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AI Automation Index
Will AI Replace Sound Engineering Technicians?
Task-level automation exposure for Sound Engineering Technicians: 14 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
39%
weighted task index
14 of 14 tasks scored
Median Salary
$73,130 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
13,080 people hold this job — size, not growth
Projected 2025–35
-3.1%
employment change
1,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 36 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$35,180 – $115,190
Highest medians
New Jersey $115,190
District of Columbia $106,630
New York $87,510
Nevada $84,570
Maryland $79,990
Lowest medians
Puerto Rico $35,180
Utah $36,400
South Carolina $45,240
New Mexico $45,690
Wisconsin $46,780
State figures come from the 27-4014 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 39%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 45%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 33%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 7%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 13/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
14 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 20%
3 tasks
Medium exposure (≥ 35%) 42%
6 tasks
Low exposure (below 35%) 38%
5 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#7720 · Core · 55% automatable
Confer with producers, performers, and others to determine and achieve the desired sound for a production, such as a musical recording or a film.
interpersonal — Technical detail negotiation is interactive human work
Collaborate with others to determine technical details of productions.
#7722 · Core · 20% automatable
Regulate volume level and sound quality during recording sessions, using control consoles.
physical manipulation — Console operation requires live physical adjustment
Operate control consoles for sound, lighting or video.
#7727 · Core · 20% automatable
Record speech, music, and other sounds on recording media, using recording equipment.
physical manipulation — Recording equipment physically set up and operated
Operate audio recording equipment.
#7729 · Core · 35% automatable
Separate instruments, vocals, and other sounds, and combine sounds during the mixing or postproduction stage.
visual inspection — Sound mixing needs trained ear and real-time judgment
Mix sound inputs.
#18662 · Core · 20% automatable
Set up, test, and adjust recording equipment for recording sessions and live performances.
physical manipulation — Recording equipment physically set up and operated
Operate audio recording equipment.
#7724 · Core · 65% automatable
Report equipment problems and ensure that required repairs are made.
text generation — Equipment problem notification is routine messaging
Notify others of equipment problems.
#7723 · Core · 35% automatable
Prepare for recording sessions by performing such activities as selecting and setting up microphones.
decision support — Prop selection depends on creative and physical context
Select materials or props. Operate audio recording equipment.
#7725 · Core · 35% automatable
Mix and edit voices, music, and taped sound effects for live performances and for prerecorded events, using sound mixing boards.
visual inspection — Sound mixing needs trained ear and real-time judgment
Mix sound inputs.
#7730 · Core · 82% automatable
Keep logs of recordings.
data analysis — Maintain production activity logs from inputs
Maintain logs of production activities.
#18660 · Core · 6% automatable
Tear down equipment after event completion.
physical manipulation — Dismantling structures is heavy physical labor
Dismantle equipment or temporary structures.
#7726 · Core · 20% automatable
Synchronize and equalize prerecorded dialogue, music, and sound effects with visual action of motion pictures or television productions, using control consoles.
physical manipulation — Console operation requires live physical adjustment
Operate control consoles for sound, lighting or video.
#7728 · Core · 35% automatable
Reproduce and duplicate sound recordings from original recording media, using sound editing and duplication equipment.
visual inspection — Sound mixing needs trained ear and real-time judgment
Mix sound inputs.
#18661 · Core · 90% automatable
Convert video and audio recordings into digital formats for editing or archiving.
data analysis — Format conversion fully automatable
Convert data among multiple digital or analog formats.
#7731 · Supplemental · 35% automatable
Create musical instrument digital interface programs for music projects, commercials, or film postproduction.
visual inspection — Sound mixing needs trained ear and real-time judgment
Mix sound inputs.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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