EXPOSED
The floor work — greeting customers, pulling sizes, demonstrating a product, cleaning and facing shelves, ringing up and processing returns — is physical and happens in a messy public space that robots handle poorly, which is the main thing holding this job in place. But the informational half of the job (product comparisons, availability lookups, recommendations, upsell scripting) is already what search, chatbots and app-based assistants do, and the real pressure on headcount comes from e-commerce, self-checkout and scan-and-go rather than from AI replacing a salesperson one-for-one. There is no license, no sign-off, and little consequential discretion, so nothing shields the routine tier.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $25,250 → $35,410 +12.2% 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
-0.5% 3,936,700 → 3,917,100 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -0.5% 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.
~555,800 openings a year on average, including replacing people who leave.
ClothierSalesmanShop GirlArt DealerCar DealerMeat ClerkShoe ClerkAuto DealerDairy ClerkFloor ClerkHaberdasherSales ClerkSalespersonShoe FitterShop WorkerStore ClerkBakery ClerkCar SalesmanMeat HostessRetail ClerkSales PersonLayaway ClerkShoe SalesmanBeauty Advisor
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Half the shift can't be scripted away — unboxing and steaming a garment, walking a customer to aisle 12, fitting a shoe, clearing a jammed register, recovering a ransacked display — but the part customers actually ask for, "which of these two TVs is better and do you have it in stock," is already answered by the phone in their hand, which is why this sits at 10 rather than in the resistant teens.
Hands-on in uncontrolled environments The work is on your feet for a full shift moving real merchandise — reaching stock, hauling boxes from the back, dressing mannequins, handling a public floor where spills, crowds and shoplifters change conditions minute to minute — but it's still an enclosed, lit, mapped building rather than a roof or a roadside, which puts it at the bottom edge of the hands-on band instead of the top.
No licence, no signature requirement There is no state licence, no continuing-education requirement and no exam to sell a sofa or a sweater; the store's corporate entity carries the consumer-protection and warranty exposure, and the only credential in play is a company POS training module, so there is effectively nothing personal standing between you and a staffing decision.
Executes defined procedures on defined inputs Discounts, price matches, return exceptions and holds run off a written policy with a manager override for anything outside it, and the daily calls — which size to suggest, whether to open a new register — are reversible within minutes, so the 4 reflects the small real latitude on the floor rather than any authority over consequential outcomes.
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 (10/20 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 (8/20) 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 13 of this occupation's 36 points (36%).
Embodiment (13/20) 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.
Waiters and Waitresses EXPOSED
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 51/100, still EXPOSED.
Store formats that keep goods behind glass or in locked cases (already spreading across CVS, Walgreens, Target for theft control) force an associate to physically unlock, retrieve and escort for each transaction; if loss-prevention insurance underwriters make locked-fixture staffing a condition of coverage, the in-aisle physical component becomes structural rather than optional
Genuine two-tier split: as lookups, comparisons and checkout move to the customer's phone, the residual role becomes de-escalation, fraud-sniffing on returns, fitting, and closing hesitant high-ticket buyers. This raises the score only for the surviving headcount — it is a task-mix effect on a shrinking base, not protection for the occupation's size
Categories where fit, feel or one-off provenance drives the purchase — bridal, mattresses, hearing-adjacent audio, jewelry, high-end footwear, guitar shops — already sell the human as the product; if e-commerce return-rate costs push more chains toward commissioned specialist floors (as Warby Parker, Nordstrom personal styling and Best Buy's in-home advisor programs did) the paid-for-a-human share of the occupation rises
Return-fraud and organized-retail-crime pressure pushing discretionary authority down to the floor — associate-level override on refunds, ID checks, refusal of service — plus state age-verification enforcement (tobacco, vape, alcohol, cannabis, aerosol paint) where the clerk personally absorbs the citation
Narrow route only: state-mandated seller certification with personal penalties, as in cannabis dispensary agent licensing (CO, IL), firearms counter staff under ATF Form 4473, and pharmacy-adjacent pseudoephedrine logs. Expansion of such per-clerk licensing to more restricted categories would shield those sub-segments — but it cannot reach general merchandise floor staff, which is the bulk of the 3.9M
The limit. The binding threat here is not AI capability but channel shift — e-commerce, self-checkout, scan-and-go. Every lever above protects a subset (locked-case, specialist, licensed-category) while the general merchandise floor keeps thinning; a higher score for the survivors is compatible with far fewer of them.
| New York-Newark-Jersey City, NY-NJ | 202,080 | $38,280 +8% |
| Los Angeles-Long Beach-Anaheim, CA | 130,650 | $37,700 +6% |
| Dallas-Fort Worth-Arlington, TX | 100,340 | $33,400 -6% |
| Chicago-Naperville-Elgin, IL-IN | 96,950 | $35,820 +1% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 91,370 | $34,330 -3% |
| Atlanta-Sandy Springs-Roswell, GA | 84,970 | $32,850 -7% |
| Houston-Pasadena-The Woodlands, TX | 78,960 | $31,340 -11% |
| Phoenix-Mesa-Chandler, AZ | 69,060 | $35,960 +2% |
| San Jose-Sunnyvale-Santa Clara, CA | 18,340 | $44,220 +25% |
| San Francisco-Oakland-Fremont, CA | 39,460 | $43,850 +24% |
| Seattle-Tacoma-Bellevue, WA | 46,620 | $42,080 +19% |
Target · Walmart · IKEA · Home Depot · Costco · German grocery retailer
MJBizDaily reports that California cannabis regulators approved the use of self-checkout systems at a licensed cannabis retailer.
New York Post reports a New York state legislative proposal that would require retailers to give shoppers a 10% discount for using self-checkout.
CIO.com reports on IKEA's deployment of a customer-facing chatbot and the business results derived from it.
Retail Dive reports Home Depot has added AI phone agents to handle incoming calls at its stores.
Retail Customer Experience reports that shoppers are observing Costco moving from self-checkout terminals to scan-and-go mobile checkout in stores.
Spectrum News reports proposed Ohio legislation that would impose requirements on retailers operating self-checkout lanes.
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