Скачать или смотреть AI & SUNO in the Studio: What Working Producers Actually Think (Not Fans)

Yesterday I shared the broader public sentiment on AI music.
Today is the counter-report: working music creators—the people inside the studio—speaking for themselves.
Sonarworks partnered with the legendary Sound On Sound to survey 1,194 producers, engineers, songwriters, mixers, and composers about AI in music production. And their verdict isn’t a war cry… it’s a measured, cautious evaluation.
Here’s what stands out:
• 77% fear loss of originality
• 58% already use AI for audio restoration / cleanup
• Only ~8.8% want fully automated AI music
• Producers want AI to help with the grind… not make the creative decisions
• Ethics and training data provenance matter more than hype
I also connect this to my AI music levels (my taxonomy) and explain where producers are drawing the line between “assist” and “authorship.”
Drop your take below:
Where do YOU draw the boundary—cleanup, instruments, vocals, songwriting, full generation?
________________________________________
TIMESTAMPS / TABLE OF CONTENTS (based on your flow)
0:00 – Yesterday’s public report vs today’s producer counter-report
0:14 – Sonarworks x Sound On Sound survey setup (why this matters)
1:26 – Headline findings: originality fears, adoption, and “no full automation”
2:00 – Who was surveyed: working producers, engineers, writers, mixers
3:22 – Why this survey carries different weight than consumer polls
4:05 – How producers actually use AI (testing, not trusting)
4:40 – Adoption breakdown: restoration, mixing, mastering, composition
5:06 – The line producers draw: assistance vs authorship
6:51 – Biggest concern: loss of originality (not job loss)
8:04 – My “human out of the loop” warning + what audiences reject
10:19 – Ethics as a deal-breaker: provenance and rights
11:23 – Disclosure… but with nuance (context-sensitive transparency)
13:16 – Skills shifting: what becomes less valuable vs more valuable
16:45 – The future producer = creative director (not button pusher)
17:10 – Future vision: tool vs automation vs full takeover
19:12 – Genre sensitivity: electronic vs folk/jazz/live ensembles
20:24 – The key takeaway: AI can help… but shouldn’t decide what matters
22:14 – Why “inside the studio” perspective changes the debate
23:04 – Herbie Hancock’s balanced view (humanity + ethics)
27:06 – Practical takeaway: learn AI, demand ethics, keep humans steering
28:09 – My AI music levels taxonomy (0–8) explained quickly
31:00 – Wrap-up + link to the survey + your tools/resources

Support the channel + check out Suno: 👉 https://suno.phillc.net
👉 SUNO Production Book: https://www.amazon.com/SUNO%20AI%20MU...
👉 To learn music theory, and get FREE prompt tools, visit http://phillc.net
👉 Support your buddy Phill with a ko-fi: https://ko-fi.com/s/a7ebeb0d04

#ytsunopartner
To learn music theory, visit http://phillc.net