Will AI replace First-Line Supervisors of Food Preparation and Serving Workers?
In theory, AI could do about 51% of the work in First-Line Supervisors of Food Preparation and Serving Workers. In practice, as of late 2025, almost no one is actually using it that way — yet.
O*NET-SOC 35-1012
How your 19 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~51%). By late 2025, real-world AI use had reached about 6% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
Don't trust a single AI-risk score here
For this job, the signals disagree sharply. AI's theoretical reach looks moderate (~51%), but real-world use is only ~6%, and how much AI "can" do shifts wildly by model — one 2026 study found the share of "high-risk" jobs swung 2.7% to 51.5% just by changing which AI did the rating. This page shows the spread instead of pretending there's one number.
See all 19 tasks, ratedBased on real task-level AI scores — click to collapse
- Perform various financial activities, such as cash handling, deposit preparation, and payroll.
- Assign duties, responsibilities, and work stations to employees in accordance with work requirements.
- Record production, operational, and personnel data on specified forms.
- Observe and evaluate workers and work procedures to ensure quality standards and service, and complete disciplinary write-ups.
- Estimate ingredients and supplies required to prepare a recipe.
- Resolve customer complaints regarding food service.
- Compile and balance cash receipts at the end of the day or shift.
- Present bills and accept payments.
- Perform personnel actions, such as hiring and firing staff, providing employee orientation and training, and conducting supervisory activities, such as creating work schedules or organizing employee time sheets.
- Control inventories of food, equipment, smallware, and liquor, and report shortages to designated personnel.
- Specify food portions and courses, production and time sequences, and workstation and equipment arrangements.
- Analyze operational problems, such as theft and wastage, and establish procedures to alleviate these problems.
- Forecast staff, equipment, and supply requirements, based on a master menu.
- Recommend measures for improving work procedures and worker performance to increase service quality and enhance job safety.
- Develop equipment maintenance schedules and arrange for repairs.
- Inspect supplies, equipment, and work areas to ensure efficient service and conformance to standards.
- Perform food preparation and serving duties, such as carving meat, preparing flambe dishes, or serving wine and liquor.
- Train workers in food preparation, and in service, sanitation, and safety procedures.
- Supervise and participate in kitchen and dining area cleaning activities.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.