Musicians Are Embracing AI — But Drawing a Hard Line on Creativity: Summary of A Report by Muse Group
- Karan Bhatia
- Apr 20
- 3 min read
Muse Group, creating the world’s most popular music apps and content, has published a survey conducted among 1,200 users across platforms like Ultimate Guitar, MuseScore, Audacity, and MuseHub, revealing a nuanced relationship between creators and AI. While adoption is already widespread, acceptance comes with strict conditions around control, authorship, and transparency. Artificial intelligence has rapidly entered the music creation workflow, but for most musicians, its role is clear: assist, not replace.
Full Report:
AI is Already Part of the Workflow
AI in music is no longer experimental; it’s operational.
Nearly 70% of musicians reported using AI-powered features in the past three months, primarily for technical and supportive tasks. The most common applications include cleaning audio, generating ideas, separating stems, and correcting pitch.
These use cases highlight a clear pattern: musicians are comfortable with AI when it improves efficiency without interfering with creative ownership.
Assist, Don’t Create
The report draws a sharp boundary between assistive and generative AI. Tasks like noise removal, transcription, and practice feedback are widely accepted, with over two-thirds of respondents viewing them positively. However, acceptance declines as AI moves closer to core creative decisions.
While around half of musicians are open to suggestions such as chord progressions or melodies, fewer are comfortable with AI generating lyrics or arranging full compositions. Only about one-third accept AI finishing a song entirely.
The message is consistent: creators are open to collaboration, but not delegation.
Control Is Non-Negotiable
If there is a single theme across the report, it is control.
Over 93% of respondents prefer having more control over AI tools, even if it slows them down. Most users want AI features turned off by default, with systems that ask for permission before making changes or limit themselves to suggestions.
Trust in AI tools is directly tied to transparency and reversibility. Musicians expect clear labeling of AI-generated changes, the ability to undo or compare edits, and well-defined ownership rights over outputs.
Without these safeguards, even high-performing tools risk rejection.
Trust Breaks at Ownership and Consent
The strongest resistance emerges around how AI systems are trained and what they produce.
More than 40% of respondents reject tools that use other creators’ work without permission or mimic recognizable artistic styles without consent. Similarly, unclear copyright ownership or lack of visibility into AI-generated changes are major dealbreakers.
These concerns reflect a deeper issue: AI is not just a tool, but a system embedded in broader questions of rights, attribution, and economic value.
Productivity Gains, Economic Anxiety
Despite these concerns, musicians acknowledge the practical benefits.
Nearly 68% believe AI tools will make them more productive, helping streamline repetitive and technical aspects of music creation. However, this optimism is paired with significant anxiety about long-term impact.
About 63% of respondents believe AI will make it harder for musicians to earn money, and 68% expect some roles in the industry to be replaced.
This duality, personal gain versus industry disruption, defines much of the current sentiment.
A Generational Divide
One of the report’s most surprising findings is the skepticism among younger musicians.
Users aged 18–24 are the least likely to use AI tools and the most likely to express concern or frustration. They also report the lowest levels of excitement about AI in music, suggesting a higher bar for trust or greater sensitivity to its implications.
In contrast, musicians aged 25–54 show the highest adoption and most positive attitudes.
The Future: AI as a Controlled Instrument
Ultimately, musicians do not see AI as a creative partner in the traditional sense. Instead, they view it as a highly capable instrument, one that must remain under human direction.
The ideal AI tool is not autonomous, but responsive. It improves quality, saves time, and supports learning, while keeping the creator firmly in control.
As AI continues to evolve, its success in music may depend less on what it can create and more on how well it respects the boundaries of those who do.
