923 jobs.
- Not physical 98%
- In a structured facility 2%
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 . 19 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Establish policies on issues, such as the type of gambling offered and the odds, the extension of credit, or the serving of food and beverages.Done daily by most who do it. | 28% | 6.7 h1.7 h to 2.5 work days | 55%Half by now | |
| Market or promote the casino to bring in business.Done daily by most who do it. | 14% | 3.3 h50 min to 1.7 work days | 71%Half by now | |
| Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games.Done daily by most who do it. | 10% | 1.7 h25 min to 5 h | 94%Half by now | |
| Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating.Done hourly or more by most who do it. | 8% | 50 min25 min to 1.7 h | Stays with people | |
| Prepare work schedules and station arrangements and keep attendance records.Done daily by most who do it. | 7% | 1.7 h50 min to 3.3 h | 100%Half by now | |
| Monitor staffing levels to ensure that games and tables are adequately staffed for each shift, arranging for staff rotations and breaks and locating substitute employees as necessary.Done daily by most who do it. | 6% | 38 min13 min to 1.7 h | 100%Half by now | |
| Train new workers or evaluate their performance.Done daily by most who do it. | 4% | 1.3 h38 min to 3.3 h | Stays with people | |
| Track supplies of money to tables and perform any required paperwork.Done daily by most who do it. | 4% | 25 min8 min to 1.3 h | Stays with people | |
| Review operational expenses, budget estimates, betting accounts, or collection reports for accuracy.Done daily by most who do it. | 3% | 1.3 h25 min to 2.5 h | 100%Half by now | |
| Direct the compilation of summary sheets that show wager amounts and payoffs for races or events.Done daily by most who do it. | 3% | 1.3 h25 min to 2.5 h | Stays with people | |
| Remove suspected cheaters, such as card counters or other players who may have systems that shift the odds of winning to their favor.Done more than yearly by most who do it. | 3% | 38 min13 min to 1.7 h | Stays with people | |
| Direct the distribution of complimentary hotel rooms, meals, or other discounts or free items given to players, based on their length of play and betting totals.Done daily by most who do it. | 2% | 25 min8 min to 1.3 h | 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.
- First-Line Supervisors of Gambling Services Workers30% now, 32% by 2028
- Gambling and Sports Book Writers and Runners26% now, 26% by 2028
- Gambling Surveillance Officers and Gambling Investigators48% now, 51% by 2028
- Lodging Managers50% now, 54% by 2028
- First-Line Supervisors of Office and Administrative Support Workers54% now, 58% by 2028
- Umpires, Referees, and Other Sports Officials15% now, 15% 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 Gambling Managers is within reach of AI now?
- An estimated 57% of the working time is within reach of AI models now and 74% by the end of 2028, on METR's long-run pace at four in five (72% to 74% across the three paces the site shows). 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 Gambling Managers 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: Establish policies on issues, such as the type of gambling offered and the odds, the extension of credit, or the serving of food and beverages (55% of the task's time now, 100% by the end of 2028); Market or promote the casino to bring in business (71% of the task's time now, 100% by the end of 2028); and Maintain familiarity with all games used at a facility, as well as strategies or tricks employed in those games (94% of the task's time now, 100% by the end of 2028).
- Which tasks of Gambling Managers stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Circulate among gaming tables to ensure that operations are conducted properly, that dealers follow house rules, or that players are not cheating; Train new workers or evaluate their performance; and Track supplies of money to tables and perform any required paperwork. Together such tasks are about 26% of the working time.
- Do people already use AI for the work of Gambling Managers?
- 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 Gambling Managers?
- Anthropic's robot exposure rating (September 2026) finds 2% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 2% of the working time, 2% in a structured facility. Its index is 0.05 of 3. One example: Self-service sports betting kiosks (KIOSK Information Systems, with JCM bill validators / thermal ticket printers) for "record, collect, or pay off bets, issuing receipts as necessary". 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 19 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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