Bartenders
Food Preparation & ServiceAI exposure
- Data source: BLSPublished: '26.08
Moderate· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: '26.03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: '25
0.26
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 76% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Exposed tasks only| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Mix ingredients, such as liquor, soda, water, sugar, and bitters, to prepare cocktails and other drinks.35-3011 | 0.007270.6 | 0.0016100.0 |
Create drink recipes.35-3011 | 0.003029.4 | —0 |
| Not observed on any surface — 18 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Collect money for drinks served. | —0 | —0 |
Check identification of customers to verify age requirements for purchase of alcohol. | —0 | —0 |
Balance cash receipts. | —0 | —0 |
Attempt to limit problems and liability related to customers' excessive drinking by taking steps such as persuading customers to stop drinking, or ordering taxis or other transportation for intoxicated patrons. | —0 | —0 |
Clean glasses, utensils, and bar equipment. | —0 | —0 |
Take beverage orders from serving staff or directly from patrons. | —0 | —0 |
Serve wine, and bottled or draft beer. | —0 | —0 |
Clean bars, work areas, and tables. | —0 | —0 |
Serve snacks or food items to customers seated at the bar. | —0 | —0 |
Ask customers who become loud and obnoxious to leave, or physically remove them. | —0 | —0 |
Slice and pit fruit for garnishing drinks. | —0 | —0 |
Arrange bottles and glasses to make attractive displays. | —0 | —0 |
Stock bar with beer, wine, liquor, and related supplies such as ice, glassware, napkins, or straws. | —0 | —0 |
Order or requisition liquors and supplies. | —0 | —0 |
Plan, organize, and control the operations of a cocktail lounge or bar. | —0 | —0 |
Supervise the work of bar staff and other bartenders. | —0 | —0 |
Plan bar menus. | —0 | —0 |
Prepare appetizers such as pickles, cheese, and cold meats. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Balance cash receipts.O*NET Task ID 2225 | 1.0 |
Create drink recipes.O*NET Task ID 2241 | 1.0 |
Order or requisition liquors and supplies.O*NET Task ID 2233 | 0.5 |
Arrange bottles and glasses to make attractive displays.O*NET Task ID 2236 | 0.5 |
Plan, organize, and control the operations of a cocktail lounge or bar.O*NET Task ID 2237 | 0.5 |
Plan bar menus.O*NET Task ID 2239 | 0.5 |
Collect money for drinks served.O*NET Task ID 2223 | 0.0 |
Check identification of customers to verify age requirements for purchase of alcohol.O*NET Task ID 2224 | 0.0 |
Attempt to limit problems and liability related to customers' excessive drinking by taking steps such as persuading customers to stop drinking, or ordering taxis or other transportation for intoxicated patrons.O*NET Task ID 2226 | 0.0 |
Clean glasses, utensils, and bar equipment.O*NET Task ID 2227 | 0.0 |
Take beverage orders from serving staff or directly from patrons.O*NET Task ID 2228 | 0.0 |
Serve wine, and bottled or draft beer.O*NET Task ID 2229 | 0.0 |
Clean bars, work areas, and tables.O*NET Task ID 2230 | 0.0 |
Mix ingredients, such as liquor, soda, water, sugar, and bitters, to prepare cocktails and other drinks.O*NET Task ID 2231 | 0.0 |
Serve snacks or food items to customers seated at the bar.O*NET Task ID 2232 | 0.0 |
Ask customers who become loud and obnoxious to leave, or physically remove them.O*NET Task ID 2234 | 0.0 |
Slice and pit fruit for garnishing drinks.O*NET Task ID 2235 | 0.0 |
Supervise the work of bar staff and other bartenders.O*NET Task ID 2238 | 0.0 |
Prepare appetizers such as pickles, cheese, and cold meats.O*NET Task ID 2240 | 0.0 |
Stock bar with beer, wine, liquor, and related supplies such as ice, glassware, napkins, or straws.O*NET Task ID 18735 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
Occupation information
Recent Changes Affecting This Occupation
May 2026: Anthropic observed-exposure score: 0% (physical/in-person). Zero observed exposure. Physical/in-person work — AI deployment effectively absent.
[Source: Anthropic Economic Research (Massenkoff & McCrory, 2026)]