Will AI replace Cargo and Freight Agents?

Not as a job, but it is already doing parts of the work. Across the 55 official task statements scored for Cargo and Freight Agents (United States, SOC 43-5011), 73% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 66 out of 100 (range 61–72, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Cargo and Freight Agents” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Estimate freight or postal rates and record shipment costs and weights” (93/100, very high); “Keep records of all goods shipped, received, and stored” (93/100, very high); “Select shipment routes, based on nature of goods shipped, transit times, or security needs” (93/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Cargo and Freight Agents” stay human?

About 17% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Assemble containers and crates used to transport items, such as machines or vehicles” (0/100, minimal); “Route received goods to first available flight or to appropriate storage areas or departments, using forklifts, hand trucks, or other equipment” (0/100, minimal); “Attach address labels, identification codes, and shipping instructions to containers” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Cargo and Freight Agents” do about AI?

Start from the ledger rather than the headline: 73% of this job's weighted core work is exposed, and roughly 17% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Cargo and Freight Agents calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 55 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Cargo and Freight Agents

negotiating shipping rates with freight carriers, keeping records of goods and reserving necessary space on ships. If that's your week, this page is about your job.

The honest answer

Most tasks in this job are the kind AI has learned to do: keeping records of goods. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 73%
changing shape: 10%
staying human: 17%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 66 out of 100 (61–72 allowing for uncertainty): high exposure, across 55 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for cargo and freight agents is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

It would be a lie to soften that; verifying proper packaging and labeling of exported goods is what this work rebuilds around. The plan below starts there.

Your week, as this page understands it

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. The job title says “cargo” or “freight agents”: officially one job, two names. The real job is the part underneath: verifying proper packaging and labeling of exported goods. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But cargo and freight agents is not one task. It is 55 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is verifying proper packaging and labeling of exported goods, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 73%
changing shape: 10%
staying human: 17%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

8 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

36 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Keeping records of goods
This is reading one thing and writing another: records of goods in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Keep records of goods dispatched or received.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Dispatch and receipt records are kept in systems that update themselves.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Informing clients of factors, shipping options, timelines, transfers or regulations affecting shipments
This is reading one thing and writing another: clients of factors, shipping options, timelines in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Inform clients of factors such as shipping options, timelines, transfers, or regulations affecting shipments.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Explaining options, timings and rules to clients is well-documented information easily drafted and sent.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Paying or arranging for payment of freight or insurance fees or other charges
This is reading one thing and writing another: payment of freight in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Pay or arrange for payment of freight or insurance fees or other charges.” (O*NET task statement)
How this row was scored
Exposure score: 66 out of 100 (59–73 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Freight and insurance charges are processed against set rates and invoices, so most payment preparation can be done automatically.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining efficient and cost-effective methods of moving goods from one location
This is reading one thing and writing another: efficient in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Determine efficient and cost-effective methods of moving goods from one location to another.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Choosing the cheapest sensible way to move goods is a planning calculation software handles well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Changing shape

5 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Negotiating and arranging transport of goods with shipping or freight companies
The software now makes the first pass at transport of goods, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Core
Source: “Negotiate and arrange transport of goods with shipping or freight companies.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Booking space and terms with carriers runs largely through rate portals, though relationships still shape the better deals.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Arranging for special transport of sensitive cargoes
The software now makes the first pass at special transport of sensitive cargoes, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Arrange for special transport of sensitive cargoes, such as livestock, food, or medical supplies.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Special-cargo rules for livestock, food and medical goods are documented, so arranging compliant transport is largely paperwork.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Arranging for applicable duties, taxes or paperwork for customs clearance
The software now makes the first pass at applicable duties, taxes or paperwork, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 5 · Core
Source: “Arrange for applicable duties, taxes, or paperwork for customs clearance.” (O*NET task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Duty and tax rules are published, but customs filings normally go through a licensed broker.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

