# Merchandise Displayers and Window Trimmers

> Plan and erect commercial displays, such as those in windows and interiors of retail stores and at trade exhibitions.

- **SOC code:** 27-1026.00
- **Canonical URL:** https://singulariki.com/roles/role-27-1026-00
- **Also known as:** Display Associate, Merchandiser, Visual Merchandiser (VM), Visual Merchandising Specialist, Decorator, Display Decorator, Display Specialist, In-Store Marketing Associate
- **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):
- Dress mannequins for displays.
- Plan commercial displays to entice and appeal to customers.
- Arrange properties, furniture, merchandise, backdrops, or other accessories, as shown in prepared sketches.
- Change or rotate window displays, interior display areas, or signage to reflect changes in inventory or promotion.
- Place prices or descriptive signs on backdrops, fixtures, merchandise, or floor.
- Consult with store managers, buyers, sales associates, housekeeping staff, or engineering staff to determine appropriate placement of displays or products.
- Maintain props, products, or mannequins, inspecting them for imperfections, doing touch-ups, cleaning up after customers, or applying preservative coatings as necessary.
- Supervise or train staff members on daily tasks, such as visual merchandising.
- Develop ideas or plans for merchandise displays or window decorations.
- Assemble or set up displays, furniture, or products in store space, using colors, lights, pictures, or other accessories to display the product.
- Store, pack, and maintain inventory records of props, products, or display items.
- Select themes, lighting, colors, or props to be used.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Visualization _(ability)_
- Customer and Personal Service _(knowledge)_
- Sales and Marketing _(knowledge)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Speech Clarity _(ability)_
- Active Listening _(essential_skill)_
- Fluency of Ideas _(ability)_
- Manual Dexterity _(ability)_
- Speech Recognition _(ability)_
- English Language _(knowledge)_
- Speaking _(essential_skill)_

**Skills in demand:**
- Visualization _(Specialized Skill)_
- Microsoft Excel _(Common Skill)_
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- English Language _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Time Management _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Reading Comprehension _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Adobe Creative Cloud software _(hot technology)_
- Adobe Illustrator _(hot technology)_
- Adobe InDesign _(hot technology)_
- Apple iOS _(hot technology)_
- Apple Safari _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- Google Docs _(hot technology)_
- Microsoft Edge _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 40th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 17th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 50th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 58th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 46th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.2% growth (About average); 20.8k annual openings; 193k → 199.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $37,350; 192,480 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** — automation, 73% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Prepare sketches, floor plans, or models of proposed displays. _(0.3% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me prepare sketches, floor plans, or models of proposed displays.

## 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-27-1026-00_