AI exposure: Sound Engineering Technicians
Assemble and operate equipment to record, synchronize, mix, edit, or reproduce sound, including music, voices, or sound effects, for theater, video, film, television, podcasts, sporting events, and other productions.
Reading this score
computed34.3% of this occupation's weighted task load is exposed, which puts Sound Engineering Technicians at the 59th percentile of 923 occupations. The capability is largely there. Its average task scores 2.1 out of 4 on what a current system can produce, and the frictions that hold other jobs in place are comparatively weak here.
What holds the line here is embodiment. Across this occupation's 14 tasks it averages 1.64 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Convert video and audio recordings into digital formats for editing or archiving, at 86.7%. The least is Tear down equipment after event completion, at 0.0%. A gap of 86.7% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within arts, design, entertainment, sports and media occupations, this one is less exposed than the median of 38.5% across the group's 40 roles, with 26 scoring higher. Being in an exposed family does not make a particular job exposed, and the reverse holds too.
What would move this score. Of 14 tasks, 10 are currently banded exposed, 0 assisted and 4 untouched. For that distribution to shift materially would take systems being given deeper access to the organisation's own records and history, which is already happening. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Task by task
14 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Convert video and audio recordings into digital formats for editing or archiving. | 86.7% | 13.3% | 0.0% | 3.62 | exposed |
| Keep logs of recordings. | 73.3% | 26.7% | 0.0% | 4.20 | exposed |
| Confer with producers, performers, and others to determine and achieve the desired sound for a production, such as a musical recording or a film. | 45.0% | 30.0% | 25.0% | 4.83 | exposed |
| Report equipment problems and ensure that required repairs are made. | 45.0% | 30.0% | 25.0% | 4.50 | exposed |
| Separate instruments, vocals, and other sounds, and combine sounds during the mixing or postproduction stage. | 33.3% | 16.7% | 50.0% | 4.60 | exposed |
| Mix and edit voices, music, and taped sound effects for live performances and for prerecorded events, using sound mixing boards. | 33.3% | 16.7% | 50.0% | 4.43 | exposed |
| Reproduce and duplicate sound recordings from original recording media, using sound editing and duplication equipment. | 33.3% | 16.7% | 50.0% | 3.80 | exposed |
| Create musical instrument digital interface programs for music projects, commercials, or film postproduction. | 33.3% | 16.7% | 50.0% | 3.07 | exposed |
| Regulate volume level and sound quality during recording sessions, using control consoles. | 26.7% | 23.3% | 50.0% | 4.80 | exposed |
| Synchronize and equalize prerecorded dialogue, music, and sound effects with visual action of motion pictures or television productions, using control consoles. | 26.7% | 23.3% | 50.0% | 3.88 | exposed |
| Prepare for recording sessions by performing such activities as selecting and setting up microphones. | 23.8% | 13.8% | 62.5% | 4.48 | untouched |
| Record speech, music, and other sounds on recording media, using recording equipment. | 15.0% | 10.0% | 75.0% | 4.60 | untouched |
| Set up, test, and adjust recording equipment for recording sessions and live performances. | 15.0% | 10.0% | 75.0% | 4.56 | untouched |
| Tear down equipment after event completion. | 0.0% | 0.0% | 100.0% | 3.90 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 2.11 | 0-4 |
| Embodiment | 1.64 | 0-3 |
| Presence | 1.00 | 0-3 |
| Accountability | 0.07 | 0-3 |
| Context | 1.61 | 0-3 |
| Verification cost | 1.00 | 0-3 |
What this means in practice
Where most of a role's weighted task load is exposed, the work that survives is usually the part of the job nobody wrote into the job description: deciding what should be produced rather than producing it, and being answerable for the result. The tasks lowest on this page are a better guide to where to spend your time than any general advice about the future of work.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.