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.
- Compile and balance cash receipts at the end of the day or shift.75
- Perform food preparation and serving duties, such as carving meat, preparing flambe dishes, or serving wine and liquor.75
- Assign duties, responsibilities, and work stations to employees in accordance with work requirements.75
- Record production, operational, and personnel data on specified forms.75
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.
- Supervise and participate in kitchen and dining area cleaning activities.01
- Develop equipment maintenance schedules and arrange for repairs.02
- Inspect supplies, equipment, and work areas to ensure efficient service and conformance to standards.03
- Compile and balance cash receipts at the end of the day or shift.04
- Estimate ingredients and supplies required to prepare a recipe.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
First-Line Supervisors of Housekeeping and Janitorial Workers
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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.
