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Will AI replace meter readers, utilities?

A little.

Smart meters absorb the reading, but inspections, tampering checks, service shutoffs and problems at the door still need someone on the route. This job scores 77 out of 100 on (higher is safer). Today people do 44% of the work with AI’s help, and 56% still needs a person.

Updated 3 October 2026 43-5041 7122 2026-Q4
Office and Administrative SupportMeter Readers, Utilities43-5041 · 2026-Q4
0% AI does it44% AI helps56% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 56%AI helps 44%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the route matters more than the reading

The part of this job that software can take is the easiest part: look at a dial or display, write down the number, move on. Smart meters and advanced metering infrastructure send that number by themselves, and image-recognition tools can read a legacy dial from a photo. That is real task erosion, and it has been running for years through hardware, not chatbots.

What software does not do is walk the route. Meter readers find meters behind locked gates, in basements, under snow, and in yards with dogs. They inspect meters for damage, leaks, corrosion and signs of tampering. They connect and disconnect service, leave notices, and explain a strange bill to the person standing at the door. Those tasks are why the work has not gone quietly with the meters.

The job is shrinking all the same. The Bureau of Labor Statistics counts about 19,430 meter readers in US utilities, with median pay of $48,150, and projects employment falling 10.5% between 2025 and 2035 (BLS, 2025). Fewer routes, fewer entry-level openings, and more of the remaining work pushed toward inspection and field service: that is the honest shape of it, and it is why this job sits on our list of jobs expected to shrink.

What software captures, what it assists, and what stays with a person

Reading and recording consumption is the clearest automation target. Remote meters report usage on a schedule, and optical tools can pull a number off a mechanical dial without replacing the meter. Our task split puts a share of task time in the group AI can already handle (0%), and the headline coverage figure above the task list is scored the same way we score every job, explained on how we measure coverage.

Assistance is where most of the change shows up on a working day. Software flags readings that look wrong before a bill goes out, routes a reader to the stops that actually need a visit, and holds the history that tells you whether a jump in usage means a leak, a faulty register or a new hot tub. The share of task time in that assisted group is printed above (44%).

The rest stays with a person, and the chart shows how large that part is (56%). It is the physical and social work: getting access to a hard-to-reach meter, judging whether a seal has been cut, turning service on or off safely, and dealing with a customer who is angry, confused or simply not home. Our robotics estimate above marks the physical slice and the hardware class that would be needed to do it — mobile robots, not fixed arms — which is a far harder and costlier build than reading a digit.

What the evidence actually shows

There is no published head-to-head test of AI against meter readers in the field, so our parity grade for this job is D, and we give no parity number. Vendor accuracy claims for optical reading are not the same thing as a measured comparison, and we do not treat them as evidence.

What would settle it is specific: a dated trial across meter types and conditions — glass fogged, dial worn, display dead, enclosure flooded — reporting read accuracy, exception rates, revisit rates and billing disputes for automated capture against a trained reader doing the same routes. Access and inspection outcomes would need to be measured too, because that is where the human share of the work sits. Until something like that is published, the honest answer is that the reading task is well covered and the field task is untested. The grading scale, including what a D means, is set out in how we grade quality parity.

When the balance could tip

Most likely after 2036 (8 in 10 of our scenarios). The method behind that window, and what it does and does not claim, is described in how we estimate the replacement year.

Two things could pull it earlier. Funded smart meter rollouts finishing in a service territory remove the daily read in one step. And cheap retrofit modules that read legacy dials in place lower the cost of covering the meters a utility is not ready to replace, which is why our cost comparison above puts automated reading well under a staffed route.

Two things hold it back. Customers refuse or opt out of smart meters in some states, and an opt-out meter still needs a visit. And access is stubbornly physical: a meter in a locked basement, a crawlspace or a flooded pit needs a person, as do shutoffs, tamper investigations and leak checks. Replacing a working meter fleet is capital spending that moves on utility-commission timelines, not software release cycles.

What to do: if your territory has an active AMI program, ask now which crew keeps the inspection, connect and disconnect work once the reads go remote.

