COOKED
The core task — walking a route to visually record consumption figures and upload them — has already been replaced at scale by advanced metering infrastructure that transmits readings automatically, and the remaining office work (flagging anomalous usage, logging re-reads, printing notices) is exactly the pattern-matching AI does cheaply. The job's one real moat is physical: you still need a person to get into a fenced backyard, a flooded basement, or a rural crawlspace when a meter fails or a tamper is suspected, and that is where surviving headcount is migrating. Employment has been falling for over a decade and the trend line is set by utility capital spending on smart meters, not by AI capability.
Part 2020 shock, part continued decline in the years since.
Median pay $42,280 → $48,150 -8.9% 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
-12% 20,100 → 17,700 on the projections basis
Exposed, and shrinking
Both signals point the same way: the tasks are largely automatable and the BLS projects -12% 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.
~1,300 openings a year on average, including replacing people who leave.
FieldmanMetermanMeter ReaderService WorkerUtility WorkerMeter InstallerUtility LocatorWater InspectorField TechnicianGas Meter ReaderMeter TechnicianMeter Record ClerkSteam Meter ReaderUtility TechnicianWater Meter ReaderMeter Reading ClerkWater Use InspectorUtilities TechnicianElectric Meter ReaderField Service EngineerMeter Reader InspectorUtility Service WorkerUtility Meter TechnicianDamage Prevention Specialist
Holding it up: embodiment . Weakest point: liability shield .
Core tasks are already automatable Reading a dial or encoder register and keying it into a handheld is a data-capture task AMI radios already do every 15 minutes without you, and the desk residue — comparing this cycle's kWh against last year's, tagging high/low reads for re-read, generating disconnect door hangers — is threshold logic, which is why 5 rather than 10.
Some physical or field component You are outdoors in whatever weather the route gives you, opening meter pits, dealing with dogs, locked gates, snow-covered lids and spider-filled basements, but the destination is a known address with a known meter type and you are not diagnosing or repairing anything, so this sits at 12 rather than the 16+ of a service technician pulling a meter under live voltage.
No licence, no signature requirement No state licences meter readers; a CDL for a route truck or a utility's internal safety card is the ceiling, and any billing error you record is corrected by the utility's revenue department under tariff rules, not charged to you.
Executes defined procedures on defined inputs Your discretion runs to deciding whether a read looks wrong enough to re-read, whether a broken seal or reversed dial warrants a tamper referral, and whether a dog makes the yard unsafe to enter — real calls, but each one is written into the route procedure and escalates to an investigator or supervisor rather than resolving 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 (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 (3/20) is whether buyers specifically pay for a person. Judgment and accountability (3/20) 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 7 of this occupation's 24 points (29%).
Embodiment (12/20) 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 41/100 — EXPOSED.
If the surviving role formally converts into a field meter technician/AMI maintenance position — smart-meter swap-outs, tamper investigation, communication-module replacement, disconnect/reconnect visits in occupied premises — the daily work becomes unstructured physical access to private property, which no deployed system does. Utilities in states with high AMI penetration (e.g. California IOUs, Texas ERCOT utilities) already redeploy readers into meter-services crews under existing IBEW/UWUA contracts.
Task-mix shift: once automated readings and AI anomaly flagging absorb the routine tier, what is left is the exception tier — obstructed access, suspected theft, meters whose transmitted data conflicts with physical dials, customer-disputed bills requiring an on-site verified read. If the job description is rewritten around exceptions rather than routes, resistance rises even with no new law.
If utility tariffs or state commission rules require a human field determination of record before a theft/diversion charge or estimated-bill correction is issued — i.e. the reader's written finding, not the AMI data stream, is what the utility relies on in a billing dispute or criminal referral — the role owns a consequential call. Some state commissions already require physical verification before back-billing for tampering.
If states extend gas-qualification requirements (DOT PHMSA Operator Qualification, 49 CFR 192 Subpart N) to the disconnect/reconnect and leak-check tasks these workers absorb, a named qualified individual must attest to each covered task. This is a real existing framework, not hypothetical, and already binds some gas meter personnel.
The limit. Even with every lever, this is a survival-by-relabelling story: the occupation code shrinks while a smaller field-technician role grows. Trust premium has no realistic route — no customer pays extra for a human to read a meter.
| New York-Newark-Jersey City, NY-NJ | 1,110 | $63,040 +31% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 400 | $83,350 +73% |
| Columbus, OH | 390 | $47,430 -1% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 380 | $42,280 -12% |
| Atlanta-Sandy Springs-Roswell, GA | 310 | $43,140 -10% |
| Tampa-St. Petersburg-Clearwater, FL | 310 | $40,100 -17% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 300 | $50,810 +6% |
| Dallas-Fort Worth-Arlington, TX | 270 | $44,670 -7% |
| San Francisco-Oakland-Fremont, CA | 140 | $100,480 +109% |
| Reno, NV | 40 | $89,460 +86% |
| Omaha, NE-IA | 60 | $87,320 +81% |
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 24. 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.