SOC 43-5071

Shipping and Receiving Clerks AI displacement risk

Shipment documentation, rate computation, and record keeping are increasingly automated by warehouse and transportation management systems. Verifying contents, resolving damages and discrepancies, and coordinating carriers keep a human layer.

Exposure68

Share and intensity of work current AI systems can materially affect.

Automation50%

Likely potential for exposed tasks to move to software after workflow integration.

Risk bandModerate

Documentation automates faster than the physical verification. Clerks who cross-train on systems administration and exception handling stay employable as warehouse technology spreads.

Distribution

Where Shipping and Receiving Clerks sits across 620 tracked roles

Shipping and Receiving Clerks · 58050100

Displacement pressure 58 — higher than 87% of the 620 occupations tracked on displacement.ai.

Score version

This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-08. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.

11 O*NET task statements matched to SOC 43-5071. The displayed task profile combines these official task statements with the current public score model.

Median wage context: $45,260 (May 2025, US national). The latest BLS row matched SOC 43-5071.

Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.

2030 economic stress test

How Anthropic's scenarios classify Shipping and Receiving Clerks

SOC 43-5071 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 58/100 role score and are not an occupation forecast.

Modest change

+0.4% group wage

-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.

Economy-wide: +1.6% GDP and 3.9% unemployment.

Substantial change

-0.3% group wage

-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.

Economy-wide: +8.3% GDP and 4.6% unemployment.

Extreme change

-11.5% group wage

-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.

Economy-wide: +32.4% GDP and 11.9% unemployment.

Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.

Official task evidence

O*NET task matches for Shipping and Receiving Clerks

The current evidence import matched 11 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.

Dataset31.0 (August 2026)
Matched tasks11
SOC43-5071
  • Core task / ID 20276

    Examine shipment contents and compare with records, such as manifests, invoices, or orders, to verify accuracy.

  • Core task / ID 4742

    Requisition and store shipping materials and supplies to maintain inventory of stock.

  • Core task / ID 4737

    Prepare documents, such as work orders, bills of lading, or shipping orders, to route materials.

  • Core task / ID 20277

    Pack, seal, label, or affix postage to prepare materials for shipping, using hand tools, power tools, or postage meter.

  • Core task / ID 4739

    Record shipment data, such as weight, charges, space availability, damages, or discrepancies, for reporting, accounting, or recordkeeping purposes.

  • Core task / ID 4741

    Confer or correspond with establishment representatives to rectify problems, such as damages, shortages, or nonconformance to specifications.

Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.

Task profile

Where AI changes the work

information

Prepare shipping documents

Exposure 82, automation 64%, augmentation 24%.

O*NET evidence: Prepare documents, such as work orders, bills of lading, or shipping orders, to route m... (ID 4737)

information

Record shipment data

Exposure 78, automation 58%, augmentation 30%.

O*NET evidence: Examine shipment contents and compare with records, such as manifests, invoices, or ord... (ID 20276)

compliance

Verify contents against records

Exposure 56, automation 34%, augmentation 44%.

O*NET evidence: Examine shipment contents and compare with records, such as manifests, invoices, or ord... (ID 20276)

social

Coordinate with carriers on problems

Exposure 40, automation 16%, augmentation 48%.

O*NET evidence: Contact carrier representatives to make arrangements or to issue instructions for shipp... (ID 4740)

TaskExposureAutomationAugmentation
Prepare shipping documents8264%24%
Record shipment data7858%30%
Verify contents against records5634%44%
Coordinate with carriers on problems4016%48%

Transition pathways

Adjacent moves that preserve existing skills

role redesign

Warehouse Systems Coordinator

Training horizon: 3-6 months. Skill overlap 72. Wage preservation signal 118.

  • Own WMS data quality
  • Audit automated documentation
  • Track dock exceptions
Moderate
adjacent role

Logistics Coordinator

Training horizon: 3-6 months. Skill overlap 66. Wage preservation signal 122.

  • Learn load planning
  • Track carrier performance
  • Manage shipment exceptions
Moderate

Comparison guides

Compare the next move before you commit

What the AI risk score means for Shipping and Receiving Clerks

The displacement pressure score for Shipping and Receiving Clerks is 58. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.

For this role, the clearest risk pattern is visible at the task level. Prepare shipping documents carries 64% automation pressure, while Coordinate with carriers on problems carries 48% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.

Labor-market context and wage risk

Median wage: $45,260 (May 2025, US national). Employment context: Warehouse documentation role alongside logistics automation. Typical education: High school diploma or equivalent.

Wage vulnerability is 62, while transition feasibility is 66. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.

  • Moderate to high automation pressure
  • Systems absorb documentation
  • Physical verification stays human

Upskilling priorities

Skills that make this role more resilient

The safest upskilling plan starts with skills already close to the work. For Shipping and Receiving Clerks, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.

Priority 1

Warehouse systems

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 2

Documentation accuracy

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 3

Exception resolution

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

Priority 4

Carrier coordination

Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.

90-day transition plan

The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.

  1. In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
  2. By 60 days, complete one small project connected to Warehouse Systems Coordinator, such as own wms data quality.
  3. By 90 days, compare internal openings and external postings for Warehouse Systems Coordinator or Logistics Coordinator and update your resume around measurable workflow outcomes.

FAQ

Questions about AI and Shipping and Receiving Clerks

Will AI replace Shipping and Receiving Clerks?

Shipment documentation, rate computation, and record keeping are increasingly automated by warehouse and transportation management systems. Verifying contents, resolving damages and discrepancies, and coordinating carriers keep a human layer. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.

Which parts of Shipping and Receiving Clerks work are most exposed to AI?

Prepare shipping documents and Record shipment data show the strongest automation pressure in this model. Coordinate with carriers on problems and Verify contents against records are better treated as AI-augmented work.

What should Shipping and Receiving Clerks learn next?

Start with Warehouse systems, Documentation accuracy, Exception resolution. The most practical adjacent paths in this model are Warehouse Systems Coordinator and Logistics Coordinator.

How should this score be used?

Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.

Sources

Evidence trail