COOKED
Editing is entirely screen-based, and the volume tiers of the work — logging footage, syncing audio, transcript-driven rough cuts, captioning, reframing for vertical, basic color and audio cleanup, cutting 40 social variants from one master — are already handled well by Premiere/Resolve AI features and text-based editors. What survives is narrative judgment: pacing a scene so it lands emotionally, structuring a documentary from 200 hours of unscripted material, and sitting in a room with a director or client absorbing vague notes and turning them into a cut. The modal editor today does more corporate, social, and promo work than feature narrative, and that modal work is exactly the part collapsing in price.
Nearly all of this fall was the 2020 shock. It has been climbing back since.
Median pay $63,780 → $75,420 -5.4% 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
+4%
Percentage only. The projection counts a different population from the 25,610 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +4% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~3,600 openings a year on average, including replacing people who leave.
EditorFilmmakerFilm EditorNews EditorTape EditorCue SelectorMovie EditorVideo EditorOnline EditorContent CreatorVideotape EditorNews Video EditorNon-Linear EditorDigital Video EditorContract Video EditorMultimedia SpecialistNews Videotape EditorVideo Content CreatorVideo Tape DuplicatorVideo Tape TransferrerVideo Production EditorDigital Media CoordinatorTelevision News Video EditorOptical Effects Layout Person
Holding it up: judgment & accountability . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier A 9 sits mid-band because the assembly layer — ingest, multicam sync, transcript-based stringouts, subtitle burn-in, 9:16 reframes, loudness normalization to -14 LUFS — is now a menu command, while structuring a 45-minute unscripted episode from mismatched interview coverage and finding the one reaction shot that makes a beat work still requires someone watching every frame and deciding what it means.
Fully desk- and screen-based A 4, not 0, only because you still physically handle drives, LTO pulls, and reference monitors in a calibrated suite and occasionally sit on set for on-location assembly — but nothing in the job requires leaving a desk with a keyboard, tablet, and two displays.
No licence, no signature requirement There is no licence, no board, and no exam for editing; the E&O policy and the delivery contract sit with the producer or post house, so a botched cut costs you the next gig, not your right to practice.
Meaningful discretion A 10 covers the real discretion in pacing, structure, and what a documentary subject's on-camera contradiction is allowed to imply — but the director, showrunner, or client approves the cut before it ships, so the ambiguous high-stakes call is theirs to sign off on.
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 (9/20 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 (8/20) is whether buyers specifically pay for a person. Judgment and accountability (10/20) 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 19 of this occupation's 32 points (59%).
Embodiment (4/20) 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 film and video editors 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:
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.
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 42/100 — EXPOSED.
Task-mix shift is genuine here: if the assembly/variant/caption tier is fully absorbed by text-based editing and Resolve/Premiere AI, the remaining paid work is long-form structure from unscripted material — documentary and reality story editing, where the job is finding a narrative in 200 hours with no script. Watch whether documentary/story-editor postings hold while assistant editor and social-variant postings vanish; the surviving role scores higher because the routine tier is gone from it.
Credit and provenance rules that make a named human editor a marketable fact: Motion Picture Editors Guild (IATSE Local 700) pushing AI terms into the 2026 basic agreement round, plus festival/awards eligibility rules (e.g. Academy or Sundance requiring disclosure of generative tools in editorial) so a 'cut by a human editor' credit becomes something buyers of prestige work specifically contract for.
If the editor becomes the accountable verifier of what a generative pipeline produced — signing that no footage was synthetically altered, that consent/release terms were honored, that a documentary subject was not misrepresented by a reframe or splice — the role owns a consequential call. Broadcaster standards departments (BBC editorial guidelines, network S&P) already require a named person to attest to unmanipulated footage in factual programming; extending that attestation formally to editorial AI output would raise this.
The limit. Even with every lever, this occupation is capped well below safe: the ceiling is a much smaller field of long-form story editors on prestige and factual work. Corporate, promo and social editing — the majority of the 25,610 — has no lever at all, because the buyer never wanted a human, only a cut.
| Los Angeles-Long Beach-Anaheim, CA | 6,010 | $83,210 +10% |
| New York-Newark-Jersey City, NY-NJ | 3,430 | $104,590 +39% |
| San Francisco-Oakland-Fremont, CA | 740 | $109,930 +46% |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 560 | $91,750 +22% |
| Boston-Cambridge-Newton, MA-NH | 430 | $88,910 +18% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 410 | — |
| Orlando-Kissimmee-Sanford, FL | 390 | $60,470 -20% |
| Miami-Fort Lauderdale-West Palm Beach, FL | 360 | $61,950 -18% |
| San Francisco-Oakland-Fremont, CA | 740 | $109,930 +46% |
| New York-Newark-Jersey City, NY-NJ | 3,430 | $104,590 +39% |
| Denver-Aurora-Centennial, CO | 250 | $93,600 +24% |
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 32. 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.