# First-Line Supervisors of Housekeeping and Janitorial Workers

> Directly supervise and coordinate work activities of cleaning personnel in hotels, hospitals, offices, and other establishments.

- **SOC code:** 37-1011.00
- **Canonical URL:** https://singulariki.com/roles/role-37-1011-00
- **Also known as:** Environmental Services Supervisor (EVS), Executive Housekeeper, Housekeeping Supervisor, Maintenance Supervisor, Building Services Supervisor, Buildings and Grounds Supervisor, Custodian Supervisor, Janitorial Supervisor
- **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):
- Supervise in-house services, such as laundries, maintenance and repair, dry cleaning, or valet services.
- Select the most suitable cleaning materials for different types of linens, furniture, flooring, and surfaces.
- Advise managers, desk clerks, or admitting personnel of rooms ready for occupancy.
- Inspect work performed to ensure that it meets specifications and established standards.
- Perform or assist with cleaning duties as necessary.
- Plan and prepare employee work schedules.
- Establish and implement operational standards and procedures for the departments supervised.
- Inspect and evaluate the physical condition of facilities to determine the type of work required.
- Inventory stock to ensure that supplies and equipment are available in adequate amounts.
- Issue supplies and equipment to workers.
- Forecast necessary levels of staffing and stock at different times to facilitate effective scheduling and ordering.
- Check and maintain equipment to ensure that it is in working order.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- English Language _(knowledge)_
- Oral Expression _(ability)_
- Administration and Management _(knowledge)_
- Oral Comprehension _(ability)_
- Management of Personnel Resources _(transferable_skill)_
- Education and Training _(knowledge)_
- Public Safety and Security _(knowledge)_
- Speaking _(essential_skill)_
- Monitoring _(essential_skill)_
- Coordination _(transferable_skill)_
- Time Management _(transferable_skill)_

**Skills in demand:**
- English Language _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Social Perceptiveness _(Common Skill)_
- Learning Strategies _(Specialized Skill)_
- Instructing _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Facebook _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Computerized bed control system software
- Computerized maintenance management system CMMS
- Email software

## AI exposure & outlook

- **AI task-overlap index:** 39th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 32nd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 36th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 54th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 86th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.5% growth (About average); 33k annual openings; 269.8k → 276.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $47,520; 174,660 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 45% automation, 49% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Select the most suitable cleaning materials for different types of linens, furniture, flooring, and surfaces. _(4.7% of measured AI use; directive)_
- Prepare reports on activity, personnel, and information such as occupancy, hours worked, facility usage, work performed, and departmental expenses. _(2.3% of measured AI use; task iteration)_
- Recommend changes that could improve service and increase operational efficiency. _(0.7% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me select the most suitable cleaning materials for different types of linens, furniture, flooring, and surfaces.
- Help me prepare reports on activity, personnel, and information such as occupancy, hours worked, facility usage, work performed, and departmental expenses.
- Help me recommend changes that could improve service and increase operational efficiency.

## 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

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-37-1011-00_