Is AI replacing musicians? What the tools actually do in the studio

Is AI replacing musicians? No. On every piece of evidence we could find, AI in music is working as an assistant, not a replacement. Most producers who use it use it to split stems and master tracks; almost none use it to make whole songs; and the first AI-assisted track nominated for a Grammy, which went on to win, used it to pull John Lennon's voice off an old home demo so the band could finish a song. What AI is doing is flooding streaming services with generated tracks, and that is a fight about money, not about who makes music. Both things are true, and a beginner deciding whether to learn production should know the difference.

What musicians actually use AI for

The headline fear is a machine writing songs while musicians watch. The surveys of people who make music for a living describe something much more ordinary.

Tracklib, 2024. The sample-licensing platform surveyed 1,107 self-identified producers. A quarter (25%) said they used AI in making music. Of those, 73.9% used it for stem separation, 45.5% for mastering and EQ plug-ins, 21.2% to generate elements for songs, and just 3% to create entire songs (Music Business Worldwide). Among the non-users, 82.2% gave artistic and creative reasons.

Tracklib, 2025. A larger follow-up with 1,734 producers found 32% use AI tools, "only 6% using generative tools regularly", and use concentrated on "assistive use cases such as stem separation, EQ and mastering". And 82% said they were against full song generation from text prompts (MusicTech).

Ditto Music, 2025. The distributor found 48% of artists have used AI somewhere in their music-making, down from 59.5% in 2023, for songwriting, artwork, mastering and general production. The biggest concern, cited by 42%, was a lack of personal creativity (Ditto Music).

Put those together and a clear picture forms. Working musicians are adopting AI where it removes drudgery (pulling a vocal out of a mix, getting a master to a sensible loudness) and refusing it where it would remove them. That is how assistants get used.

The Grammy-winning AI record

The best single case study is "Now and Then", the last Beatles song. John Lennon's home demo had his voice and piano tangled together on one tape. Peter Jackson's WingNut Films had built a machine-learning tool called MAL for the Get Back documentary, and used it to separate Lennon's vocal from the piano, which made it possible to finish the song (Wikipedia). Paul McCartney was blunt about what that meant: "nothing has been artificially or synthetically created. It's all real and we all play on it" (MusicTech).

The song won the 2025 Grammy for Best Rock Performance (Recording Academy). An AI tool did one technical job, separating a voice from a piano, and the result was more human, not less: Lennon's own voice, freed from a muddy recording, with his bandmates playing around it.

What the tools are designed to do

You can also read intent straight from how the software makers describe their own products.

• Apple calls Logic Pro's Session Players "AI-powered musicians" that play drum, bass, keyboard and synth parts that fit your song (Apple). A session player is someone you direct, not someone who takes your seat.
• Ableton added stem separation to Live Suite in Live 12.3 that "runs locally", splitting audio into four stems (Ableton release notes).
• Image-Line pitches FL Studio 2026's Gopher assistant as "just help when you need it", with "no data collection of your work, no training models" (Image-Line).
• AI DAWs go furthest, and still keep the musician in charge. Veena's CoProducer, for example, offers "3 options" for every new part and writes nothing that depends on it "until you pick one"; every change it makes is one undo (Veena). The design assumes a human choosing.

The jobs data

The US Bureau of Labor Statistics counts about 170,400 musician and singer jobs in 2025 and projects employment will "show little or no change from 2025 to 2035", with about 17,400 openings a year (BLS). That projection runs deep into the generative-AI era and shows no collapse. It is US-only and it is a forecast, but it is the most careful public number there is.

The honest worry: generated tracks and income

None of this means AI is harmless to musicians. Deezer said in July 2026 that more than half of its daily uploads are AI-generated tracks, peaking at a monthly average of 90,000 a day in June 2026 (TechCrunch). A study by PMP Strategy for CISAC, the global body of authors' societies, puts 24% of music creators' revenues at risk by 2028 (CISAC). CISAC is an interested party and that is a projection, but the mechanism is real: generated filler competes for the same playlist slots and library placements that pay working musicians.

Notice what that threat is. It comes from song generators producing finished tracks at scale, not from musicians using AI inside their own sessions. A producer who uses AI to split stems is not the problem; a content farm uploading thousands of untouched renders a day is. We argue the money side in full in our column Will AI replace music producers?

What we think

AI is not replacing musicians, and the people closest to the work are telling us so with their behaviour: they use it for the chores and keep the creative decisions. The tools that will matter most for musicians are the ones built on that same split. An AI that hands you finished songs competes with you. An AI that hands you editable parts inside a DAW works for you.

That is why we think the AI DAW is the right shape for this technology, and why we would tell a beginner to learn production now rather than wait. The skills that matter (taste, choosing, editing, knowing when a part is right) are exactly the ones the AI leaves to you, and an AI collaborator gets you to the point of using them faster. What would change our mind: evidence that working producers were moving to whole-song generation in large numbers. Every survey so far points the other way.

Next in the series: traditional DAW vs AI DAW. Previous: what is an AI DAW. Back to the hub: what is a DAW.

FAQ

Will AI replace music producers? Not on current evidence. Producers who use AI mostly use it for stem separation and mastering, and only 6% use generative tools regularly, per Tracklib's 2025 study.

Are most musicians using AI? About half have used it somewhere: 48% in Ditto's 2025 survey. About a third of producers (32%) use AI tools, per Tracklib.

Is using AI in a song "fake"? It depends what the AI did. Cleaning up a recording, as on "Now and Then", or splitting stems is a production tool. We look at the harder cases in is using AI to make music cheating?