How to stay needed on the route

Lean into the tasks that stay with people. Inspection is first: spotting damage, corrosion, tampering and the usage pattern that means a leak. Service work is second: safe connects, disconnects and reconnects, and the paperwork and safety rules around them. Customer contact is third: handling the disputed bill, the refusal, the no-access property and the exception that software kicks out.

Two skills travel well from here. One is meter data work — reading AMI exception reports and knowing which flag needs a truck roll and which does not. The other is utility field safety and compliance: gas, water or electric basics, lockout rules and documentation that holds up in an audit.

If you want a next step rather than a side step, the nearest work by code and by day-to-day task is weighers, measurers, checkers and samplers. Field inspection skills carry into work as an energy auditor, and the licensed, hands-on end of utility work sits with electrical power-line installers and repairers. You can put any two of them side by side on our job comparison tool.

For the wider picture, this job sits in the material recording and dispatching family and in the utilities sector, where scores for related roles are listed together. How every figure on this page is built is set out in our scoring method.

Frequently asked questions

Why do some people say no to smart meters?

Common reasons are cost concerns, privacy worries about detailed usage data, doubts about billing accuracy after an install, and health or radio-frequency concerns. Some customers simply prefer not to have equipment changed on their property. Utilities usually handle refusals through an opt-out program, which keeps a manual read on the schedule. Those opt-out properties are part of why field visits have not disappeared.

Can I refuse to have a smart meter installed?

It depends on your state and your utility. Many US utilities run an opt-out or non-communicating meter option approved by the state utility commission, often with a one-time fee and a monthly charge to cover manual reading. Some territories have no opt-out at all. Check your utility’s tariff page or ask your state public utility commission, since the rules differ by service area and fuel type.

Are meter readers being forced out by automation?

The pressure is real but gradual. Remote metering removes the daily read, so utilities post fewer new routes and often move existing staff into inspection, connects and disconnects, or field service. The Bureau of Labor Statistics projects employment in this job falling 10.5% from 2025 to 2035 (BLS, 2025). That is a shrinking entry point, not a sudden end to the work.

How accurate is AI reading of old mechanical meters?

Optical and image-recognition tools can read clear dials and digital displays reliably. Accuracy drops with fogged glass, worn digits, partial rotations, poor light and obstructed enclosures, which is why vendors pair reads with validation and exception flags. No published field trial compares these systems with trained readers across meter types, so the evidence grade shown above this section stays low for now.

Are electricians going to be replaced by AI?

Electrical work is mostly physical, code-bound and done in awkward, varied spaces, so it sits very differently from desk work. Software already helps with design, load calculations, estimating and diagnostics. The install, repair and inspection work needs hands and a license. You can look up electricians and related trades on our rankings page to see how each one is scored.

What should a meter reader learn next?

Start with the work the task list above puts in the human group: inspection, tamper and leak detection, and safe service connects and disconnects. Add meter data handling so you can triage AMI exception reports, and get formal safety or compliance training for your fuel type. Those skills move you toward field service, metering technician and auditing roles rather than out of the sector.

Each ridge is a slice of the job's task time.Needs a human 56%AI helps 44%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Meter Readers, Utilities, O*NET-SOC 43-5041. 56% of the job’s task time still needs a human, so 56 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 56% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 56%AI helps 44%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 56%AI helps 44%AI does it 0%
Read electric, gas, water, or steam consumption meters and enter data in route books or hand-held computers.Needs a human
Upload into office computers all information collected on hand-held computers during meter rounds, or return route books or hand-held computers to business offices so that data can be compiled.AI helps
Walk or drive vehicles along established routes to take readings of meter dials.Needs a human
Verify readings in cases where consumption appears to be abnormal, and record possible reasons for fluctuations.AI helps
Install new or replace broken meters.Needs a human
Inspect meters for unauthorized connections, defects, and damage, such as broken seals.Needs a human
Perform preventative maintenance or minor repairs on meters.Needs a human
Answer customers' questions about services and charges, or direct them to customer service centers.AI helps
Report to service departments any problems, such as meter irregularities, damaged equipment, or impediments to meter access, including dogs.AI helps
Leave messages to arrange different times to read meters in cases in which meters are not accessible.AI helps
Dig dirt away from meters to take readings.Needs a human
Report lost or broken keys.AI helps
Connect and disconnect utility services at specific locations.Needs a human
Update client address and meter location information.AI helps
Collect past-due bills.Needs a human

