# Food Service Managers

> Plan, direct, or coordinate activities of an organization or department that serves food and beverages.

- **SOC code:** 11-9051.00
- **Canonical URL:** https://singulariki.com/roles/role-11-9051-00
- **Also known as:** F and B Manager (Food and Beverage Manager), Food Service Director, Food Service Manager, Restaurant Manager, Banquet Manager, CDM (Certified Dietary Manager), Catering Manager, Dining Service Director
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Monitor employee and patron activities to ensure liquor regulations are obeyed.
- Greet guests, escort them to their seats, and present them with menus and wine lists.
- Count money and make bank deposits.
- Establish standards for personnel performance and customer service.
- Keep records required by government agencies regarding sanitation or food subsidies.
- Schedule staff hours and assign duties.
- Investigate and resolve complaints regarding food quality, service, or accommodations.
- Maintain food and equipment inventories, and keep inventory records.
- Perform some food preparation or service tasks, such as cooking, clearing tables, and serving food and drinks when necessary.
- Monitor budgets and payroll records, and review financial transactions to ensure that expenditures are authorized and budgeted.
- Schedule and receive food and beverage deliveries, checking delivery contents to verify product quality and quantity.
- Coordinate assignments of cooking personnel to ensure economical use of food and timely preparation.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Administration and Management _(knowledge)_
- Food Production _(knowledge)_
- Active Listening _(essential_skill)_
- Speaking _(essential_skill)_
- Monitoring _(essential_skill)_
- Coordination _(transferable_skill)_
- Management of Personnel Resources _(transferable_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_

**Skills in demand:**
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Critical Thinking _(Common Skill)_
- English Language _(Common Skill)_
- Time Management _(Common Skill)_
- Mathematics _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Negotiation _(Common Skill)_
- Learning Strategies _(Specialized Skill)_
- Instructing _(Specialized Skill)_

**Tools & technology:**
- Microsoft Office software _(hot technology, in demand)_
- Facebook _(hot technology)_
- Google Docs _(hot technology)_
- Intuit QuickBooks _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Word _(hot technology)_
- Aestiva Employee Time Clock
- Apache Groovy
- Army Food Management Information System

## AI exposure & outlook

- **AI task-overlap index:** 42nd percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 45th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 61st percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 27th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 27th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 6.4% growth (About average); 42k annual openings; 352.8k → 375.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $65,310; 244,230 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 46% automation, — augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Investigate and resolve complaints regarding food quality, service, or accommodations. _(0.4% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me investigate and resolve complaints regarding food quality, service, or accommodations.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-11-9051-00_