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AI Automation Index
Will AI Replace Amusement and Recreation Attendants?
Task-level automation exposure for Amusement and Recreation Attendants: 17 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
47%
weighted task index
17 of 17 tasks scored
Median Salary
$32,150 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Very High
397,830 people hold this job — size, not growth
Projected 2025–35
+3.7%
employment change
100,400 openings a year · BLS line item
Pay by state
BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$21,050 – $45,680
Highest medians
Alaska $45,680
Hawaii $39,920
District of Columbia $37,960
Washington $37,790
California $37,000
Lowest medians
Guam $21,050
Oklahoma $22,040
Puerto Rico $22,210
Louisiana $22,680
Mississippi $23,160
State figures come from the 39-3091 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 47%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 5%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 26%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 7%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 9/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
17 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 34%
6 tasks
Medium exposure (≥ 35%) 29%
4 tasks
Low exposure (below 35%) 37%
7 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#5119 · Core · 32% automatable
Sell tickets and collect fees from customers.
interpersonal — Closing sales requires persuasion and accountability
Sell products or services.
#5116 · Core · 56% automatable
Provide information about facilities, entertainment options, and rules and regulations.
information retrieval — AI explains policies; human handles live questions
Explain regulations, policies, or procedures. Provide attraction or event information to patrons.
#5120 · Core · 65% automatable
Keep informed of shut-down and emergency evacuation procedures.
information retrieval — AI synthesizes business info; contextual grasp is human
Maintain knowledge of business operations.
#5130 · Core · 45% automatable
Direct patrons to rides, seats, or attractions.
interpersonal — In-person directions need situated human presence
Provide patrons with directions to locales or attractions.
#5118 · Core · 50% automatable
Monitor activities to ensure adherence to rules and safety procedures, or arrange for the removal of unruly patrons.
interpersonal — Cross-staff problem resolution involves politics and trust
Monitor operational quality or safety. Communicate with management or other staff to resolve problems.
#5117 · Core · 80% automatable
Record details of attendance, sales, receipts, reservations, or repair activities.
data analysis — Maintain financial records; human reconciles exceptions
Maintain financial or account records. Prepare operational reports or records.
#5134 · Core · 72% automatable
Maintain inventories of equipment, storing and retrieving items and assembling and disassembling equipment as necessary.
data analysis — Supply inventory tracking and reorder largely automatable
Maintain supply or equipment inventories.
#5131 · Supplemental · 5% automatable
Provide assistance to patrons entering or exiting amusement rides, boats, or ski lifts, or mounting or dismounting animals.
physical manipulation — Physically assisting boarding and exiting
Assist patrons with entering or exiting vehicles or other forms of transportation.
#5121 · Supplemental · 8% automatable
Clean sporting equipment, vehicles, rides, booths, facilities, or grounds.
physical manipulation — Tool cleaning is physical manipulation
Clean facilities or work areas. Clean tools or equipment.
#5125 · Supplemental · 20% automatable
Inspect equipment to detect wear and damage and perform minor repairs, adjustments, or maintenance tasks, such as oiling parts.
visual inspection — Hands-on verification of equipment functioning
Inspect equipment to ensure proper functioning.
#5128 · Supplemental · 70% automatable
Verify, collect, or punch tickets before admitting patrons to venues, such as amusement parks and rides.
information retrieval — Credential verification via databases, human handles exceptions
Verify patron or staff credentials.
#5124 · Supplemental · 34% automatable
Fasten safety devices for patrons, or provide them with directions for fastening devices.
information retrieval — AI explains policies; human handles live questions
Explain regulations, policies, or procedures. Assist patrons with entering or exiting vehicles or other forms of transportation.
#5123 · Supplemental · 50% automatable
Announce or describe amusement park attractions to patrons to entice customers to games and other entertainment.
information retrieval — Event info retrieval assisted; patron interaction human
Provide attraction or event information to patrons.
#5133 · Supplemental · 72% automatable
Schedule the use of recreation facilities, such as golf courses, tennis courts, bowling alleys, or softball diamonds.
data analysis — AI optimizes schedules; human handles exceptions
Arrange facility schedules.
#5132 · Supplemental · 32% automatable
Sell and serve refreshments to customers.
interpersonal — Closing sales requires persuasion and accountability
Sell products or services.
#5127 · Supplemental · 30% automatable
Rent, sell, or issue sporting equipment and supplies, such as bowling shoes, golf balls, swimming suits, or beach chairs.
interpersonal — Closing sales requires persuasion and accountability
Sell products or services. Distribute resources to patrons or employees.
#5126 · Supplemental · 62% automatable
Operate, drive, or explain the use of mechanical riding devices or other automatic equipment in amusement parks, carnivals, or recreation areas.
information retrieval — AI explains policies; human handles live questions
Explain regulations, policies, or procedures.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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