EXPOSED
The core work — walking a route, knocking on doors, working a street cart, reading a stranger's face in the first three seconds and closing on the spot — is physical, in-person persuasion that language models cannot perform. But the shield is narrow: no license, no signature, minimal discretion, and the real threat to this occupation is not AI but e-commerce, targeted digital advertising, and app-based ordering, which have already shrunk US employment here to roughly 2,760. Lead lists, scripts, territory routing, and follow-up messaging are already generated by software.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $27,420 → $41,380 +20.7% 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
-10%
Percentage only. The projection counts a different population from the 2,760 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -10% 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.
~2,700 openings a year on average, including replacing people who leave.
HawkerVendorPeddlerHucksterBumboaterCanvasserDelivererBook AgentFulleretteLei SellerNews AgentDistributorKettle GirlCandy VendorFish PeddlerFruit VendorPillow AgentSales VendorCandy ButcherIce Cream ManKettle WorkerPaper CarrierPeanut VendorRoute Carrier
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier A knock, a doorstep read, and a same-visit close cannot be delivered by software, but the parts around it — territory routing, lead qualification, pitch scripts, price quotes, and follow-up texts — are already handled by CRM and ad-targeting tools, which is why this sits at 13 rather than up with trades work that resists digitisation end to end.
Hands-on in uncontrolled environments You are outdoors on foot in whatever weather, hauling product or pushing a cart, dealing with locked gates, dogs, stairs, and hostile residents on unfamiliar property — uncontrolled environments throughout — held just under the top band because the physical demand is walking and carrying rather than skilled manual technique.
No licence, no signature requirement There is no occupational license behind this work; the most you face is a municipal peddler or solicitation permit and a Do-Not-Knock registry check, and when a sale goes wrong it is the company's contract and the FTC three-day cooling-off rule that answer for it, not your signature.
Executes defined procedures on defined inputs Pricing, product line, financing terms, and refund policy come down from the employer or distributor; your calls are whether to keep talking, which house to try next, and how much stock to bring out — real choices, but low-stakes and reversible within a day, which is what puts this at 4.
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 (13/20 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 (2/20) is whether the law requires a licensed human to sign. Trust premium (9/20) 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 15 of this occupation's 43 points (35%).
Embodiment (15/20) 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 door-to-door sales workers, news and street vendors, and related workers 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 56/100, still EXPOSED.
Task-mix shift: once list-building, routing, scripting, and follow-up messaging are fully automated, what remains is only the unscripted doorstep read and objection handling. This raises the share of the remaining day AI cannot do — but note it raises resistance per remaining worker while shrinking headcount, which is the pattern already underway here.
State door-to-door solicitation statutes tightening so that the individual canvasser must be personally registered/permitted, badged, and named on the contract's right-of-rescission disclosure — with personal exposure for misrepresentation. Solar-financing fraud enforcement (California AB 1208-style proposals, FTC and multiple state AG actions against solar canvassers) is pushing toward per-canvasser registration rather than firm-level licensing.
Growth of the segments where the in-person pitch IS the product — solar/roofing/pest-control canvassing, direct-to-farm and farmers-market vending, and utility/broadband 'switch' campaigns where regulators (e.g. state PUC door-to-door marketing rules) require an identifiable human agent to present the offer rather than a robocall or app funnel. Also visible: municipal street-vendor licensing regimes (NYC's 2021 permit expansion) that formalize and protect physical vending stalls, making the human seller a scarce, licensed presence.
If canvassers move from script-readers to on-the-spot qualifiers who must make and document the eligibility, affordability, or cooling-off disclosure call before a contract is signed — a duty some state solar and home-improvement rules already attach to the person at the door.
The limit. The binding constraint is not AI capability but demand: e-commerce and targeted digital advertising have already reduced this to ~2,760 workers. Every lever above raises the per-worker score while the occupation continues to contract; a high resistance score on a vanishing job is not job security. No plausible route to a meaningful embodiment increase — the physical difficulty is already fully counted.
| Los Angeles-Long Beach-Anaheim, CA | 260 | $35,090 -15% |
| Portland-Vancouver-Hillsboro, OR-WA | 90 | $39,970 -3% |
| Dallas-Fort Worth-Arlington, TX | 70 | $49,330 +19% |
| New York-Newark-Jersey City, NY-NJ | 70 | $44,370 +7% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 50 | $35,590 -14% |
| Virginia Beach-Chesapeake-Norfolk, VA-NC | 40 | $31,550 -24% |
| Dallas-Fort Worth-Arlington, TX | 70 | $49,330 +19% |
| New York-Newark-Jersey City, NY-NJ | 70 | $44,370 +7% |
| Portland-Vancouver-Hillsboro, OR-WA | 90 | $39,970 -3% |
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 43. 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.