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Sound Engineering Technicians

Arts, Design, Entertainment & Mediamediumaugment
BLS 2024-34: +5%
Median Wage: $59,040
Employment: 18K

Overall Exposure

47+12

2025 vs 2023

Theoretical Exposure

63

What AI could do

Observed Exposure

28

What AI actually does

Automation Risk Score

36

Displacement risk

3-Year Outlook (2025 โ†’ 2028)

Projected changes in AI automation metrics over the next 3 years based on estimated data.

Overall Exposure

47โ†’60
+13

2025 โ†’ 2028 (estimated)

Theoretical Exposure

63โ†’77
+14

2025 โ†’ 2028 (estimated)

Observed Exposure

28โ†’38
+10

2025 โ†’ 2028 (estimated)

Automation Risk

36โ†’47
+11

2025 โ†’ 2028 (estimated)

Exposure Metrics (2023 - 2028)

Detailed Metrics Table

YearOverallTheoreticalObservedRiskData Type
202335501826actual
202441572331actual
202547632836actual
202652683240estimated
202756733544estimated
202860773847estimated

Task Breakdown

Mix and balance audio levels across multiple tracks
52%ฮฒ 0.5
Remove noise and apply audio restoration processing
68%ฮฒ 1
Set up and calibrate recording equipment and microphones
25%ฮฒ 0
Master final audio mixes for distribution formats
45%ฮฒ 0.5

About This Occupation

If you work as a Sound Engineering Technician, AI is increasingly influencing your field. With an automation risk of 40/100 and overall exposure at 52%, this role faces medium transformation. The most automatable task is noise removal and audio restoration at 68%. Classified as an 'augment' role, AI excels at repetitive audio cleanup but live sound engineering and artistic mixing decisions require human expertise. BLS projects +5% growth through 2034, sustained by expanding podcast, streaming, and live event industries. Technicians who integrate AI-powered plugins and DAW features will enhance their productivity.

Frequently Asked Questions

With an automation risk score of 36%, Sound Engineering Technicians faces a moderate level of AI-driven change. Some tasks can be automated, but many require human judgment, creativity, or interpersonal skills that AI cannot yet replicate. The role is more likely to evolve alongside AI than be replaced.

The AI automation risk score for Sound Engineering Technicians is 36% (2025 data). Overall AI exposure is 47%, with 63% theoretical exposure and 28% observed exposure. The risk trend from 2023 to 2025 is +10 points.

The tasks with the highest automation potential for Sound Engineering Technicians are: Remove noise and apply audio restoration processing (68%), Mix and balance audio levels across multiple tracks (52%), Master final audio mixes for distribution formats (45%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.

The BLS projects +5% employment change for Sound Engineering Technicians from 2024 to 2034. Combined with an overall AI exposure of 47%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.

Since AI primarily augments capabilities in this role, professionals in Sound Engineering Technicians should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.

Recent AI Impact Changes

Mar 2026: Published evergreen blog post analyzing AI impact on sound engineers: 52% exposure, 40% automation risk, noise removal 68% automated, +5% BLS growth.

[Source: AI Changing Work Blog]