# Will food service supervisors be replaced by AI? Updated October 2026 Food service supervisors score 41 of 100 for AI exposure. The largest share of their task time, 70%, is work AI speeds up while they stay in charge. AI can take over 8% outright, and 22% stays with people. - **8%** AI can do it - **70%** AI helps - **22%** Needs a person Moderate exposure Higher than 55% of the 923 occupations we scored. ## Task by task We graded 26 tasks, listed here from most to least exposed. AI can do 3 of them today, speeds up 18 and leaves 5 to people. | Task | AI exposure | | --- | --- | | Record production, operational, and personnel data on specified forms. Recording production and personnel data is routine data entry. | 80% AI can do it | | Estimate ingredients and supplies required to prepare a recipe. Recipe scaling and ingredient estimates are routine calculations. | 75% AI can do it | | Schedule parties and take reservations. Online booking and reservation tools handle most scheduling digitally. | 65% AI can do it | | Forecast staff, equipment, and supply requirements, based on a master menu. Forecasting from sales and menu data suits AI, with review. | 60% AI helps | | Compile and balance cash receipts at the end of the day or shift. POS software reconciles totals; physical cash counting remains manual. | 58% AI helps | ## How food service supervisors compare All occupations (923) Food preparation and serving (16) **Food service supervisors score 41**, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 25 for food preparation and serving. ## Pay and outlook in the US Median pay $44,080 a year, May 2025 People employed 1.2 million in the US, May 2025 Projected change in jobs +5.4% from 2024 to 2034 ## Skills to build - Record production and personnel data in Microsoft Excel - Run shift staffing and forecasts from sales data in Excel - Reconcile end-of-shift cash counts in Intuit QuickBooks Point of Sale - Train crews on sanitation and safety procedures hands-on - Inspect equipment and work areas on the floor in person - Pick and approve supplier orders in Compris software ## Safer roles nearby 5 related occupations with lower scores. - [Farm supervisors28 out of 100](https://www.aigentcy.com/ai-exposure/farm-supervisors/) - [Transportation supervisors37 out of 100](https://www.aigentcy.com/ai-exposure/transportation-supervisors/) - [Warehouse supervisors40 out of 100](https://www.aigentcy.com/ai-exposure/warehouse-supervisors/) - [Logistics supervisors39 out of 100](https://www.aigentcy.com/ai-exposure/logistics-supervisors/) - [Chefs36 out of 100](https://www.aigentcy.com/ai-exposure/chefs/) ## Questions about food service supervisors and AI Will AI replace food service supervisors? Partly. About 4 in 10 working hours go to tasks AI can already do, mostly recording production and personnel data and estimating ingredients and supplies. Guest greeting, floor inspection, cleaning oversight and training on hands-on work stay with supervisors because they need a person on the floor and in the kitchen. Which food service supervisor tasks is AI taking over? Recording production and personnel data scores 80 on exposure and is marked for automation, since it is routine data entry. Ingredient and supply estimates score 75 because recipe scaling is routine arithmetic. Reservation scheduling scores 65 because online booking tools handle most of it digitally. Which food service supervisor tasks stay with people? Greeting and seating guests scores 5 on exposure because it is in-person hospitality work. Carving, flambe, and wine service score 5 as hands-on physical tasks. Inspecting equipment and work areas scores 15 because it requires physical presence on site. How do food service supervisors stay valuable as AI takes over paperwork? Spend the hours freed from data entry on floor supervision, hands-on training, and inspections. Check AI-built forecasts against your sales history in Excel before ordering. Lead sanitation and safety demonstrations in person, and keep cash counts and POS reports accurate in QuickBooks Point of Sale. ## Related jobs - [Recreation supervisors42 out of 100](https://www.aigentcy.com/ai-exposure/recreation-supervisors/) - [Housekeeping supervisors42 out of 100](https://www.aigentcy.com/ai-exposure/housekeeping-supervisors/) - [Sales supervisors48 out of 100](https://www.aigentcy.com/ai-exposure/sales-supervisors/) - [Production supervisors43 out of 100](https://www.aigentcy.com/ai-exposure/production-supervisors/) ## Next steps for food service supervisors - ### Check your job Your job title is a rough guide. Your actual tasks decide your score. Paste your job description or CV and see which of your tasks AI can do. [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/) ### Check which roles in your team AI can take on We map your team's tasks, show what AI can do today and build the automations that pay back first. [Book an AI audit](https://www.aigentcy.com/audit/) ## Related topics - [**Jobs AI can't replace**Cement masons score lowest, at 8.](https://www.aigentcy.com/ai-exposure/jobs-ai-cant-replace/) - [**Jobs most at risk from AI**Proofreaders score highest, at 76.](https://www.aigentcy.com/ai-exposure/jobs-most-exposed-to-ai/) - [**High-paying jobs with low AI exposure**Radiologists earn a median $420,860 and score 46.](https://www.aigentcy.com/ai-exposure/high-paying-jobs-low-ai-exposure/) - [**Entry-level jobs with low AI exposure**Cement masons need little prior training and score 8.](https://www.aigentcy.com/ai-exposure/entry-level-jobs-low-ai-exposure/) - [**Jobs AI speeds up the most**For natural sciences managers, AI speeds up 96% of task time.](https://www.aigentcy.com/ai-exposure/jobs-ai-speeds-up/) - [**AI and jobs in Malta**15 iGaming roles graded task by task.](https://www.aigentcy.com/ai-exposure/malta/) - [**Skills that keep work human**The skills to build in the jobs AI changes least.](https://www.aigentcy.com/ai-exposure/skills/) - [**Jobs A to Z**Every job we publish, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/) - [**AI exposure by industry**Average scores for 22 occupation groups.](https://www.aigentcy.com/ai-exposure/industries/) - [**Write a CV screening software can read**How applicant tracking systems read a CV, and what to change.](https://www.aigentcy.com/ai-exposure/cv-screening-guide/) - [**AI for businesses**The tasks to automate first in each team and industry.](https://www.aigentcy.com/ai-for/) - [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/) Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.