AI is changing what makes music feel human

AI can make a Taylor Swift song. Or a Fleetwood Mac song. Or a Frank Sinatra song. Now, musicians and listeners alike are starting to think outside of AI's black box. 

More than ever, music is veering into the unexpected, whether it be leaning into sour notes, playing non-traditional melodies against odd time signatures, or creating entirely new genres like Celtic EDM. These new sounds serve as evidence of humanity: Something so strange, interesting, or thoughtful could have only come from the mind of a living, breathing human. 

It's a sign that AI's ability to create polished music isn't just changing the music industry. It's changing the sound of music itself. The result? Imperfections have become a badge of honor. 

"Even coming from a pre-AI era, we can make music perfect," David Das, vice president of the Society of Composers and Lyricists, told The Deep View. "We can beat perfect drums, we can tune vocals, we can make everything sound like it was made by a computer. But AI, in its current incarnation, seems to take [it] even further than that." 

The birth of a new sound

One of the most common complaints about AI-generated music is that it lacks grit. 

It's why Cecil Coleman, a drummer in Australian band Body Type, has seen a pivot toward imperfect playing as fellow musicians get frustrated with how overly-clean AI sounds. There’s a general consensus that AI-generated music tends to sound overproduced and too polished, she said. "A lot of the artists I really love, I've seen them doing more of this earthy, gritty type of vibe to distinguish [themselves]." 

In Das's writing and composing, he is leaning into raw sounds and flaws, recording without click tracks and samples as a form of psychological rebellion against pristine music. "I'm in a phase of my life [where] I just want [music] to feel human again."  

So why does AI-generated music sound so perfect? Robert Rowe, a New York University professor who teaches about music innovation, told The Deep View that while AI outputs often sound "believable," they face core problems due to the way large language models are constructed. They are built to predict the next letters rather than make an entire, cohesive piece.

"It sounds good locally, from phrase to phrase, and then over the course of an entire song, it is kind of laughable. It just doesn't make any sense, or it repeats in weird ways, or sounds too much like something else," said Rowe.

This could be attributed to "autophagy" in machine learning, or when these models are trained on machine-generated data that creates a feedback loop, Carmine-Emanuele Cella, a composer, professor and co-director of UC Berkeley’s Center for New Music and Audio Technologies, told The Deep View. When AI consumes the data that it generates, the models end up creating "all sorts of unique patterns and repetitions and things that you are, in fact, able to recognize in the same way you would recognize a text generated by AI." 

This results in common tells that listeners often point out, he said, such as over-repetition in lyrics, choruses, and harmonic sequences. And according to recording engineer Liam Weiland, AI-generated music has another giveaway: a "high-end hiss." Still, the average listener doesn't tend to notice—or if they do, they might not think about why it’s there. And with AI production constantly improving, Weiland said, these indicators might not be around for long. 

Additionally, AI may have a similar impact on music as photography had on painting. 

While the birth of photography in the 19th century initially made painters fear that their occupation would become obsolete, what resulted were new styles of painting that went beyond the confines of realism, leading to the birth of impressionism and abstract art. Meanwhile, photography itself became an artistic medium. 

AI could create a "new paradigm" for both listeners and musicians, said Das, where both AI-generated music and counter-AI genres gain traction. "I think it'll go in both directions," he said.

Robert Prey, professor of digital culture at Oxford University, told the Deep View that AI could essentially be a forcing function that drives musicians to become more creative. For instance, if AI can create polished, pleasant enough melodies, "then perhaps we don't need musicians to do that. Maybe musicians can move into a more creative realm. They may be enticed to experiment more, rather than write the standard four-chord pop song." 

While some artists are leaning into grit, imperfections, and weirdness as a means of rebelling against the new wave of technology, one genre in particular has taken to it: electronic music. 

• Diplo, for instance, has unabashedly embraced the tech, urging musicians to either adapt to AI or "just give up and become an Uber driver" in a podcast in April, noting that AI can give him "the best voice" and that he doesn't need anyone to sing anymore.

• In an interview with Billboard, Steve Aoki said that he uses AI for lyric generation, and that even though he's a "novice" in the tech, fellow musicians should "ride the wave."   

• As early as 2023, David Guetta said that AI is the future of music after using the tech to create lyrics and rap in the vocal style of Eminem for a song.   

• And DJ and producer Josh Fawaz saw an AI cover of Madonna's "Like a Prayer" amass millions of streams and top the charts, though he has faced intense backlash for openly embracing Suno. 

DJs and electronic music producers tend to embrace this tech more openly due to the nature of the music itself, Seth Forsgren, co-founder and head of product for Google Flow Music, the company's AI music and production tool, told The Deep View. Just as developers were the first frontier for AI adoption in the enterprise due to their technical prowess, electronic music artists tend to be more technically-inclined than others. For instance, Forsgren said that some of the most avid users of Flow Music fall in this genre. 

"These are artists who are deep on their computer and doing amazing, crazy stuff with their tools already," said Forsgren. "So the idea of having a new way to create sounds out of nothing is inherently approachable and exciting to that audience."

But beyond musicians adopting the tech, AI has the capability to shift the boundaries between musician and consumer entirely, said Forsgren. AI could create a world in which a piece of music is a building block for the consumer to reimagine, rather than a "static piece that doesn't change." The key piece, he said, is that the artist has to want their work to be something malleable that listeners can reference and "take actions on top of." 

"I think for the artists who want to, and people who are excited to have their music out in the world and have it be a living being," said Forsgren. "Having fans interact with that, have them engage with it, have them be a part of changing it. It is just like a really novel new thing." 

