EXPOSED
This is a catch-all bucket — campus safety monitors, fire watch and life-safety attendants, court and facility security aides, animal control and park protection staff — and the modal worker is an unarmed, on-foot presence who patrols, observes, logs, and escalates. The physical presence and the ability to walk into an unscripted human situation (an agitated visitor, an unlocked door, a smoke alarm at 2am) are genuinely hard to automate; the observation-and-reporting half is exactly what camera analytics, badge systems, and automated incident logging are already eating. Little licensure and modest formal authority mean the job is protected by bodies-in-buildings economics, not by law.
Most of this decline happened after 2021 — it is not the pandemic dip.
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.
BLS projection, 2024–2034
+2.5% 84,000 → 86,100 on the projections basis
Growing, and only partly exposed
The BLS expects +2.5% more of these jobs by 2034, and at 48/100 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.
~23,300 openings a year on average, including replacing people who leave.
RangerShopperTipstaffBus EscortBus MatronSki PatrolBus MonitorPark RangerHall MonitorFederal AgentWarrant ServerStore DetectiveCafeteria MonitorGamewell OperatorPlayground MonitorPolygraph ExaminerSchool Bus MonitorSecurity AmbassadorSecurity SpecialistLoss Prevention AgentLoss Prevention GuardPrevention SpecialistProtection SpecialistAsset Protection Agent
The BLS uses Protective Service 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: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Walking a stairwell at 2am to check that a fire door actually latched, or talking an agitated visitor back out of a lobby, is not something a fixed camera does — but the other half of the shift (watching monitors, writing incident logs, checking badge swipes, filing shift reports) is already handled by video analytics and access-control software in the buildings that have budget for it, which is what puts this at 12 and not 16.
Hands-on in uncontrolled environments The post is a physical post: foot patrols across parking structures and grounds, fire watch standing next to a disabled sprinkler riser, animal control working a loose dog in a stranger's yard, court aides screening bags and hands-on wanding — all in weather, at night, in spaces nobody controls, and it lands at 15 rather than 18 only because much of a shift is spent stationary at a desk or gate.
No licence, no signature requirement Most of these jobs need a state guard registration or a short certification card at most — fire watch training, animal control certification, a background check — and it is the property owner, the hospital, the university, or the contracting security firm that carries the liability when something goes wrong; nothing is signed in your name.
Meaningful discretion You decide in the moment whether a situation is a conversation, a call to the desk, or a 911 call, and that call has consequences — but standing orders, post orders, and the explicit instruction to observe-and-report rather than intervene mean the hard calls are escalated to sworn officers or facility management, which caps this at 9.
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 (12/20 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 (4/20) 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 (9/20) 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 21 of this occupation's 48 points (44%).
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.
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.
Insurer and AHJ practice: property carriers (FM Global, Zurich) already condition coverage during sprinkler impairment on a documented human fire watch with signed rounds. If carriers explicitly refuse to accept camera/thermal analytics as a substitute for the signed watch, the requirement hardens into a contractual mandate rather than a staffing preference.
Two-tier split is real here: the routine tier (camera monitoring, badge checks, patrol logs) automates, leaving unscripted human de-escalation, physical intervention, and alarm verification. Formal crisis-intervention/mental-health-response certification (CIT-style, already spreading to campus and transit safety staff) makes the residual tier the whole job.
State-level guard-card expansion to currently exempt roles: several states (California BSIS, New York's Security Guard Act, Texas DPS PSB) already license contract guards but exempt in-house/proprietary campus and facility staff. If a state closes the proprietary-employee exemption — or if fire-watch attendants are brought under NFPA 601 / local fire-marshal certification with a named certified individual signing the fire-watch log during impairment of a sprinkler or alarm system — a specific human becomes the accountable, personally sanctionable signer for hot-work and system-outage watches.
Task-mix shift plus formal escalation authority: as analytics absorb the log-and-observe tier, what remains is the decision to evacuate, restrain, deny entry, or invoke a duty-to-warn. Codified in policy — e.g. campus Clery Act timely-warning authority or a behavioral-threat-assessment team seat where the officer's judgment triggers the alert — the role owns a consequential ambiguous call rather than relaying one.
Court-rule and statutory in-person presence: state court security standards and ADA/Title IX escort provisions that name a physical attendant — e.g. court rules requiring a human bailiff or security aide present during proceedings with a witness or juror — keep the body in the building regardless of sensor coverage.
The limit. Trust premium has no realistic route: buyers of unarmed patrol coverage are procurement departments buying hours at the lowest compliant price, not clients paying for a named human. Even with every lever above, the bucket stays a wage-floor occupation whose headcount tracks square footage and insurance terms, and the licensure gains would apply unevenly across a catch-all SOC — animal control and park staff would not benefit from fire-watch or court rules at all.
| Los Angeles-Long Beach-Anaheim, CA | 9,160 | $37,290 -12% |
| New York-Newark-Jersey City, NY-NJ | 3,880 | $57,920 +36% |
| San Francisco-Oakland-Fremont, CA | 2,820 | $44,490 +5% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 2,760 | $35,060 -18% |
| Seattle-Tacoma-Bellevue, WA | 2,750 | $42,170 -1% |
| San Diego-Chula Vista-Carlsbad, CA | 2,570 | $44,270 +4% |
| Denver-Aurora-Centennial, CO | 2,550 | $43,720 +3% |
| Riverside-San Bernardino-Ontario, CA | 2,400 | $43,050 +1% |
| Albany, OR | 90 | $70,180 +65% |
| Naples-Marco Island, FL | 50 | $69,240 +63% |
| Reno, NV | 150 | $63,250 +49% |
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 48. 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.