Staying human

14 tasks

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Negotiating shipping rates with freight carriers
The value here is that a specific person handles rates and stands behind it. That is earned, not computed.
importance 5 · Core
Source: “Negotiate shipping rates with freight carriers.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Software can benchmark rates and prepare a case, but agreeing a price with a carrier rests on the relationship between the two firms.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Verifying proper packaging and labeling of exported goods
This work happens in the physical world: proper packaging and labeling of exported goods, in a real place. Software cannot follow it there.
importance 4 · Core
Source: “Verify proper packaging and labeling of exported goods.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Checking that goods are actually packed and labeled correctly means looking at the physical shipment.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Retrieving stored items and trace lost shipments
This work happens in the physical world: stored items, in a real place. Software cannot follow it there.
importance 3 · Core
Source: “Retrieve stored items and trace lost shipments as necessary.” (O*NET task statement)
How this row was scored
Exposure score: 32 out of 100 (25–39 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Tracing a lost shipment is records work, but physically retrieving stored items happens in the warehouse.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Show the other 45 tasks

Estimating freight or postal rates and recording shipment costs and weights
shifting to AI
This is reading one thing and writing another: freight in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Estimate freight or postal rates and record shipment costs and weights.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Rating a shipment and recording its cost and weight is straightforward calculation from rate tables.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Keeping records of all goods
shifting to AI
This is reading one thing and writing another: records of all goods in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Keep records of all goods shipped, received, and stored.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Keeping shipping and storage records is exactly what warehouse and freight systems do.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Selecting shipment routes, based on nature of goods shipped, transit times or security needs
shifting to AI
This is reading one thing and writing another: shipment routes in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Select shipment routes, based on nature of goods shipped, transit times, or security needs.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Choosing routes on cost, transit time and security is a classic optimization software does well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating weight, volume or cost of goods
shifting to AI
This is reading one thing and writing another: weight, volume or cost of goods in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Calculate weight, volume, or cost of goods to be moved.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Weight, volume and cost calculations follow fixed formulas.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Monitoring or recording locations of goods in transit
shifting to AI
This is reading one thing and writing another: locations of goods in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Monitor or record locations of goods in transit.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recording where goods are in transit is automated tracking data.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing invoices or cost quotations for freight transportation
shifting to AI
This is reading one thing and writing another: invoices in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Prepare invoices or cost quotations for freight transportation.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Building an invoice or quote from rates, weights and surcharges is routine calculation.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Analyzing shipping routes to determine how to minimize environmental impact
shifting to AI
This is reading one thing and writing another: routes in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Analyze shipping routes to determine how to minimize environmental impact.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Comparing emissions across routes is a calculation once distances and modes are known.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing the environmental records of freight carriers to inform shipping decisions
shifting to AI
This is reading one thing and writing another: the environmental records of freight carriers in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Review the environmental records of freight carriers to inform shipping decisions.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reviewing published carrier environmental records and summarizing them is document work software handles well.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Tracking delivery progress of shipments
shifting to AI
This is reading one thing and writing another: delivery progress of shipments in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Track delivery progress of shipments.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tracking shipments is already done by systems that pull carrier updates automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Preparing manifests showing numbers of airplane passengers and baggage
shifting to AI
This is reading one thing and writing another: manifests showing numbers of airplane passengers in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Prepare manifests showing numbers of airplane passengers and baggage, mail, and freight weights, transmitting data to destinations.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Manifests are built from booking and weight data and transmitted automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Determining method of shipment and preparing bills of lading
shifting to AI
This is reading one thing and writing another: method of shipment in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Determine method of shipment and prepare bills of lading, invoices, and other shipping documents.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Bills of lading and invoices follow set formats, and drafting them from shipment details is routine document work.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Preparing shipping documentation, such as bills of lading, packing lists, dock receipts or certificates of origin
shifting to AI
This is reading one thing and writing another: documentation in, a record out. That is the shape today's tools are built for.
importance 5 · Core
Source: “Prepare shipping documentation, such as bills of lading, packing lists, dock receipts, or certificates of origin.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Bills of lading, packing lists and certificates of origin are standard forms filled from shipment data.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Verifying adherence of documentation
shifting to AI
This is reading one thing and writing another: adherence of documentation in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Verify adherence of documentation to customs, insurance, or regulatory requirements.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Comparing documents against published customs and insurance requirements is careful checking software does reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Checking import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group
shifting to AI
