Headline risk
20%
Moderate RiskBaggage porters and bellhops
United States AI Work Index tracks this occupation on the shared structural baseline and then layers on local demand resilience, wages, and confidence.
Why This Score
Share of job tasks that overlap with current AI capabilities
Median annual wage
Projected employment change over 10 years
Typical preparation needed for this occupation
Occupation profile
Handle baggage for travelers at transportation terminals or for guests at hotels or similar establishments.
Task evidence
91% weighted task match · 9% effective coverage
Scores combine AI task overlap, human advantages, and local demand. How it works
United States Now
Median Wage
USD 36,020
Employment 2024
32.5K
Projected Change (2024–34)
-1.6%
Openings (2024–34)
4.6K
Wage distribution
Demand outlook
Projections published, but no prose outlook available.
Role Profile
Tasks
- 1. Supply guests or travelers with directions, travel information, and other information, such as available services and points of interest. AI use: 100%
- 2. Transfer luggage, trunks, and packages to and from rooms, loading areas, vehicles, or transportation terminals, by hand or using baggage carts. AI use: 0%
- 3. Greet incoming guests and escort them to their rooms. AI use: 0%
- 4. Receive and mark baggage by completing and attaching claim checks. AI use: 0%
- 5. Assist travelers and guests with disabilities.
- 6. Transport guests about premises and local areas, or arrange for transportation. AI use: 0%
Technologies
Requirements
Work context
Worker profile
Median age 41.9 · 80K employed
Under 25: 9% · 25–54: 65% · 55+: 26%
Related
No direct US role match is available yet for this occupation.
Source coverage
11/11 source families · O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Mapping quality
crosswalk_exact · employment series present
Narrative & sources
Published limitations
This page shows the local country layer, not realised individual job outcomes. The global structural baseline is shared across countries; only the local demand and wage layer changes here.
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.