# Computer, Automated Teller, and Office Machine Repairers

> Repair, maintain, or install computers, word processing systems, automated teller machines, and electronic office machines, such as duplicating and fax machines.

- **SOC code:** 49-2011.00
- **Canonical URL:** https://singulariki.com/roles/role-49-2011-00
- **Also known as:** ATM Technician (Automated Teller Machine Technician), Computer Technician, Copier Technician, Service Technician, Computer Repair Technician, Customer Service Engineer, Field Engineer, Field Service Engineer
- **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):
- Reassemble machines after making repairs or replacing parts.
- Converse with customers to determine details of equipment problems.
- Disassemble machines to examine parts, such as wires, gears, or bearings for wear or defects, using hand or power tools and measuring devices.
- Advise customers concerning equipment operation, maintenance, or programming.
- Align, adjust, or calibrate equipment according to specifications.
- Repair, adjust, or replace electrical or mechanical components or parts, using hand tools, power tools, or soldering or welding equipment.
- Travel to customers' stores or offices to service machines or to provide emergency repair service.
- Maintain parts inventories and order any additional parts needed for repairs.
- Reinstall software programs or adjust settings on existing software to fix machine malfunctions.
- Operate machines to test functioning of parts or mechanisms.
- Clean, oil, or adjust mechanical parts to maintain machines' operating efficiency and to prevent breakdowns.
- Maintain records of equipment maintenance work or repairs.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Computers and Electronics _(knowledge)_
- Customer and Personal Service _(knowledge)_
- Near Vision _(ability)_
- Oral Comprehension _(ability)_
- Mechanical _(knowledge)_
- Active Listening _(essential_skill)_
- Repairing _(transferable_skill)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_
- Critical Thinking _(essential_skill)_
- Written Comprehension _(ability)_
- Finger Dexterity _(ability)_

**Skills in demand:**
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Excel _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Visualization _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- Time Management _(Common Skill)_
- Equipment Selection _(Specialized Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Extensible markup language XML _(hot technology)_
- Hypertext markup language HTML _(hot technology)_
- JavaScript _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Active Directory _(hot technology)_
- Microsoft Active Server Pages ASP _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 44th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 39th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 41st percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 54th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 60th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -0.9% growth (Declining); 7.6k annual openings; 79.1k → 78.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $46,860; 73,010 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 64% automation, 33% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** feedback loop.

**Tasks most handed to AI here:**
- Reinstall software programs or adjust settings on existing software to fix machine malfunctions. _(17.1% of measured AI use; feedback loop)_
- Install and configure new equipment, including operating software or peripheral equipment. _(9.2% of measured AI use; learning)_
- Advise customers concerning equipment operation, maintenance, or programming. _(1.8% of measured AI use; learning)_
- Analyze equipment performance records to assess equipment functioning. _(0.8% of measured AI use; learning)_
- Read specifications, such as blueprints, charts, or schematics, to determine machine settings or adjustments. _(0.6% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me reinstall software programs or adjust settings on existing software to fix machine malfunctions.
- Help me install and configure new equipment, including operating software or peripheral equipment.
- Help me advise customers concerning equipment operation, maintenance, or programming.
- Help me analyze equipment performance records to assess equipment functioning.
- Help me read specifications, such as blueprints, charts, or schematics, to determine machine settings or adjustments.

## 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-49-2011-00_