This is reading one thing and writing another: import in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Check import or export documentation to determine cargo contents and use tariff coding system to classify goods according to fee or tariff group.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (81–95 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tariff codes and customs documents are fully published, so classifying and checking paperwork is well-suited to software.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Providing detailed port information to importers or exporters
shifting to AI
This is reading one thing and writing another: detailed port information in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Provide detailed port information to importers or exporters.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Port details are published reference information that is easy to look up and pass on.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Arranging insurance coverage for goods
shifting to AI
This is reading one thing and writing another: insurance coverage in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Arrange insurance coverage for goods.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (74–88 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Arranging cargo cover follows standard forms and cover terms, so the paperwork is routine.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Obtaining or arranging cargo insurance
shifting to AI
This is reading one thing and writing another: cargo insurance in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Obtain or arrange cargo insurance.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (74–88 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Arranging cargo insurance uses standard forms and documented cover terms.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reserving necessary space on ships
shifting to AI
This is reading one thing and writing another: necessary space in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Reserve necessary space on ships, aircraft, trains, or trucks.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Booking space with carriers is done through portals that software can drive directly.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Arranging delivery or storage of goods at destinations
shifting to AI
This is reading one thing and writing another: delivery in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Arrange delivery or storage of goods at destinations.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (72–86 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Booking delivery or storage at the destination runs through documented systems and standard messages.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Providing shipment status notification
shifting to AI
This is reading one thing and writing another: shipment status notification in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Provide shipment status notification to exporters, consignees, or insurers.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Status notifications to consignees and insurers are automated messages in most freight systems.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Notifying consignees, passengers or customers of freight or baggage arrival and arranging for delivery
shifting to AI
This is reading one thing and writing another: consignees, passengers or customers of freight or baggage in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Notify consignees, passengers, or customers of freight or baggage arrival and arrange for delivery.” (O*NET task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Arrival notices and delivery bookings are standard messages systems already send automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Completing customs paperwork
shifting to AI
This is reading one thing and writing another: customs paperwork in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Complete customs paperwork.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Customs forms are highly structured, though the filing itself usually needs a licensed broker.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Considering environmental sustainability factors when determining merchandise packing methods
shifting to AI
This is reading one thing and writing another: environmental sustainability factors in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Consider environmental sustainability factors when determining merchandise packing methods.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Sustainable packing choices follow documented material and weight trade-offs.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Recommending shipping solutions to minimize cost or environmental impacts
shifting to AI
This is reading one thing and writing another: solutions in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Recommend shipping solutions to minimize cost or environmental impacts.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Cost and emissions comparisons are calculable, though which options are actually workable depends on local knowledge.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Making arrangements with customs brokers to facilitate the passage of goods through customs
shifting to AI
This is reading one thing and writing another: arrangements in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Make arrangements with customs brokers to facilitate the passage of goods through customs.” (O*NET task statement)
How this row was scored
Exposure score: 69 out of 100 (62–76 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Passing shipment details to a customs broker is standard, structured correspondence.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Maintaining current knowledge of relevant legislation
shifting to AI
It is the same call made over and over on current knowledge of relevant legislation, with a right answer to check it against. That is what a model is trained on.
importance 4 · Core
Source: “Maintain current knowledge of relevant legislation, political situations, or other factors that could affect freight shipping.” (O*NET task statement)
How this row was scored
Exposure score: 65 out of 100 (58–72 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: News and rule changes are easy to gather and summarize, but the judgment about what matters stays with the agent.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Advising clients on transportation and payment methods
shifting to AI
This is reading one thing and writing another: clients in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Advise clients on transportation and payment methods.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Options and payment terms are documented, so clear tailored advice is easy to produce for a typical enquiry.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Consolidating loads with a common destination to reduce costs to individual shippers
shifting to AI
This is reading one thing and writing another: loads in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Consolidate loads with a common destination to reduce costs to individual shippers.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Grouping shipments to save cost is a planning puzzle software is good at, though deadlines and mixed cargo need judgement.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Recommending or arranging appropriate merchandise packing methods
shifting to AI
This is reading one thing and writing another: appropriate merchandise packing methods in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Recommend or arrange appropriate merchandise packing methods, according to climate, terrain, weight, nature of goods, or costs.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Packing guidance for climate, weight and handling is documented, so sound recommendations are easy to produce.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Referring exporters to experts in areas
shifting to AI
This is reading one thing and writing another: exporters in, a record out. That is the shape today's tools are built for.
importance 4 · Supplemental
