SAFE
Wardens spend their days patrolling backcountry, waterways and hunting grounds by truck, boat, ATV and on foot — checking licenses and bag limits, seizing gear, making arrests, and running search-and-rescue in bad weather. AI and drones will absorb the surveillance and paperwork layers (camera-trap review, poaching pattern analysis, report drafting), but a sworn officer with arrest powers must still be physically present to detain a person, handle a firearm, and testify. The real constraint on this occupation is state agency budgets and headcount, not automation.
Most of this decline happened after 2021 — it is not the pandemic dip.
Median pay $57,500 → $74,060 +3.0% 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
-6%
Percentage only. The projection counts a different population from the 5,770 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Hard to automate, but shrinking anyway
The work resists current AI, yet the BLS projects -6% by 2034. Whatever is shrinking this occupation, the evidence does not point to automation — demand, demographics, offshoring and industry decline all shrink jobs that no machine could do.
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.
~500 openings a year on average, including replacing people who leave.
WardenGame AgentPark GuardFish WardenGame WardenPark WardenWoods WardenGame ProtectorResource OfficerWildlife OfficerState Game WardenWildlife ProtectorFishing Game WardenConservation OfficerFish and Game WardenMammal Control AgentState Game ProtectorState Wildlife OfficerWildlife Control AgentGame and Fish ProtectorFish and Wildlife WardenNatural Resource OfficerWildlife Control PartnerDistrict Resource Officer
Holding it up: embodiment . Weakest point: trust premium .
Tasks largely resist digitisation Reading a hunter's tag against a field-dressed carcass, judging whether a boat's live well is over limit, and taking a physical custody arrest are tasks no software completes — the parts that do fall (incident report drafting, camera-trap triage, license database queries) are real but sit around the edges of the encounter, which is why this is 15 and not 18.
Hands-on in uncontrolled environments A warden works alone in waders, on ATVs and patrol boats, in snow and dark, tracking blood trails and hauling drowning victims out of water — there is no controlled site anywhere in the job description, and 19 rather than 20 only reflects the desk hours spent on case files and court prep.
Licensed human required and personally liable You hold a state peace-officer commission under your fish-and-wildlife code with POST or equivalent academy certification, and your name goes on the citation, the seizure inventory and the probable-cause affidavit; it sits at 14 rather than 18 because the badge and arrest authority are delegated by the agency, which indemnifies and can revoke, unlike a portable professional licence.
Exists to be accountable for ambiguous calls You decide alone, out of radio range, whether a trespass shooting is a warning or a felony charge, whether to draw on an armed subject in the woods, and when to call off a search — 15 reflects that discretion running against statutory bag limits and charging standards rather than open-ended policy authorship.
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 (15/20 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 (14/20) is whether the law requires a licensed human to sign. Trust premium (11/20) is whether buyers specifically pay for a person. Judgment and accountability (15/20) 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 40 of this occupation's 74 points (54%).
Embodiment (19/20) 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 84/100, still SAFE.
State evidence and court rules that make AI/drone-derived detections inadmissible without a sworn warden's independent corroboration and testimony — the mechanism is already visible in state constitutional rulings against warrantless wildlife-agency surveillance of private land (e.g. the Tennessee open-fields litigation against TWRA over camera traps, and similar Institute for Justice suits in Pennsylvania and Virginia). If courts or legislatures require a warrant plus a named officer affiant for camera-trap and drone evidence, the sworn signature becomes structurally unavoidable rather than customary.
Task-mix shift as the surveillance and paperwork tier is absorbed: this occupation genuinely has two tiers, and the residual is felony poaching investigation, undercover commercial-trafficking work (Lacey Act cases), interstate case coordination, and courtroom testimony. If camera-trap review and report drafting go, the remaining day is disproportionately the judgment tier — no new law required.
State POST (peace officer standards and training) commissions extending certification and personal-liability rules to cover AI-assisted enforcement decisions — e.g. a rule that a citation or seizure initiated by an analytics flag must be reviewed and signed by a commissioned warden who is individually named in any wrongful-seizure claim, mirroring how body-camera and use-of-force review policies were folded into POST standards after 2020.
Formal expansion of warden discretion into codified charging-decision authority — some states already have warden-issued civil restitution assessments for illegally taken game and administrative license-revocation hearings where the warden is the charging party. If more states shift wildlife violations from court prosecution to agency administrative adjudication, the warden owns more consequential, contestable calls personally.
Already near ceiling at 19; the only route is formal designation of wardens as primary wilderness search-and-rescue and swiftwater/ice-rescue responders in state emergency-management plans, which some states do and others assign to sheriffs. Such designation hardens the physical-presence requirement but adds little to an already maxed score.
The limit. Trust premium is omitted deliberately: there is no buyer. Enforcement is a state monopoly funded by license fees and Pittman-Robertson excise revenue, and no hunter or angler chooses a human warden over an alternative. The binding threat to this occupation is not automation but appropriations — a state legislature cutting warden FTEs and justifying it with drone and analytics coverage reduces headcount without any dimension score moving. Watch agency budget lines and vacancy rates, not capability benchmarks.
| New York-Newark-Jersey City, NY-NJ | 90 | $73,130 -1% |
| Virginia Beach-Chesapeake-Norfolk, VA-NC | 80 | $63,060 -15% |
| Tampa-St. Petersburg-Clearwater, FL | 60 | $31,200 -58% |
| Atlanta-Sandy Springs-Roswell, GA | 50 | $79,440 +7% |
| Los Angeles-Long Beach-Anaheim, CA | 50 | $87,140 +18% |
| Syracuse, NY | 50 | $56,730 -23% |
| Houston-Pasadena-The Woodlands, TX | 40 | $85,980 +16% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 40 | $76,290 +3% |
| Sacramento-Roseville-Folsom, CA | 40 | $105,780 +43% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 40 | $89,300 +21% |
| Albany-Schenectady-Troy, NY | 30 | $89,110 +20% |
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 74. 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.