COOKED
The clerical half of this job — matching packing slips to POs, keying receipts into the WMS, generating bills of lading, tracing shipments, reconciling inventory counts — is already handled by barcode/RFID scanning, EDI, and warehouse software, and AI closes the remaining exception-handling gap. What holds is the physical half: actually opening cartons, inspecting goods for damage, counting what the system got wrong, staging pallets, and talking to drivers on the dock. No license, no signature requirement, and buyers pay for accurate throughput rather than a relationship with the clerk.
Headcount grew steadily across the period.
Median pay $34,190 → $45,260 +5.9% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-7.7% 862,200 → 795,800 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -7.7% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~69,300 openings a year on average, including replacing people who leave.
ShipperReceiverForwarderCar CheckerOrder ClerkShip RunnerCloth BookerMerchandiserOrder FillerOrder WriterSheet WriterVault PersonVault WorkerBooking ClerkBreak Out ManExpress ClerkFish ReceiverFreight ClerkMilk ReceiverRouting ClerkFruit ReceiverFuel Oil ClerkGarment SorterPackage Sorter
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier A 7 rather than a 4 because the paperwork chain — PO matching, BOL generation, ASN reconciliation, carrier tracing — is essentially solved by EDI and WMS scanning, but the daily reality of a shorted pallet, a mislabeled SKU, or a carton whose contents don't match the manifest still requires someone to physically open it and decide what the system should say; that residual exception work is what keeps it out of the 0-6 band.
Some physical or field component At 11 you spend real time on a dock — cycle counting bins, breaking down and shrink-wrapping pallets, running a pallet jack or RF gun, checking seals and trailer temps — but it's inside a known building with fixed rack locations and posted dock doors, not the uncontrolled outdoor or customer-site conditions that push a score past 13.
No licence, no signature requirement A 1 because nothing you sign carries personal exposure: the BOL binds the carrier and shipper, the customs entry is the licensed broker's, and hazmat or FDA-regulated freight moves under the employer's registration and a trained-employee certificate that transfers with the job, not a license you hold.
Executes defined procedures on defined inputs A 4 because the calls you make — refuse or accept short, note damage as exception, put stock in quarantine, flag a count variance for research — are bounded by written receiving SOPs and dollar thresholds above which a supervisor or buyer decides, so the discretion is real but pre-scripted rather than open-ended.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (7/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (1/20) is whether the law requires a licensed human to sign. Trust premium (3/20) is whether buyers specifically pay for a person. Judgment and accountability (4/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 8 of this occupation's 26 points (31%).
Embodiment (11/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
No occupation passed every test: close enough to shipping, receiving, and inventory clerks on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.
The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.
Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:
That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 39/100 — EXPOSED.
Customs and controlled-goods paperwork is the one place a named human already signs. Expansion of DOT hazmat shipping-paper certification (49 CFR 172.204 requires a signed shipper's certification), FDA FSMA 204 traceability recordkeeping, or CTPAT/AES export filings requiring an identified, trained employee to attest to a specific receipt or manifest would attach personal accountability to a portion of these clerks. This raises the score only for the hazmat/food/export-facing subset, not the general dock clerk.
Damage inspection, carton opening, seal verification, and mixed-SKU count verification in non-standard environments (cross-docks, retail backrooms, cold storage) remain hard for robots. Score rises only in the sense that automating clerical work concentrates the job in these physical tasks; no policy change drives this.
Genuine two-tier structure: if scanning, EDI matching and BOL generation are fully automated, the residual role is discrepancy adjudication — deciding whether a short-count is theft, mis-pick, supplier shortage, or a system error, and whether to refuse a delivery. Where employers consolidate clerks into 'inventory control analyst' roles owning cycle-count variance investigation and root-cause writeups, the remaining day is mostly judgment tier.
If a named receiving clerk is designated the person who accepts or rejects a delivery under contract terms — signing off on OS&D (over, short, damaged) claims that become the basis for a freight claim or chargeback against a carrier — the role owns a consequential, contestable call. Some 3PL and retail DC contracts already make the receiver's notation the controlling evidence in claim disputes.
Pharmaceutical distribution under DSCSA already requires verified handling and suspect-product quarantine decisions by designated personnel; extension of similar named-responsible-person requirements to other regulated receiving (medical devices, precursor chemicals) would harden a niche.
The limit. Even with every lever, this stays low. There is no realistic route to a trust premium — nobody selects a vendor because of who keys the receipt — and the liability and judgment gains apply only to regulated or claims-facing subsets (hazmat, pharma, customs, freight-claim receiving), which is a minority of the 817k. Realistic ceiling is roughly the high 30s, and only for those subsets; general dock and stockroom clerical work has no floor to stand on.
| New York-Newark-Jersey City, NY-NJ | 38,970 | $46,550 +3% |
| Los Angeles-Long Beach-Anaheim, CA | 33,250 | $45,980 +2% |
| Dallas-Fort Worth-Arlington, TX | 29,670 | $44,310 -2% |
| Chicago-Naperville-Elgin, IL-IN | 26,030 | $47,740 +5% |
| Houston-Pasadena-The Woodlands, TX | 22,670 | $41,590 -8% |
| Atlanta-Sandy Springs-Roswell, GA | 16,280 | $44,850 -1% |
| Phoenix-Mesa-Chandler, AZ | 15,790 | $45,840 +1% |
| Riverside-San Bernardino-Ontario, CA | 15,120 | $44,520 -2% |
| Seattle-Tacoma-Bellevue, WA | 12,520 | $56,370 +25% |
| Walla Walla, WA | 150 | $55,960 +24% |
| Kahului-Wailuku, HI | 120 | $55,950 +24% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 26. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.