BETA
Updated: Feb 6
BETA
Updated: Feb 6
Evolving
Last Update: 11/21/2025
Your role’s AI Resilience Score is
46.4%
Median Score
Changing Fast
Evolving
Stable
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
Sound Engineering Technicians
They make sure music and sound are clear and balanced at events or in recordings by setting up and adjusting audio equipment.
Summary
The career of a sound engineering technician is labeled as "Evolving" because AI is increasingly being used to handle routine tasks like audio editing and mixing. While AI tools can speed up technical chores, the creative aspects, such as making sound decisions and setting up equipment, still depend on human skills.
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View analysisChat with CoachLatest newsMore career infoSummary
The career of a sound engineering technician is labeled as "Evolving" because AI is increasingly being used to handle routine tasks like audio editing and mixing. While AI tools can speed up technical chores, the creative aspects, such as making sound decisions and setting up equipment, still depend on human skills.
Read full analysisContributing Sources
AI Resilience
All scores are converted into percentiles showing where this career ranks among U.S. careers. For models that measure impact or risk, we flip the percentile (subtract it from 100) to derive resilience.
CareerVillage.org's AI Resilience Analysis
AI Task Resilience
Evolving47.5%
47.5%
Microsoft's Working with AI
AI Applicability
Stable75.2%
75.2%
Anthropic's Economic Index
AI Resilience
Stable73.6%
73.6%
Will Robots Take My Job
Automation Resilience
Evolving42.7%
42.7%
Low Demand
Labor Market Outlook
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
-1.7%
Growth Percentile:
19.2%
Annual Openings:
1.2
Annual Openings Pct:
14.1%
Analysis of Current AI Resilience
Sound Engineering Tech
Updated Quarterly • Last Update: 11/21/2025
State of Automation & Augmentation
Sound engineering technicians do a mix of technical and creative tasks. They “confer with producers” about the right sound, set up and test microphones and mixers, record audio, log recordings, convert files to digital formats, tear down gear after an event, and mix tracks [1] [1]. Some parts of this work are already handled by software.
For example, converting analog recordings to digital is routine, and digital audio workstations automatically time-stamp takes or save project logs. AI and modern software can now even separate voices from instruments in a mix. Apple’s Logic Pro added a “Stem Splitter” that uses machine learning to isolate vocals and instruments in a song [2].
Tech news also notes new AI-powered music tools that auto-create and mix tracks from simple prompts [3]. These tools can handle much of the “mixing or mastering” grunt work and remove background noise [4].
However, many tasks are still very hands-on. Physically setting up equipment, placing mics, and taking down cables are done by people. Hi-fi sound quality also depends on human listening and creative choices.
Even when AI suggests edits, experienced engineers usually tweak the result. In practice, AI today acts as a helper: it can speed up technical chores or suggest levels, but skilled humans make the final sound decisions [3] [4]. In short, computers handle routine audio edits and signal separation, but the creative, coordination-heavy parts of the job remain human.
Sources
AI Adoption
AI tools for audio are becoming more available, but adoption depends on cost, trust, and the value of human skill. Some consumer devices already use AI (for example, modern phones use smart noise cancellation and real-time voice translation [4]), and major audio software companies are adding AI features. This shows industry interest.
But studios and venues will balance these tools against hiring engineers. Audio gear and pro software is an investment, and many employers may prefer experienced technicians who need little setup time. Reviews of new AI tools find that they often “need human refinement” to sound natural [3], especially for complex music.
Engineers worry about copyright and creativity too – tech articles mention “legal controversies” and quality concerns about AI-generated music [3].
On the positive side, AI can boost productivity. It can automate tedious editing steps so engineers can focus on creative work. Efficiency gains (like fast audio cleanup and auto-mixing) may encourage gradual adoption [4] [3].
But social and artistic factors will slow a full takeover. Audiences and artists still value the ear and judgment of a real engineer. In summary, growth of AI in sound engineering will likely be steady but not overnight.
As technology improves, technicians who learn to use AI tools will have an edge, while the uniquely human skills of listening, problem-solving, and collaboration remain essential [3] [4].
Sources
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More Career Info
Career: Sound Engineering Technicians
Parent Careers
Employment & Wage Data
Median Wage
$66,430
Jobs (2024)
16,900
Growth (2024-34)
-1.7%
Annual Openings
1,200
Education
Postsecondary nondegree award
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Confer with producers, performers, and others to determine and achieve the desired sound for a production, such as a musical recording or a film.
2
Report equipment problems and ensure that required repairs are made.
3
Tear down equipment after event completion.
4
Set up, test, and adjust recording equipment for recording sessions and live performances.
5
Regulate volume level and sound quality during recording sessions, using control consoles.
6
Prepare for recording sessions by performing activities such as selecting and setting up microphones.
7
Mix and edit voices, music, and taped sound effects for live performances and for prerecorded events, using sound mixing boards.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
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