EXPOSED
The paperwork half of this job — lead research, spec sheets, quote configuration, proposal drafting, CRM notes, follow-up sequences, RFP responses — is already being absorbed by AI and sales-automation stacks, and that's a real chunk of the week. What survives is the part buyers actually pay for: standing in a plant or lab, watching how the customer really runs the process, running the demo, negotiating multi-stakeholder deals, and being the person accountable when the equipment underperforms. Reps selling commoditized catalog items are far more exposed than those selling capital equipment or engineered systems with long, consultative cycles.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $81,020 → $104,920 +3.6% 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
+1.9% 303,200 → 308,900 on the projections basis
Growing, and only partly exposed
The BLS expects +1.9% more of these jobs by 2034, and at 50/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.
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.
~27,200 openings a year on average, including replacing people who leave.
SalesmanCanvasserSolar AdvisorSales EngineerSales AssociateSales AgronomistSales ConsultantSales SpecialistSolar ConsultantEnergy ConsultantAuthorized RetailerRetail MerchandiserSolar Sales AdvisorRetail Solar AdvisorSales RepresentativeSolar Sales AssessorSolar Sales EstimatorEnterprise SalespersonSolar Sales AmbassadorSolar Sales ConsultantSolar Sales SpecialistOutside Sales ExecutivePharmaceutical DetailerSolar Energy Consultant
Holding it up: trust premium . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier An 11 reflects the split week: quote configuration, spec lookup, RFP boilerplate, CRM hygiene and cadence email are automatable today, while diagnosing why a customer's mass-spec throughput is off spec during a plant walkthrough, or reading which of six stakeholders will actually block the PO, has no digital substitute — so roughly half the calendar resists and half does not.
Some physical or field component A 10 rather than a 4 because the demo and site survey are the job — measuring available floor space and utility drops, hauling a benchtop unit into a customer's QC lab, walking a production line in PPE — but the rep does not install, commission, or repair the equipment, and a large share of prospecting and follow-up runs from a laptop.
No licence, no signature requirement A 2 is correct: no state licence gates technical sales, and product warranties, performance guarantees, and regulatory claims are underwritten by the manufacturer's entity and its engineers, not by the rep whose name is on the quote — CSP or industry product certifications help you win deals but nothing legally requires a human to hold the account.
Meaningful discretion A 12 fits real but bounded discretion — you decide which configuration to propose, what to concede on price and terms within an approval matrix, whether to walk away from an unqualified opportunity, and how to sequence a multi-stakeholder committee — but pricing floors, discount authority, and contract language route through sales management, legal, and applications engineering rather than terminating with you.
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 (11/20 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 (15/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) 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 29 of this occupation's 50 points (58%).
Embodiment (10/20) 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 sales representatives, wholesale and manufacturing, technical and scientific products 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 65/100, still EXPOSED.
Task-mix shift is genuinely two-tiered here: if quoting, CRM hygiene, RFP boilerplate and lead qualification are fully absorbed by sales-automation stacks, what remains is on-site process observation, application engineering, demo execution and multi-stakeholder negotiation — work that requires reading an unfamiliar plant floor. Watch for the rep title collapsing into 'application engineer' or 'technical account manager' at capital-equipment vendors (already visible at Thermo Fisher, Danaher, Rockwell channel roles).
Narrow but real routes: state pesticide/agrichemical dealer licensing (already required in most states for ag chemical reps, with personal liability for recommendation), radiation-producing device and medical-device rep credentialing, and hospital vendor-credentialing regimes. If a state or a professional body extended a named-signer requirement to technical specification sign-off — e.g. requiring a licensed PE or certified applications specialist to sign engineered-system specs where AI produced the configuration — this moves meaningfully. Watch state boards of pharmacy/agriculture and NCHCR hospital credentialing rules.
If more OEMs tie commissioning and validation to the selling rep — e.g. FDA/GMP-regulated lab or pharma equipment where an IQ/OQ site acceptance test must be witnessed on the customer's premises, or semiconductor tool install-and-qual — the physical, unpredictable-site share of the week rises. Watch for vendor contracts bundling install/qualification into the sales role rather than a separate field-service org.
If compensation and contract structure shift so the rep personally owns performance guarantees — throughput/yield warranties on engineered systems, or shared-savings and outcome-based pricing where the rep's specification error is the vendor's loss — the role owns consequential ambiguous calls more explicitly. Watch for outcome-based contracting spreading from medical devices to industrial capital equipment.
Already high and hard to raise much. The one visible mechanism: buyers reacting to AI-generated outbound by refusing unattributed contact — enterprise procurement policies requiring a named human account owner of record, or FTC/state rules on AI disclosure in commercial solicitation making human-originated contact the only reliably deliverable channel.
The limit. Commodity catalog selling has no realistic route on any dimension — the levers above only apply to capital equipment, engineered systems, and regulated-product channels. Liability shield for this occupation is structurally weak: sales has almost no tradition of personal professional licensure outside agrichemicals and a few device categories, so a jump past ~8 is unlikely absent an unprecedented licensure regime.
| Dallas-Fort Worth-Arlington, TX | 13,400 | $99,270 -5% |
| Boston-Cambridge-Newton, MA-NH | 8,670 | $122,550 +17% |
| Austin-Round Rock-San Marcos, TX | 8,620 | $83,170 -21% |
| Seattle-Tacoma-Bellevue, WA | 7,910 | $129,550 +23% |
| Houston-Pasadena-The Woodlands, TX | 7,800 | $100,980 -4% |
| New York-Newark-Jersey City, NY-NJ | 7,800 | $133,690 +27% |
| Phoenix-Mesa-Chandler, AZ | 7,150 | $101,030 -4% |
| Los Angeles-Long Beach-Anaheim, CA | 6,450 | $107,020 +2% |
| San Jose-Sunnyvale-Santa Clara, CA | 2,790 | $167,630 +60% |
| Shreveport-Bossier City, LA | 350 | $163,320 +56% |
| Rochester, MN | 150 | $160,960 +53% |
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 50. 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.