Insurance Appraisers, Auto Damage

Score — 37/100 resistance

Holding it up: embodiment (10/20). Weakest point: task resistance (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 5 + 10 + 8 + 6 + 8 = 37. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

This occupation has already been through one. Headcount fell 28.4% between 2017 and 2025 — 16,150 to 11,560 — while the median wage held roughly flat in real terms ( -3.4% after inflation). A job being commoditised usually loses pay along with headcount. One that shrinks by half while pay holds is leaving a specialist core behind, and the score above was assigned from the occupation title without sight of that history — so it may be describing the job this used to be rather than the people still doing it. Why this is a known limit.

Confidence: high · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

Active moats on the surviving side: embodiment, licensure

How to future-proof this job

• Specialize in reinspection and disputed-estimate resolution — the tier carriers escalate to when AI photo estimates get challenged by shops or attorneys.
• Get licensed in states that mandate a licensed appraiser signature or physical inspection above a dollar threshold, and hold that as your billing basis.
• Move into heavy commercial, fleet, RV, motorcycle, and EV battery-pack damage, where parts data is thin and teardown judgment still drives the number.
• Build the fraud/prior-damage niche: SIU referral work, staged-loss recognition, and testimony-ready inspection documentation.

Where to go deeper on what this job runs on: Purdue OWL — the standard reference for professional writing free · Toastmasters — public speaking practice at local clubs worldwide low · Khan Academy — reading and vocabulary, all levels, free free · Coursera — active listening and communication skills free to audit · Coursera — critical thinking and logic, audit free free to audit · Coursera — work planning and personal productivity free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — nothing clears the bar

No occupation passed every test: close enough to insurance appraisers, auto damage 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.

Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:

Bill and Account Collectors COOKED 20/100 (-17) · 59% overlap
Word Processors and Typists COOKED 8/100 (-29) · 57% overlap
Correspondence Clerks COOKED 13/100 (-24) · 56% overlap

That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.

What would move this occupation up is the other direction, and on this page it's the more useful one.

Where this work is, and what it pays there

BLS metro figures for 35 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Percentages are against this occupation's national median of $78,240. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 37. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.