Source: “Refer exporters to experts in areas such as trade financing, international marketing, government export requirements, international banking, or marine insurance.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pointing exporters to the right kind of specialist is straightforward, though good referrals lean on personal contacts.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Arranging for transport, using a variety of modes, such as rail
shifting to AI
This is reading one thing and writing another: transport in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Arrange for transport, using a variety of modes, such as rail, short sea shipping, air, or roadways, to minimize carbon emissions or other environmental impacts.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Emissions per mode are documented, so lower-impact routings can be proposed, though carrier availability decides.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Contacting vendors or claims adjustment departments to resolve shipment problems or contact service depots to arrange for repairs
shifting to AI
This is reading one thing and writing another: vendors in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Contact vendors or claims adjustment departments to resolve shipment problems or contact service depots to arrange for repairs.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Chasing vendors and claims departments about a shipment problem is routine correspondence with a documented process.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Assisting clients in obtaining insurance reimbursements
changing shape
The software now makes the first pass at clients, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · Supplemental
Source: “Assist clients in obtaining insurance reimbursements.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Claim paperwork is standard, but pushing an insurer to pay often depends on a person chasing it.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Entering shipping information into a computer by hand or by a hand-held scanner that reads bar codes on goods
changing shape
The software now makes the first pass at information, but part of it still happens in the physical world. So the job becomes checking and deciding rather than producing.
importance 3 · Core
Source: “Enter shipping information into a computer by hand or by a hand-held scanner that reads bar codes on goods.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Keying data is easily automated, but scanning barcodes means standing beside the goods.
The five ratings: output a model can produce 4/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Maintaining a supply of packing materials
staying human
This work happens in the physical world: a supply of packing materials, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Maintain a supply of packing materials.” (O*NET task statement)
How this row was scored
Exposure score: 38 out of 100 (31–45 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Reordering packing materials is easy to automate, though restocking them is physical.
The five ratings: output a model can produce 3/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Inspecting and counting items received and checking them against invoices or other documents
staying human
This work happens in the physical world: items, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Inspect and count items received and check them against invoices or other documents, recording shortages and rejecting damaged goods.” (O*NET task statement)
How this row was scored
Exposure score: 14 out of 100 (7–21 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Counting and inspecting arriving goods means physically handling and looking at them.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Coordinating and supervising activities of workers engaged in packing and shipping merchandise
staying human
This work happens in the physical world: activities of workers, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Coordinate and supervise activities of workers engaged in packing and shipping merchandise.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Supervising packers and shippers means being on the floor with them.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Directing or participating in cargo loading to ensure completeness of load and even distribution of weight
staying human
This work happens in the physical world: cargo, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Direct or participate in cargo loading to ensure completeness of load and even distribution of weight.” (O*NET task statement)
How this row was scored
Exposure score: 12 out of 100 (5–19 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Load planning can be calculated, but the task includes being at the loading itself.
The five ratings: output a model can produce 2/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Packing goods for shipping, using tools, staplers, strapping machines and hammers
staying human
This work happens in the physical world: goods, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Pack goods for shipping, using tools such as staplers, strapping machines, and hammers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Packing goods with staplers, strapping and hammers is handwork.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Directing delivery trucks to shipping doors or designated marshaling areas and help load and unload goods safely
staying human
This work happens in the physical world: delivery trucks, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Direct delivery trucks to shipping doors or designated marshaling areas and help load and unload goods safely.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Directing trucks to doors and helping load is done on the dock.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Installing straps, braces and padding to loads to prevent shifting or damage during shipment
staying human
This work happens in the physical world: straps, braces, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Install straps, braces, and padding to loads to prevent shifting or damage during shipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Strapping, bracing and padding a load is done by hand.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Opening cargo containers and unwrap contents
staying human
This work happens in the physical world: cargo containers, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Open cargo containers and unwrap contents, using steel cutters, crowbars, or other hand tools.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Opening containers with cutters and crowbars is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.
Attaching address labels, identification codes and shipping instructions to containers
staying human
This work happens in the physical world: address labels, identification codes and shipping instructions, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Attach address labels, identification codes, and shipping instructions to containers.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Sticking labels and instructions onto containers means handling each one.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Routing received goods to first available flight or to appropriate storage areas or departments
staying human
This work happens in the physical world: received goods, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Route received goods to first available flight or to appropriate storage areas or departments, using forklifts, hand trucks, or other equipment.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Moving received goods with a forklift or hand truck is physical work.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Assembling containers and crates used to transport items
staying human
This work happens in the physical world: containers, in a real place. Software cannot follow it there.
importance 3 · Supplemental
Source: “Assemble containers and crates used to transport items, such as machines or vehicles.” (O*NET task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Building crates and containers is hands-on assembly.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 1/4.

