AI exposure: Gambling Dealers
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.
Reading this score
computedAt 22.4% of weighted task load, Gambling Dealers sits at the 42th percentile, below the point where a job's centre of gravity has moved. 63.9% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 21 tasks it averages 2.19 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Compute amounts of players' wins or losses, or scan winning tickets presented by patrons to..., at 86.7%. The least is Seat patrons at gaming tables, at 0.0%. A gap of 86.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within personal care and service occupations, this one is less exposed than the median of 24.4% across the group's 31 roles, with 17 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 21 tasks, 5 are currently banded exposed, 1 assisted and 15 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 1.55 | 0-4 |
| Embodiment | 2.19 | 0-3 |
| Presence | 2.19 | 0-3 |
| Accountability | 0.98 | 0-3 |
| Context | 1.19 | 0-3 |
| Verification cost | 0.86 | 0-3 |
Task by task
21 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Compute amounts of players' wins or losses, or scan winning tickets presented by patrons to calculate the amount of money won. | 86.7% | 13.3% | 0.0% | 4.60 | exposed |
| Refer patrons to gaming cashiers to collect winnings. | 86.7% | 13.3% | 0.0% | 3.87 | exposed |
| Answer questions about game rules and casino policies. | 80.0% | 20.0% | 0.0% | 4.51 | exposed |
| Prepare collection reports for submission to supervisors. | 73.3% | 26.7% | 0.0% | 4.12 | exposed |
| Train new dealers. | 30.0% | 20.0% | 50.0% | 4.18 | exposed |
| Receive, verify, and record patrons' cash wagers. | 23.3% | 26.7% | 50.0% | 4.69 | assisted |
| Supervise staff and monitor gambling tables to ensure security of the game. | 16.2% | 21.2% | 62.5% | 4.61 | untouched |
| Greet customers and make them feel welcome. | 13.3% | 11.7% | 75.0% | 4.89 | untouched |
| Inspect cards and equipment to be used in games to ensure that they are in good condition. | 13.3% | 11.7% | 75.0% | 4.79 | untouched |
| Check to ensure that all players have placed bets before play begins. | 10.0% | 15.0% | 75.0% | 4.83 | untouched |
| Deal cards to house hands, and compare these with players' hands to determine winners, as in black jack. | 10.0% | 15.0% | 75.0% | 4.78 | untouched |
| Stand behind a gaming table and deal the appropriate number of cards to each player. | 10.0% | 15.0% | 75.0% | 4.75 | untouched |
| Apply rule variations to card games such as poker, in which players bet on the value of their hands. | 10.0% | 15.0% | 75.0% | 4.70 | untouched |
| Conduct gambling games, such as dice, roulette, cards, or keno, following all applicable rules and regulations. | 10.0% | 15.0% | 75.0% | 4.66 | untouched |
| Work as part of a team of dealers in games, such as baccarat or craps. | 10.0% | 15.0% | 75.0% | 4.63 | untouched |
| Start and control games and gaming equipment, and announce winning numbers or colors. | 10.0% | 15.0% | 75.0% | 4.61 | untouched |
| Open and close cash floats and game tables. | 10.0% | 15.0% | 75.0% | 4.51 | untouched |
| Participate in games for gambling establishments to provide the minimum complement of players at a table. | 10.0% | 15.0% | 75.0% | 4.04 | untouched |
| Pay winnings or collect losing bets as established by the rules and procedures of a specific game. | 0.0% | 0.0% | 100.0% | 4.92 | untouched |
| Exchange paper currency for playing chips or coin money. | 0.0% | 0.0% | 100.0% | 4.83 | untouched |
| Seat patrons at gaming tables. | 0.0% | 0.0% | 100.0% | 4.39 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.