← Risk register SOC 27-4014 · reviewed 2026-08-11

Sound Engineering Technicians

13,080 US workers · median $73,130/yr · Media

EXPOSED

The post-production half of this job — noise reduction, de-essing, dialogue cleanup, level matching, mastering, stem separation, podcast editing — is where AI tools already deliver commercially acceptable results at a fraction of the hours. What survives is physical: rigging and cabling a room, placing mics on a drum kit or a lectern, ringing out a PA in a bad-sounding venue, and riding a live mix in real time while a band changes the set list. The modal worker splits time between a studio/edit bay and load-ins, so exposure is real but not total.

10-year outlook: Studio and post-production headcount keeps shrinking as editing tools absorb the grunt work, while live sound, system tech, and installed-AV roles hold up and increasingly become where the paychecks are.

US employment, 2019–2025+1.5%
12,89013,080 workers

Roughly flat across the period, with year-to-year wobble.

Median pay $54,740 → $73,130 +6.9% in real terms (nominal +33.6%, less ~25% US inflation over the period)

The job count is not the verdict

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

-1.7%

Percentage only. The projection counts a different population from the 13,080 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Exposed, and shrinking

Both signals point the same way: the tasks are largely automatable and the BLS projects -1.7% 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.

~1,200 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

MixerProducerRecordistSound MixerSound CutterSound EditorSound PrinterAudio EngineerAudio OperatorDisc RecordistFilm RecordistMusic EngineerMusic ProducerSound DesignerSound EngineerMixing EngineerMixing OperatorSound RecordistMusical EngineerDub Room EngineerRerecording MixerMastering EngineerPlay Back OperatorRecording Engineer

Score — 38/100 resistance

Holding it up: embodiment (12/20). Weakest point: liability shield (1/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 8 + 12 + 1 + 8 + 9 = 38. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 8/20

Mixed — a routine tier and a judgment tier An 8 reflects the split: iZotope RX, Auphonic, Adobe Enhance Speech and Dolby's automatic loudness normalisation already handle the dialogue repair, de-noising and LUFS-compliant delivery that used to fill your billable afternoons, but nothing automates coiling a snake, taping a lav under a shirt, or catching a feedback ring at 2.4 kHz before the audience does — hence mixed, not condemned.

Embodiment 12/20

Some physical or field component A 12 comes from load-in and load-out work in venues you don't control — flying line arrays, running XLR under carpet, boom operating on location in wind and traffic noise — but the modal week still ends in a chair at a DAW with a control surface, which is what keeps this out of the 13-plus band where the entire job happens on a truss or in a field.

Liability shield 1/20

No licence, no signature requirement A 1 is accurate because nothing gatekeeps this work: no state licence, no mandatory certification, and Dante Level 3 or Avid Pro Tools certification is a hiring signal a producer may ignore entirely — if a mix is unusable, the client re-books someone else rather than filing against a credential.

Trust premium 8/20

Some relationship component An 8 recognises that repeat clients hire the engineer who already knows their vocalist's sibilance and their room's 80 Hz null, and that FOH engineers tour with specific bands for years — but album credits and session work are still awarded on demo reels and rates, and a broadcast facility will slot any qualified operator into the Tuesday shift.

Judgment & accountability 9/20

Meaningful discretion A 9 fits calls that are real but recoverable: choosing the mic pattern for a noisy interview, deciding how much gain-before-feedback you can steal for a soft speaker, judging when a take is unfixable and must be re-recorded — decisions with schedule and budget consequences, made against loudness specs and delivery standards rather than in a vacuum.

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, physical-presence, trust

How to future-proof this job

Where to go deeper on what this job runs on: Coursera — active listening and communication skills free to audit · Toastmasters — public speaking practice at local clubs worldwide low · Coursera — critical thinking and logic, audit free free to audit · MIT OpenCourseWare — problem-solving and analytical method courses free · Khan Academy — reading and vocabulary, all levels, free free · edX — operations management and process monitoring courses 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 sound engineering 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.

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:

Audio and Video Technicians EXPOSED 48/100 (+10) · 69% overlap
Audiovisual Equipment Installers and Repairers EXPOSED 60/100 (+22) · 66% overlap
Musical Instrument Repairers and Tuners SAFE 67/100 (+29) · 64% 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.

What would move this back up — beyond any one person

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 54/100, still EXPOSED.

5 specific changes that would raise this score
  • already happening task resistance +4

    Task-mix shift: as Izotope/Adobe/Auphonic-class tools absorb the routine cleanup tier (dialogue denoise, leveling, podcast edit, loudness-spec delivery), the residual job is live mixing, mic placement on unusual sources, system tuning in untreated rooms, and creative mix decisions — tiers with no usable AI substitute. This raises the score of what remains even as total hours fall.

  • plausible trust premium +4

    Union and guild credit/labeling rules: IATSE Local 695 and CAS (Cinema Audio Society) contract terms requiring named human mixer credit, plus streamer/broadcaster delivery specs that require a human-signed QC pass on final mixes. A 'human-mixed' disclosure norm in music (following AI-labeling moves at Spotify/Deezer and the Grammys' human-authorship rule) would extend this to records.

  • plausible embodiment +3

    Growth in live/touring and corporate AV work as recorded-audio hours shrink pushes the modal worker toward load-ins, rigging, RF coordination in crowded spectrum, and FOH — plus FCC wireless-mic spectrum churn (post-600MHz repacking) making frequency coordination a recurring on-site human task.

  • plausible liability shield +3

    Life-safety and code hooks on the install/tour side: NFPA 72 mass-notification intelligibility (STI) testing and ADA assistive-listening compliance being signed off by a certified technician (AVIXA CTS-D, or a state low-voltage license), and rigging sign-off requiring an ETCP-certified rigger. This applies only to the systems-integration/touring slice, not studio post.

  • unlikely judgment accountability +2

    Live show sound-pressure-level and hearing-safety limits enforced on the operator — as in municipal noise ordinances and EU-style occupational noise rules — making the mixer the named person accountable for on-the-night SPL calls.

The limit. Ceiling is low. There is no licensure body for audio engineering as such, and the credit/label route protects reputation, not work volume — a named human mixer can still supervise AI-produced stems. The only durable floor is physical: rooms, mics, rigging, and real-time mixes. Post-production hours are unlikely to return.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 43 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.

Most of these jobs

Los Angeles-Long Beach-Anaheim, CA 2,820 $77,850 +6%
New York-Newark-Jersey City, NY-NJ 1,960 $97,510 +33%
San Francisco-Oakland-Fremont, CA 460 $94,990 +30%
Chicago-Naperville-Elgin, IL-IN 450 $73,140 +0%
Minneapolis-St. Paul-Bloomington, MN-WI 380 $83,810 +15%
Nashville-Davidson--Murfreesboro--Franklin, TN 320 $71,180 -3%
Dallas-Fort Worth-Arlington, TX 300 —
Washington-Arlington-Alexandria, DC-VA-MD-WV 240 $79,990 +9%

Best paid

New York-Newark-Jersey City, NY-NJ 1,960 $97,510 +33%
San Francisco-Oakland-Fremont, CA 460 $94,990 +30%
Atlanta-Sandy Springs-Roswell, GA 150 $86,610 +18%

Percentages are against this occupation's national median of $73,130. 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 38. 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.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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Kept current

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