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: no sooner than 2036

Most likely after 2036 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
A little.
By 2045
60%
of our scenarios have AI largely doing this job by 2045 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)
By 2060
90%
of our scenarios have AI largely doing this job by 2060 (Largely.)
10% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could do a little of this job (A little.)100%Today2030: 80.0% of scenarios: AI could do a little of this job (A little.)80%2030: 20.0% of scenarios: AI could partly do this job (Partly.)20%20302035: 30.0% of scenarios: AI could do a little of this job (A little.)30%2035: 30.0% of scenarios: AI could partly do this job (Partly.)30%2035: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2035: 10.0% of scenarios: AI could largely do this job (Largely.)10%20352040: 10.0% of scenarios: AI could do a little of this job (A little.)10%2040: 20.0% of scenarios: AI could partly do this job (Partly.)20%2040: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2040: 50.0% of scenarios: AI could largely do this job (Largely.)50%20402045: 10.0% of scenarios: AI could do a little of this job (A little.)10%2045: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2045: 60.0% of scenarios: AI could largely do this job (Largely.)60%20452050: 10.0% of scenarios: AI could do a little of this job (A little.)10%2050: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%2050: 80.0% of scenarios: AI could largely do this job (Largely.)80%20502055: 10.0% of scenarios: AI could do a little of this job (A little.)10%2055: 90.0% of scenarios: AI could largely do this job (Largely.)90%20552060: 10.0% of scenarios: AI could do a little of this job (A little.)10%2060: 90.0% of scenarios: AI could largely do this job (Largely.)90%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%100.0%0.0%
20300.0%0.0%20.0%80.0%0.0%
203510.0%30.0%30.0%30.0%0.0%
204050.0%20.0%20.0%10.0%0.0%
204560.0%30.0%0.0%10.0%0.0%
205080.0%10.0%0.0%10.0%0.0%
205590.0%0.0%0.0%10.0%0.0%
206090.0%0.0%0.0%10.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 2.6 out of 5 for consequence and decisions 3.8 out of 5 for impact; someone has to answer for them.
Clients want a personFace-to-face contact is rated 4.8 and physical closeness 3.9 out of 5; caring for or serving people is 2.4 out of 5 in importance.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
RegulationWorkers rate responsibility for others' health and safety 3.0 out of 5.
Physical work46% of the task time is physical; robots have been shown on 100% of that time.
LicensingUsual entry requirement (BLS): high school diploma or equivalent, then short-term on-the-job training.

What would it cost to hand the work to AI?

The share of the year AI could handle (414 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$40–$4,140
A person’s wage for the same hours
$6,910–$17,100

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

46%
of the task time is physical work
Mobile robots
the kind of robot the physical work would need
Commercial in warehouses, hospitals and some outdoor sites; hands are still limited.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 56%AI helps 44%AI does it 0%
Writing · 14.2% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 7.5% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 7% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 15.2% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 50.4% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 5.7% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 56%AI helps 44%AI does it 0%
How exposed is it?

Still needs a human: 77/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 56% needs a human, 44% AI helps, 0% AI does it. Still needs a human: 77/100 ↑ safer. Will AI replace them? A little.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 77/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

Smart meters and automated systems will replace many routine meter-reading tasks, but humans will still be needed for exceptions, inspections, and legacy infrastructure.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudeYes

Most utility meter reading has already been automated via smart meters and remote telemetry, and this trend will continue to eliminate the need for human meter readers within a decade.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While automated smart meters will eliminate the majority of manual reading roles, AI and automation won't completely replace human workers in the next decade due to legacy infrastructure, physical maintenance needs, and the slow pace of utility upgrades in rural areas.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI and smart meters will eliminate many traditional meter-reading jobs within the next decade, but field technicians will still be needed for exceptions, maintenance, and inspections.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Meter Readers, Utilities? A little. Still needs a human: 77/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/meter-readers-utilities/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.