Will AI replace Waiters and Waitresses?
Most of the work in Waiters and Waitresses still leans on things AI struggles with — research rates its theoretical AI reach at only ~18%, and real-world use lower still.
O*NET-SOC 35-3031
How your 24 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 (~18%). By late 2025, real-world AI use had reached 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 (~18%), 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 24 tasks, ratedBased on real task-level AI scores — click to collapse
- Write patrons' food orders on order slips, memorize orders, or enter orders into computers for transmittal to kitchen staff.
- Explain how various menu items are prepared, describing ingredients and cooking methods.
- Prepare checks that itemize and total meal costs and sales taxes.
- Present menus to patrons and answer questions about menu items, making recommendations upon request.
- Inform customers of daily specials.
- Describe and recommend wines to customers.
- Provide guests with information about local areas, including directions.
- Take orders from patrons for food or beverages.
- Check with customers to ensure that they are enjoying their meals, and take action to correct any problems.
- Check patrons' identification to ensure that they meet minimum age requirements for consumption of alcoholic beverages.
- Collect payments from customers.
- Remove dishes and glasses from tables or counters, and take them to kitchen for cleaning.
- Serve food or beverages to patrons, and prepare or serve specialty dishes at tables as required.
- Clean tables or counters after patrons have finished dining.
- Prepare tables for meals, including setting up items such as linens, silverware, and glassware.
- Assist host or hostess by answering phones to take reservations or to-go orders, and by greeting, seating, and thanking guests.
- Escort customers to their tables.
- Perform cleaning duties, such as sweeping and mopping floors, vacuuming carpet, tidying up server station, taking out trash, or checking and cleaning bathroom.
- Prepare hot, cold, and mixed drinks for patrons, and chill bottles of wine.
- Roll silverware, set up food stations, or set up dining areas to prepare for the next shift or for large parties.
- Stock service areas with supplies such as coffee, food, tableware, and linens.
- Bring wine selections to tables with appropriate glasses, and pour the wines for customers.
- Fill salt, pepper, sugar, cream, condiment, and napkin containers.
- Perform food preparation duties, such as preparing salads, appetizers, and cold dishes, portioning desserts, and brewing coffee.
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.