Lodging Managers
ManagementAI exposure
- Data source: BLSPublished: 2026-08
High· 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: 2026-03
0.121
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.37
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, 53% 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
Show 17 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Develop and implement policies and procedures for the operation of a department or establishment.11-9081 | 0.017761.2 | 0.002911.6 |
Answer inquiries pertaining to hotel policies and services, and resolve occupants' complaints.11-9081 | 0.006522.5 | 0.012650.4 |
Monitor the revenue activity of the hotel or facility.11-9081 | 0.00175.9 | 0.00239.2 |
Prepare required paperwork pertaining to departmental functions.11-9081 | 0.00155.2 | —0 |
Meet with clients to schedule and plan details of conventions, banquets, receptions and other functions.11-9081 | 0.00155.2 | —0 |
Show, rent, or assign accommodations. | —0 | 0.004518.0 |
Coordinate front-office activities of hotels or motels, and resolve problems. | —0 | 0.002710.8 |
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 |
|---|---|
Prepare required paperwork pertaining to departmental functions.O*NET Task ID 1117 | 1.0 |
Greet and register guests.O*NET Task ID 1104 | 0.5 |
Answer inquiries pertaining to hotel policies and services, and resolve occupants' complaints.O*NET Task ID 1105 | 0.5 |
Assign duties to workers, and schedule shifts.O*NET Task ID 1106 | 0.5 |
Coordinate front-office activities of hotels or motels, and resolve problems.O*NET Task ID 1107 | 0.5 |
Participate in financial activities, such as the setting of room rates, the establishment of budgets, and the allocation of funds to departments.O*NET Task ID 1108 | 0.5 |
Manage and maintain temporary or permanent lodging facilities.O*NET Task ID 1111 | 0.5 |
Observe and monitor staff performance to ensure efficient operations and adherence to facility's policies and procedures.O*NET Task ID 1112 | 0.5 |
Show, rent, or assign accommodations.O*NET Task ID 1114 | 0.5 |
Develop and implement policies and procedures for the operation of a department or establishment.O*NET Task ID 1115 | 0.5 |
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