# Transportation Inspectors

> Inspect equipment or goods in connection with the safe transport of cargo or people. Includes rail transportation inspectors, such as freight inspectors, rail inspectors, and other inspectors of transportation vehicles not elsewhere classified.

- **SOC code:** 53-6051.00
- **Canonical URL:** https://singulariki.com/roles/role-53-6051-00
- **Also known as:** Cargo Surveyor, Marine Cargo Surveyor, Marine Surveyor, Petroleum Inspector, Inspector, Admeasurer, Bridge Inspector, Cargo Inspector
- **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):
- Prepare and submit reports after completion of freight shipments.
- Inspect shipments to ensure that freight is securely braced and blocked.
- Record details about freight conditions, handling of freight, and any problems encountered.
- Advise crews in techniques of stowing dangerous and heavy cargo.
- Observe loading of freight to ensure that crews comply with procedures.
- Post warning signs on vehicles containing explosives or flammable or radioactive materials.
- Recommend remedial procedures to correct any violations found during inspections.
- Measure heights and widths of loads to ensure they will pass over bridges or through tunnels on scheduled routes.
- Inspect loaded cargo, cargo lashed to decks or in storage facilities, and cargo handling devices to determine compliance with health and safety regulations and need for maintenance.
- Notify workers of any special treatment required for shipments.
- Direct crews to reload freight or to insert additional bracing or packing as necessary.
- Check temperatures and humidities of shipping and storage areas to ensure that they are at appropriate levels to protect cargo.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Transportation _(knowledge)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_
- English Language _(knowledge)_
- Deductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Written Comprehension _(ability)_
- Written Expression _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Active Listening _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Google Android _(hot technology)_
- Email software
- Web browser software

## AI exposure & outlook

- **AI task-overlap index:** 45th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 44th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 50th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 43rd percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 78th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.7% growth (About average); 2.5k annual openings; 25.7k → 26.1k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $85,750; 23,320 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/
- **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-53-6051-00_