EXPOSED
The core of this job is physically handling instruments — mounting a pressure transducer on a deadweight tester, aligning optical comparators, torquing fixtures, running a thermocouple through a bath — which today's robotics cannot do across the messy variety of customer equipment and plant floors. What AI does erode is the paperwork half: calibration certificates, uncertainty budgets, drift trend analysis, procedure write-ups, and ISO 17025 documentation packages are all text-and-spreadsheet work that automates well. Accreditation regimes require a named, competent technician to sign results, which slows substitution without legally locking it the way an engineering stamp or nursing license does.
Headcount grew steadily across the period.
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
+4.7% 15,800 → 16,500 on the projections basis
Growing, and only partly exposed
The BLS expects +4.7% more of these jobs by 2034, and at 51/100 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.
~1,400 openings a year on average, including replacing people who leave.
Test TechnicianCalibration EngineerEquipment TechnicianElectronic TechnicianHydrometer CalibratorInstrument TechnicianCalibration SpecialistCalibration TechnicianMaintenance TechnicianCalibration CoordinatorCalibration TechnologistField Service TechnicianInstrumentation TechnicianMobile Technician (Mobile Tech)Powertrain Calibration EngineerCertified Calibration TechnicianElectromechanical Equipment TesterElectronics Calibration TechnicianDiagnostic Technician (Diagnostic Tech)Electronic Instrument Testing TechnicianMetrology Calibration Technician (Metrology Calibration Tech)
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier Automated calibration software already sequences multimeter and pressure-controller runs, captures readings over GPIB/Ethernet, and generates as-found/as-left tables without a human touching a keyboard — but someone still has to select the standard with adequate TUR, build the fixture, decide whether a failing gauge gets adjusted or condemned, and troubleshoot an instrument that drifts nonlinearly, which is why this sits at 12 and not down in the automatable band.
Hands-on in uncontrolled environments Work happens on plant floors, in temperature-controlled labs, and at customer sites: hauling standards in a van, mounting torque wrenches and transducers, running thermocouples through salt and oil baths, cleaning and shimming optical comparators, working around live 480V panels and pressurized lines — 15 rather than 18 only because a meaningful share of the day is spent in a bench-and-terminal environment you control.
Certification preferred, not legally required ISO/IEC 17025 and ANSI/NCSL Z540.3 require a named, technically competent person to authorize each certificate, and ASQ CCT or NCSLI credentials are routinely demanded by accredited labs — but that is an accreditation-body finding against your employer, not a state licence that can be revoked from you personally, so it delays substitution rather than blocking it.
Meaningful discretion Most decisions run off written procedures and published tolerances, but you own the genuinely ambiguous calls: whether an out-of-tolerance finding triggers a reverse-traceability notification on every part measured since the last cal, whether to guard-band a marginal pass, and how to justify an uncertainty budget contribution an assessor will challenge — discretion inside a documented framework, hence 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 (8/20) is whether the law requires a licensed human to sign. Trust premium (7/20) 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 24 of this occupation's 51 points (47%).
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.
No occupation passed every test: close enough to calibration technologists and technicians 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.
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 66/100, still EXPOSED.
Out-of-tolerance impact assessment becoming the explicit, documented duty of the technician: ISO 9001 cl. 7.1.5.2 and ISO 17025 cl. 7.10 already require assessing the validity of prior measurements when equipment is found out of tolerance. If customer quality agreements and auditors start naming the calibration technician (rather than the customer's QA engineer) as the owner of the reverse-traceability recall call, this rises.
Task-mix shift: this occupation has a genuine two-tier split. If certificate generation, drift trending and boilerplate procedure writing automate away, the residual job is measurement assurance design — choosing reference standards and TUR/guard-banding, building uncertainty budgets for non-standard setups, diagnosing why a UUT and a standard disagree, and interlab comparison work. Watch for job postings shifting title toward 'metrologist' or 'measurement assurance specialist' with the same SOC code.
ILAC/A2LA/ANAB policy explicitly addressing AI-assisted results: a requirement that every calibration certificate carry a named authorized signatory who holds documented competence for the specific measurement discipline, is personally accountable in audit findings, and cannot delegate uncertainty-budget approval to software. ILAC already issued guidance-type statements on remote assessment; an equivalent statement on AI-generated uncertainty budgets and certificates under ISO/IEC 17025:2017 cl. 7.8 and 8.5 is the specific thing to watch.
Regulated-sector layering: FDA 21 CFR Part 11 / Annex 11 enforcement (or an EU GMP Annex 11 revision, which is in active redraft) treating AI-produced calibration records as requiring a qualified human reviewer signature, plus NQA-1 (nuclear) and NADCAP AC7115 audit checklists adding a line item that AI-generated calibration data must be verified by a named technician.
Narrow route only: defense, nuclear and pharma contracts that specify on-site witnessed calibration by a named accredited technician, or ITAR/classified-site rules barring cloud-connected diagnostic tooling. This is a contract-clause premium, not a consumer preference; it will not generalize to general industrial calibration.
The limit. The realistic ceiling is roughly the mid-60s. The accreditation regime can strengthen a signature requirement but ISO 17025 competence attestation is not a state license with personal tort exposure, so liability_shield is unlikely to reach the 15+ range of stamped engineering or clinical roles. There is no plausible route by which buyers of calibration services pay a premium for humanness as such — the premium is for traceability, and traceability is transferable to instruments. Note also that embodiment, the largest single score here, is a capability dimension and can only fall: bench-top automated calibration systems for pressure, temperature and electrical parameters are already commercial, so the field-service variety argument erodes first for high-volume single-parameter work and holds longest for messy plant-floor and one-off fixture work.
| Houston-Pasadena-The Woodlands, TX | 1,930 | $78,610 +16% |
| Dallas-Fort Worth-Arlington, TX | 890 | $64,150 -5% |
| New York-Newark-Jersey City, NY-NJ | 630 | $71,950 +6% |
| Los Angeles-Long Beach-Anaheim, CA | 430 | $71,640 +6% |
| San Juan-Bayamon-Caguas, PR | 430 | $38,490 -43% |
| Indianapolis-Carmel-Greenwood, IN | 380 | $61,990 -9% |
| Minneapolis-St. Paul-Bloomington, MN-WI | 350 | $61,100 -10% |
| Baton Rouge, LA | 330 | $80,670 +19% |
| Seattle-Tacoma-Bellevue, WA | 240 | $107,220 +58% |
| San Jose-Sunnyvale-Santa Clara, CA | 150 | $101,840 +50% |
| San Francisco-Oakland-Fremont, CA | 240 | $99,660 +47% |
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 51. 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.