# Logging Equipment Operators

> Drive logging tractor or wheeled vehicle equipped with one or more accessories, such as bulldozer blade, frontal shear, grapple, logging arch, cable winches, hoisting rack, or crane boom, to fell tree; to skid, load, unload, or stack logs; or to pull stumps or clear brush. Includes operating stand-alone logging machines, such as log chippers.

- **SOC code:** 45-4022.00
- **Canonical URL:** https://singulariki.com/roles/role-45-4022-00
- **Also known as:** Loader Operator, Logging Equipment Operator, Skidder Driver, Skidder Operator, Delimber Operator, Feller Buncher Operator, Harvester Operator, Log Processor 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):
- Inspect equipment for safety prior to use, and perform necessary basic maintenance tasks.
- Control hydraulic tractors equipped with tree clamps and booms to lift, swing, and bunch sheared trees.
- Grade logs according to characteristics such as knot size and straightness, and according to established industry or company standards.
- Drive and maneuver tractors and tree harvesters to shear the tops off of trees, cut and limb the trees, and cut the logs into desired lengths.
- Drive straight or articulated tractors equipped with accessories such as bulldozer blades, grapples, logging arches, cable winches, and crane booms to skid, load, unload, or stack logs, pull stumps, or clear brush.
- Drive crawler or wheeled tractors to drag or transport logs from felling sites to log landing areas for processing and loading.
- Fill out required job or shift report forms.
- Calculate total board feet, cordage, or other wood measurement units, using conversion tables.
- Drive tractors for building or repairing logging and skid roads.

**Emerging tasks** (O*NET):
- Operate remote-controlled logging machines and drones for dangerous or hard-to-reach tasks.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mechanical _(knowledge)_
- Operation and Control _(transferable_skill)_
- Control Precision _(ability)_
- Reaction Time _(ability)_
- Operations Monitoring _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Multilimb Coordination _(ability)_
- Depth Perception _(ability)_
- Public Safety and Security _(knowledge)_
- Problem Sensitivity _(ability)_
- Response Orientation _(ability)_
- Rate Control _(ability)_

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

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- BCS Woodlands Systems The Logger Tracker
- TradeTec TallyWorks Logs
- TradeTec TallyWorks TimeTracker

## AI exposure & outlook

- **AI task-overlap index:** 10th percentile (Low) 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):** 24th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 1st percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 64th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -1.4% growth (Declining); 4.2k annual openings; 30.9k → 30.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,210; 22,520 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-45-4022-00_