COOKED
The core of this job — answering and routing calls, taking messages, booking and confirming appointments, entering visitor data, answering routine questions about hours, services, and directions — is already handled at usable quality by voice AI, scheduling bots, and self-check-in kiosks. What holds is the physical front desk: greeting people who walk in, issuing badges, taking deliveries, calming a frustrated patient or client, and being the human someone can walk up to. That presence is real but cheap to consolidate, which is why one receptionist increasingly covers what three used to.
Part 2020 shock, part continued decline in the years since.
Median pay $30,050 → $38,010 +1.2% 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% 1,007,200 → 1,007,600 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects 0% 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.
~128,500 openings a year on average, including replacing people who leave.
QuoterGreeterRegistrarSchedulerCall TakerReceptionistUtility ClerkPeople GreeterRegister ClerkResearch ClerkSpace SchedulerTelephone ClerkClerk SpecialistFront Desk ClerkHospitality AideIn File OperatorOffice AssistantOutpatient ClerkSpa ReceptionistAppointment ClerkCall Center AgentMedical SchedulerAppointment SetterFront Desk Officer
Holding it up: embodiment . Weakest point: liability shield .
Core tasks are already automatable Call routing, message-taking, appointment booking and confirmation reminders, visitor log entry, and answering "what are your hours / where is Suite 300" are the bulk of the shift, and each of those is already shipped as a product — which is why this sits at 5 rather than 10; the only tasks that don't fall are the ones that need a body in the lobby, not a different kind of thinking.
Some physical or field component You are tied to a specific chair in a specific lobby — badging visitors in, signing for FedEx, buzzing the door, walking someone to a conference room — so this isn't remote-capable screen work, but it's a climate-controlled front desk with no tools, no lifting beyond a package, and no unpredictable site conditions, which caps it at 10 instead of the high teens a field technician earns.
No licence, no signature requirement No state licence, no board, no certification exam gates the front desk; a temp agency can place someone tomorrow, and when a message is lost or a wrong visitor is admitted the exposure lands on the employer's policy, not on you personally — hence 1 rather than 0 only because HIPAA-covered front desks carry a thin, employer-mediated confidentiality duty.
Executes defined procedures on defined inputs The decisions are scripted or escalated: who gets put through, who waits, who gets the manager, which form to hand over, and the genuinely ambiguous calls — admitting an angry non-appointment patient, a security concern, a billing dispute — get pushed up the chain rather than owned, leaving 4 for the real triage discretion in how you sequence a full waiting room.
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 (5/20 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 28 points (46%).
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 receptionists and information 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 42/100 — EXPOSED.
Task-mix shift: this job genuinely has two tiers. Once routing, booking, confirmations and FAQ are fully absorbed by voice agents, what remains is exception handling — the walk-in whose insurance was denied, the person the bot could not parse, the angry visitor, the delivery that needs a signature and a decision. If headcount collapses onto that residue rather than being eliminated, the remaining role's non-automatable share rises even as total jobs fall.
Physical-security and access-control mandates that require a staffed, human-verified visitor screening point rather than a kiosk — e.g. hospital infant-abduction and workplace-violence prevention requirements under Joint Commission Environment of Care standards, state hospital workplace-violence laws (CA SB 553, NY S4451A), and school visitor-screening statutes (Alyssa's Law-adjacent front-office rules) that name a person at the entrance, plus courthouse/clinic entry screening. Concrete watch item: a Joint Commission or state DOH survey citation for unstaffed check-in.
Narrow, segment-specific: luxury hotels, private wealth management, concierge medicine, and law firms that market a named human at the door, plus a visible backlash market (businesses advertising 'a real person answers our phone' after customer-satisfaction damage from voice bots). Also possible via state consumer laws requiring a human option on calls — CA AB 1018-style bot-disclosure and 'human alternative' provisions. Applies to a minority of the 910k and does not lift the occupation's floor.
Front desk formally designated as the accountable node in a safety or privacy protocol: HIPAA-facing patient identity verification where the desk owns the match, or an active-threat/lockdown role where the receptionist is the designated initiator under a written emergency plan (already written into many school and hospital plans). This is role-design change inside employers, not new law, and is checkable in job descriptions and emergency operations plans.
The limit. No plausible route to liability_shield — there is no license, no scope of practice, and no personal liability to attach; every credible lever here is small and segment-limited. Even if all fire, this stays in the low-to-mid 40s with far fewer positions: the levers change what the surviving job looks like, not how many survive.
| New York-Newark-Jersey City, NY-NJ | 74,190 | $44,690 +18% |
| Los Angeles-Long Beach-Anaheim, CA | 35,000 | $43,280 +14% |
| Chicago-Naperville-Elgin, IL-IN | 30,540 | $38,060 +0% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 22,210 | $38,030 +0% |
| Dallas-Fort Worth-Arlington, TX | 21,380 | $37,060 -2% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 19,850 | $37,570 -1% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 17,920 | $41,240 +8% |
| Houston-Pasadena-The Woodlands, TX | 17,140 | $35,350 -7% |
| San Francisco-Oakland-Fremont, CA | 8,510 | $49,450 +30% |
| Fairbanks-College, AK | 160 | $47,260 +24% |
| San Jose-Sunnyvale-Santa Clara, CA | 3,990 | $47,130 +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 28. 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.