EXPOSED
This is a residual catch-all bucket, so the modal worker is a generalist seller — prospecting lists, sending outreach, quoting prices, demoing products, logging activity in CRM — and the prospecting, follow-up sequencing, quote generation, and pipeline notes are already the strongest use case for current AI. What survives is the part where a buyer wants a person in the room: reading hesitation, negotiating terms, and being the accountable face when the deal or the delivery goes sideways. No license protects the role, and volume-based seat counts are the first thing trimmed when AI raises per-rep throughput.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $31,820 → $48,280 +21.4% 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
+3.7%
Percentage only. The projection counts a different population from the 93,180 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +3.7% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~16,000 openings a year on average, including replacing people who leave.
ShorerGreeterShopperSponsorMeasurerAppraiserCollectorCounselorAuctioneerLiquidatorPawnbrokerBid AnalystFund RaiserPawn BrokerGift WrapperRug MeasurerSong PluggerStamp AnalystStore ShopperTicket BrokerCoin CollectorContact PersonPeople GreeterCirculation Man
The BLS uses Sales and Related Workers, All Other for work that doesn't fit any named occupation, so it covers roles that have little in common with each other. Two consequences worth knowing before you read anything below:
Holding it up: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier At 8, the split is real but lopsided: list building, cadence emails, quote-and-proposal assembly, and CRM hygiene — likely most of a rep's logged hours — are already being handed to tools, while the discovery call where a buyer talks himself out of a purchase and has to be talked back in still needs a human to hear the pause and change tack.
Some physical or field component A 7 reflects that most of the week is phone, email, and video, but this bucket absorbs event and trade-show sellers, in-home demo reps, and route-and-territory canvassers who carry samples, set up booths, and drive to the buyer's site — physical presence that shows up in some jobs here, not in the baseline one.
No licence, no signature requirement A 2 rather than 0 acknowledges that some employers require product-specific certification badges and background checks, but nothing here is a state license: no exam gates the work, no registry can be struck, and the employer or manufacturer absorbs any misrepresentation claim.
Meaningful discretion An 8 covers the discretion that actually exists — how far to discount inside an approved band, which objection to concede, whether an account is worth the quarter's attention — while pricing floors, contract terms, and credit approval sit with sales management and finance, so the rep rarely owns the call that can't be reversed.
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 (8/20 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 (10/20) is whether buyers specifically pay for a person. Judgment and accountability (8/20) 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 20 of this occupation's 35 points (57%).
Embodiment (7/20) 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.
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 49/100, still EXPOSED.
Task-mix shift: once AI absorbs prospecting, sequencing, quoting and CRM hygiene, the surviving seat is the complex-deal tier — multi-stakeholder negotiation, custom terms, on-site demos, escalation recovery. This is a genuine two-tier occupation, but the shift raises per-seat resistance while cutting seat count, so the register score rises for a smaller population.
Buyer-side procurement rules that require a named human account representative and prohibit AI-only quoting on contracts above a threshold — visible already in some enterprise and government vendor terms and in state bills restricting automated pricing/AI-set prices (e.g. California and New York algorithmic-pricing disclosure bills). If a named human of record becomes a standard contract clause, the premium hardens.
Discount and concession authority formally delegated to the rep with a signed approval of record, as AI recommends but cannot authorize — the pattern in existing CPQ approval-matrix policies. Codified as a human-authorization gate in deal desk rules, the role owns the consequential call.
Sector-specific licensing pulling parts of this residual bucket into regulated selling: e.g. state insurance producer or securities registration extended to adjacent product sellers, or FTC/state enforcement on AI-generated sales claims requiring a named human to attest to representations made in a quote or demo. Narrow, because the bucket is unlicensed by definition.
The limit. Realistic ceiling is mid-50s. The bucket is a residual SOC code with no professional body, no license, and no unified employer, so nothing can shield it uniformly; whatever survives is headcount-thinned enterprise closers, and the register score rises for the remnant rather than for the 93,180.
| Los Angeles-Long Beach-Anaheim, CA | 12,330 | $50,840 +5% |
| Denver-Aurora-Centennial, CO | 4,270 | $63,110 +31% |
| New York-Newark-Jersey City, NY-NJ | 3,860 | $74,530 +54% |
| Dallas-Fort Worth-Arlington, TX | 3,070 | $39,790 -18% |
| San Francisco-Oakland-Fremont, CA | 3,010 | $60,050 +24% |
| Houston-Pasadena-The Woodlands, TX | 2,510 | $38,820 -20% |
| Atlanta-Sandy Springs-Roswell, GA | 2,430 | $52,080 +8% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 2,370 | $38,330 -21% |
| Bellingham, WA | 40 | $81,120 +68% |
| Waterbury-Shelton, CT | 80 | $79,640 +65% |
| Spokane-Spokane Valley, WA | 90 | $76,120 +58% |
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 35. 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.