# Cargo and Freight Agents

> Expedite and route movement of incoming and outgoing cargo and freight shipments in airline, train, and trucking terminals and shipping docks. Take orders from customers and arrange pickup of freight and cargo for delivery to loading platform. Prepare and examine bills of lading to determine shipping charges and tariffs.

- **SOC code:** 43-5011.00
- **Canonical URL:** https://singulariki.com/roles/role-43-5011-00
- **Also known as:** Air Export Specialist, Drop Shipment Clerk, Logistics Coordinator, Logistics Service Representative, Freight Broker, Intermodal Dispatcher, International Coordinator, Load Planner
- **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):
- Negotiate and arrange transport of goods with shipping or freight companies.
- Determine method of shipment and prepare bills of lading, invoices, and other shipping documents.
- Track delivery progress of shipments.
- Prepare manifests showing numbers of airplane passengers and baggage, mail, and freight weights, transmitting data to destinations.
- Advise clients on transportation and payment methods.
- Arrange insurance coverage for goods.
- Estimate freight or postal rates and record shipment costs and weights.
- Install straps, braces, and padding to loads to prevent shifting or damage during shipment.
- Keep records of all goods shipped, received, and stored.
- Notify consignees, passengers, or customers of freight or baggage arrival and arrange for delivery.
- Check import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group.
- Coordinate and supervise activities of workers engaged in packing and shipping merchandise.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Transportation _(knowledge)_
- Geography _(knowledge)_
- Public Safety and Security _(knowledge)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- English Language _(knowledge)_
- Administration and Management _(knowledge)_
- Written Comprehension _(ability)_
- Speaking _(essential_skill)_
- Active Listening _(essential_skill)_
- Education and Training _(knowledge)_
- Law and Government _(knowledge)_

**Skills in demand:**
- Geography _(Specialized Skill)_
- English Language _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Active Listening _(Common Skill)_
- Telecommunications _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Time Management _(Common Skill)_
- Negotiation _(Common Skill)_
- Writing _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Social Perceptiveness _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Brokerage software
- Corel WordPerfect Office Suite
- Database software
- Email software
- Microsoft OneNote
- Posting software

## AI exposure & outlook

- **AI task-overlap index:** 75th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 96th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 55th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 71st percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 99th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 8.5% growth (Growing fast); 8.8k annual openings; 100.6k → 109.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,900; 97,800 employed.

## How people actually use AI here

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

- **Autonomy median:** 3.0 (higher = AI acts more independently).

**Tasks most handed to AI here:**
- Check import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group. _(0.3% of measured AI use)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me check import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group.

## 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

---
_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-43-5011-00_