# Operating Engineers and Other Construction Equipment Operators

> Operate one or several types of power construction equipment, such as motor graders, bulldozers, scrapers, compressors, pumps, derricks, shovels, tractors, or front-end loaders to excavate, move, and grade earth, erect structures, or pour concrete or other hard surface pavement. May repair and maintain equipment in addition to other duties.

- **SOC code:** 47-2073.00
- **Canonical URL:** https://singulariki.com/roles/role-47-2073-00
- **Also known as:** Equipment Operator (EO), Heavy Equipment Operator (HEO), Machine Operator, Operating Engineer, Back Hoe Operator, Engineering Equipment Operator, Forklift Operator, Hot Mix Asphalt Operator
- **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):
- Learn and follow safety regulations.
- Take actions to avoid potential hazards or obstructions, such as utility lines, other equipment, other workers, or falling objects.
- Check fuel supplies at sites to ensure adequate availability.
- Start engines, move throttles, switches, or levers, or depress pedals to operate machines, such as bulldozers, trench excavators, road graders, or backhoes.
- Coordinate machine actions with other activities, positioning or moving loads in response to hand or audio signals from crew members.
- Locate underground services, such as pipes or wires, prior to beginning work.
- Align machines, cutterheads, or depth gauge makers with reference stakes and guidelines or ground or position equipment, following hand signals of other workers.
- Signal operators to guide movement of tractor-drawn machines.
- Repair and maintain equipment, making emergency adjustments or assisting with major repairs as necessary.
- Load and move dirt, rocks, equipment, or other materials, using trucks, crawler tractors, power cranes, shovels, graders, or related equipment.
- Drive and maneuver equipment equipped with blades in successive passes over working areas to remove topsoil, vegetation, or rocks or to distribute and level earth or terrain.
- Operate tractors or bulldozers to perform such tasks as clearing land, mixing sludge, trimming backfills, or building roadways or parking lots.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Operation and Control _(transferable_skill)_
- Control Precision _(ability)_
- Depth Perception _(ability)_
- Multilimb Coordination _(ability)_
- Near Vision _(ability)_
- Far Vision _(ability)_
- Mechanical _(knowledge)_
- Rate Control _(ability)_
- Reaction Time _(ability)_
- English Language _(knowledge)_
- Operations Monitoring _(transferable_skill)_
- Equipment Maintenance _(transferable_skill)_

**Skills in demand:**
- Depth Perception _(Common Skill)_
- English Language _(Common Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Finger Dexterity _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Windows _(hot technology)_
- Maintenance record software
- Work record software

## AI exposure & outlook

- **AI task-overlap index:** 17th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 22nd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 9th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 30th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 89th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.6% growth (About average); 41.9k annual openings; 489.3k → 507.1k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $58,710; 469,270 employed.

## 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/
- **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-47-2073-00_