In an earlier article, I posed nine questions to music industry leadership about AI and music. The second question was: What does "musicianship" mean?
Have I just wasted two hours trying to track down and eliminate a "ground loop" in my home music studio?
That, and many similar, painfully familiar "administrative" problems musicians face every day, can easily be dismissed as time wasted. But is it?
After the technical issue was solved, I found that a musical theme I had been struggling with was also solved. In that time that my conscious mind had shifted into "fix it" mode, my creative subconscious had been free to wander and do its own work.
Would that have happened if the "friction" caused by the technology had been removed? Would I have resolved that creative theme if I hadn't been afforded that space?
Many AI tools offer the allure of removing friction from the creative process and getting to the output as efficiently as possible. But music-making is so much more than output. It is an identity-forming process through which people discover taste, technique, limits, community, and voice.
This matters to artists because AI music tools are often marketed and measured by speed, abundance, or reduction of effort. Those metrics are useful for some tasks, but they can miss something fundamental about what musicians value, and why they pursue music.
The purpose of a creative tool is not always to remove work; sometimes the work is the medium through which a person becomes an artist and a musician.
It may be useful therefore to distinguish different types of friction, in order to understand the roles they play in the creative process.
Administrative Friction
Administrative friction in musicianship arises from repetitive, time-consuming, or "non-creative" technical tasks.
A musician may decide that removing this administrative friction helps them stay focused on what matters at the moment. In those cases, any tool, including an AI-assisted one, that reduces this friction is helpful.
However, not every interruption functions in the same way. If that friction allows or requires the artist to switch gears, approach a problem differently, or rethink the outcome, then it may be better understood as a form of unconscious creative friction, which is explored below.
The important point is not that musicians should preserve every inconvenience; rather, it is that the choice about which friction to remove, and when, should remain with the musician.
Creative Friction
Creative friction includes doubting, choosing, failing, revising, arranging, performing, listening, and gradually learning how to recognize when something—a sound, a melody, a lyric, an effect—actually matters.
These are inefficient processes almost by definition. They are also central to developing an artist's style and persona.
Removing too much creative friction risks flattening the very process that gives music its human specificity. A system that gets a musician to the plausible, easy answer might bypass the decisions through which an artist could discover a better or more personal result.
Workflow Friction
Workflow friction arises from the systems surrounding the creative process.
It can include licensing problems; broken, missing, or inaccurate metadata; rendering delays and fails; file-format problems; import and export issues; platform takedowns; and incompatibilities between tools.
In an ideal world, all parts of this ecosystem would work seamlessly together. In the real world, competition, legacy systems, and innovation mean that different tools continue to operate in different ways and cannot simply be harmonized.
The goal should not necessarily be harmonization but interoperability—making it easier for all digital artifacts (audio, MIDI, automation, DAW and plug-in settings, metadata and other files, rights and credits information, etc.) to move between and across systems without loss or difficulty and be subsequently usable throughout the value network.
This is an area where AI may have a particularly useful role. Reducing workflow friction does not necessarily reduce creative agency; done well, it can give musicians more time and space to exercise it.
Collaborative Friction
Collaborative friction occurs when musicians create together. It is an inevitable part of the creative process. But there are technical issues—including latency, clock-sync errors, sample rates, and drop-outs—that can all interrupt collaboration.
The laws of physics limit the possibilities of real-time collaboration at a distance, but improvements in network infrastructure, 6G technologies, and AI-enhanced network optimization can help reduce this friction and open significant possibilities for remote collaboration. Extremely low latency and reduced 'lag' could allow a musician in one place to more naturally rehearse, improvise, or create with musicians elsewhere, without technology barriers that have made real-time collaboration so frustrating.
Removing this friction can expand rather than diminish human creativity.
Where should the human remain in the process?
These distinctions help reconcile two positions that are often treated as opposites.
Musicians can oppose unlicensed training, unauthorized voice cloning, or output markets that devalue creative labor while still welcoming tools that help them make more expressive or adventurous work. Conversely, tools—in particular, overused AI tools—can be technically impressive and still be creatively alienating if they reduce a musician, at best, to a project manager or, at worst, to a supervisor of plausible mediocrity.
The question is not simply whether AI participates in the studio. The more useful question is whether the musician can perform through it, retaining the center of creative gravity with the human creator rather than drifting toward the AI tool.
This matters artistically, but it also matters legally. Recognition of human creativity remains central to copyright policy. The U.S. Copyright Office has concluded that using AI to assist in the creative process does not by itself undermine copyright protection, while prompt-only or purely AI-generated material may not qualify for protection.[1]
For product designers, this suggests a practical design principle: expose the points of human choice. Tools should make selection, arrangement, editing, performance, and modification visible rather than collapsing the entire process behind a single "generate" button. They can help preserve a record of where creative decisions occurred and who made them.
Creative Agency as a Design Principle
The human agency argument is also an economic and cultural discussion.
Creator groups have consistently emphasized consent, control, attribution, and fair compensation in debates over technology. For example, the Human Artistry Campaign recognizes the potential for AI and technology to support human creativity, but views them as unacceptable when they create shortcuts around copyright, publicity, or compensation.[2] Research by GEMA and SACEM has similarly documented significant music creator demand for transparency in AI training data, consent, and participation in AI revenues.[3]
These positions are not anti-innovation; they are pro-agency within innovation.
For the Music Technology Coalition, this suggests that AI evaluation should include a creative-agency test.
Does a tool increase a musician's control over their creative process, or does it primarily increase output volume? Does it remove friction that prevents participation, or friction that helps produce judgement, skill, message, and voice? Does the tool in use leave meaningful decisions with the musician?
The future of musicianship will almost certainly include AI at many points in the creative workflow. That need not diminish human creativity.
The most valuable tools may be those that know the difference between the difficulty that creates and supports a unique voice and the friction that blocks creativity.
Trustworthy AI music design begins with simple respect: the process matters.
[1] U.S. Copyright Office Copyright and Artificial Intelligence, Part 2: Copyrightability
[2] Human Artistry Campaign (2023), Core principles for AI applications in support of human creativity and accomplishment.
[3] GEMA, SACEM, and Goldmedia (2024), AI and music: Generative artificial intelligence in the music sector.