Will AI replace Dining Room and Cafeteria Attendants and Bartender Helpers?
Most of the work in Dining Room and Cafeteria Attendants and Bartender Helpers still leans on things AI struggles with — research rates its theoretical AI reach at only ~0%, and real-world use lower still.
O*NET-SOC 35-9011
How your 16 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 relatively low share of this job's tasks (~0%). By late 2025, real-world AI use had caught up to about 0% 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.
The signals here line up
Theoretical reach (~0%), real-world use (~0%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 16 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- No tasks in this middle tier.
- Run cash registers.
- Serve ice water, coffee, rolls, or butter to patrons.
- Scrape and stack dirty dishes and carry dishes and other tableware to kitchens for cleaning.
- Wipe tables or seats with dampened cloths or replace dirty tablecloths.
- Set tables with clean linens, condiments, or other supplies.
- Greet and seat customers.
- Clean up spilled food or drink or broken dishes and remove empty bottles and trash.
- Maintain adequate supplies of items, such as clean linens, silverware, glassware, dishes, or trays.
- Locate items requested by customers.
- Fill beverage or ice dispensers.
- Carry food, dishes, trays, or silverware from kitchens or supply departments to serving counters.
- Perform serving, cleaning, or stocking duties in establishments, such as cafeterias or dining rooms, to facilitate customer service.
- Carry trays from food counters to tables for cafeteria patrons.
- Stock cabinets or serving areas with condiments and refill condiment containers.
- Serve food to customers when waiters or waitresses need assistance.
- Clean and polish counters, shelves, walls, furniture, or equipment in food service areas or other areas of restaurants and mop or vacuum floors.
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.