How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Provide information about facilities, entertainment options, and rules and regulations.73
- Provide assistance to patrons entering or exiting amusement rides, boats, or ski lifts, or mounting or dismounting animals.73
- Keep informed of shut-down and emergency evacuation procedures.73
- Verify, collect, or punch tickets before admitting patrons to venues, such as amusement parks and rides.72
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Fasten safety devices for patrons, or provide them with directions for fastening devices.01
- Record details of attendance, sales, receipts, reservations, or repair activities.02
- Clean sporting equipment, vehicles, rides, booths, facilities, or grounds.03
- Monitor activities to ensure adherence to rules and safety procedures, or arrange for the removal of unruly patrons.04
- Inspect equipment to detect wear and damage and perform minor repairs, adjustments, or maintenance tasks, such as oiling parts.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Lifeguards, Ski Patrol, and Other Recreational Protective Service Workers
Shares some work
Compare these careers →Umpires, Referees, and Other Sports Officials
Shares some work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