What this job pays, and how many people do it

Median pay: $52,260a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 97,670in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: records of goods in, a record out. The rows above are exactly that shape: keeping records of goods and informing clients of factors, shipping options, timelines, transfers or regulations affecting shipments. What it cannot do is be there in the room, and that is still where proper packaging and labeling of exported goods get done. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

The exposed part of your job is the biggest part, and I am not going to dress that up: keeping records of goods is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 73% of this job's task weight sits in rows the software is already learning, 10% in rows that change shape rather than disappear, and 17% in rows it is nowhere near. That is the position, measured across 55 scored tasks. It is not a forecast about you.

What you have that the software does not is verifying proper packaging and labeling of exported goods, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.

This week: one thing

Sit on the machine's side of the desk. Pick one real piece of records of goods you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.

What you end up holding: a written list of the machine’s mistakes, in your handwriting
How long it takes: an evening, or an hour if you pick one job rather than one client

If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of records of goods, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.

Over the next 90 days

Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is keeping records of goods” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.

Over the next 12 months

Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of verifying proper packaging and labeling of exported goods you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to cargo and freight agents (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was compliance officers: only about 3% of its durable work is work you already do. I am not going to pretend that is comfortable news: 73% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “negotiate and arrange transport of goods with shipping or freight companies” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Compliance Officers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already make arrangements with customs brokers to facilitate the passage of goods through customs, and their equivalent is to clear goods through customs and to their destinations for clients. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →
Transportation, Storage, and Distribution Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already keep records of all goods shipped, received, and stored, and their equivalent is to supervise the activities of workers engaged in receiving, storing, testing, and shipping products…. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step. The pay gap is the market pricing a barrier: $107,230 against your $52,260 is 2.05× (OEWS May 2025 (both)), and you would be crossing it holding about 3% of their durable work. A gap that size with an overlap that small is a wish, not a route.
Look at that job’s page anyway →
Heavy and Tractor-Trailer Truck Drivers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already calculate weight, volume, or cost of goods to be moved, and their equivalent is to inventory and inspect goods to be moved to determine quantities and conditions. Across both published task lists that is about 3% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 3% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 73% of its task weight, across 55 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: verifying proper packaging and labeling of exported goods is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

If you run a team doing this job

If you run a team doing this job, the conversation you owe them is the one on this page, and sooner than feels comfortable. Show them the ledger rather than a reassurance: the rows moving toward the software are keeping records of goods, and the rows that are not are where you want your people visible. Ask each of them to do the this-week move and bring the list to your next one-to-one. It turns a rumour into a piece of work, and it tells you which parts of your team's week are actually at stake. And say the thing out loud that a team lead usually leaves unsaid: a shrinking team is your exposure too, so do the move yourself as well.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Importers and exporters is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

In UK official statistics this job is counted as Importers and exporters. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
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No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for cargo / freight agents, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 73% of the work on this page is already inside what they can do.

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The AI Authority is a general community about working with AI, not a course for cargo / freight agents. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

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No Space for cargo / freight agents yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

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Collab365 launches new communities where the need is real. If one for cargo / freight agents existed, with researched problems, courses and people in the same boat, would you want in?

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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Cargo and Freight Agents?: Not as a job, but it is already doing parts of the work. Across the 55 official task statements scored for Cargo and Freight Agents (United States, SOC 43-5011), 73% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 66 out of 100 (range 61–72, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Cargo and Freight Agents” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Estimate freight or postal rates and record shipment costs and weights” (93/100, very high); “Keep records of all goods shipped, received, and stored” (93/100, very high); “Select shipment routes, based on nature of goods shipped, transit times, or security needs” (93/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Cargo and Freight Agents” stay human?: About 17% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Assemble containers and crates used to transport items, such as machines or vehicles” (0/100, minimal); “Route received goods to first available flight or to appropriate storage areas or departments, using forklifts, hand trucks, or other equipment” (0/100, minimal); “Attach address labels, identification codes, and shipping instructions to containers” (0/100, minimal). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Cargo and Freight Agents” do about AI?: Start from the ledger rather than the headline: 73% of this job's weighted core work is exposed, and roughly 17% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Cargo and Freight Agents calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 55 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
8 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.