The way music is taught 

This changing landscape is something that music educators, especially those with a focus in production, are exploring with their students. At NYU, Rowe approaches his class "Music, the Mind, and Artificial Intelligence," geared toward non-music majors, as an exploration of AI as a tool, not a replacement for creativity. 

"We approach it from user cognition," said Rowe. "What happens to us when we're producing or listening to music? How do we as humans process it? And then we go through the history of AI more generally, leading up to the current state of affairs: large language models, and so forth."

Meanwhile, both UC Berkeley’s Center for New Music and Audio Technologies and The Berklee College of Music's Emerging Artistic Technology Lab are addressing this pivot.

"I am redesigning the pedagogy in a way that is more about creating creative coding for music, where the focus is not about developing neural networks, but is about understanding the behaviors of these neural networks and understanding how you find the space where these interact with music making or music composition or performance at large," Cella said. 

Jonathan Wyner, the head of artistic technology initiatives for Berklee's tech lab, wants to introduce students to new technology in part because it’s where opportunity lives.  

"We feel a sense of responsibility to provide access to tools and to help the students understand what it means to go out into the world where these tools exist and make smart decisions for themselves about how, when, and where to engage with them," he told The Deep View. 

Wyner advocates for "the creative position" within AI music companies like Suno and Moises, acknowledging those organizations are technical in nature. Having those roles allows generation tools to produce "the best sound possible," he said. "I believe that great sound is important, both from the standpoint of expression and also the standpoint of culture." 

In his position, he can influence the systems, ensuring they’re useful for musicians. "The ones that we learn from as we interact with them, and they help us get better at our craft, as opposed to systems that simply automate all the decisions and remove decisions and control from the user."

Advocacy is an ongoing effort in the ideal partnership between AI music companies and musicians. Wyner hopes "that as students figure out where the technology is useful or not useful, that that becomes a force for putting pressure on the developers to make tools better, so they actually work for musicians." 

Why listeners are getting weird 

But AI isn't just changing the way that music is being made. It's changing the things that listeners want to hear. And in the face of ultra-polished, pitch perfect AI-generated music, consumers, too, are leaning into weird. 

Let's take the masked Canadian fusion band, Angine de Poitrine, as an example. The duo, which dresses up in fantastical alien-like masks for their performances, skyrocketed into the public eye earlier this year after publishing a 28-minute live set on YouTube that went viral, scoring 18 million views since it was posted in February by the KEXP radio station. 

The band is the definition of outlandish, both in their use of complex time signatures, microtonal scales and unpredictable, progressive-rock melody patterns, and in the genre-bending way they define themselves: as a pair of "space-time voyagers" in a "mantra-rock, Dadaist, Pythagorean-Cubist orchestra."

It is true that weird things often catch the eye of the consumer. If you're scrolling on your Instagram or TikTok feed and you come across a polka dot-clad band that's playing music that sounds like aliens trying to emulate human music, you're probably going to stop and listen. Though Angine de Poitrine and the "math rock" genre has generally preceded the age of AI, the recent reverence for this band goes beyond just the simple fact that they are doing something unique: Many listeners see this kind of music as everything that AI isn't. 

And it's evidenced by some of the comments under their viral radio set. One commenter wrote "I showed this to an AI and it factory reset itself out of fear." Another, meanwhile, said that "this is 100% why AI can't and shouldn't replace human art and creativity." And another wrote that "the sophistication of this band is what makes me have faith in humanity. AI can’t beat or replicate this kind of artistic output." 

The success of Angine de Poitrine may be a harbinger. "I don't know exactly how music will change, but I do think what musicians will start doing will be one step ahead of [what] the generative models that can replicate," Geraldo Ramos, CEO of AI music production firm Moises, told The Deep View. 

It's not just whimsical and outlandish sounds that consumers are leaning into, said Das. It's imperfections. More than ever, listeners are craving mistakes in their music, he said. Things like sour notes, off-rhythm playing, or vocal cracks are the things that distinguish human-generated music from its AI counterpart.

"Where we are in 2026, the knock on AI music seems to be generally that it sounds too perfect," Das added. "People think they can identify AI tracks because it's just beyond what's perfect. I can see that there could be enough of a backlash to this movement where people just crave the real thing." 

Naturally, the desire for organic sound could lead to a surging interest in live music, said Ramos. Being able to play an instrument live at all will become "way more valuable as more music becomes AI," he said. Fans will want to see their favorite musicians with their fingers on keys and strings, to hear their voices shift and crack in ways that AI doesn't emulate. 

And artists, too, want to show off their capabilities—even those in genres that don't always lend themselves to raw, live performances using instruments. 

It's why Armin Van Buuren, a Dutch Grammy-nominated DJ, recorded one of his electronic albums as a live piano performance. "That's the reason why I want to sit behind the piano and play," he told The Deep View. "So you can see what I'm doing is real, there's a chance for mistakes, every piano performance is different, there's a beauty to it." 

The blurring lines

What consumers dislike more than AI-generated music, however, is being tricked by it. 

For instance, in November, the song "I Run" by HAVEN achieved virality well before listeners realized that the song's producers used Suno to transform Harrison Walker’s vocals into a feminine voice. The backlash led to the song being banned from streaming services entirely. Meanwhile, a band called The Velvet Sundown, garnered over a million listeners across streaming platforms before admitting it was "a synthetic music project guided by human creative direction," much to the dismay of fans. 

Tired of being misled, many are now dedicated to sniffing out AI bands. One TikTok account by the band Pawns or Kings has an entire series dedicated to investigating: "Is this band real or AI?"'

"There are few people who would actually say AI-generated music is bad, but I think we live in a world where there's people who want to reward an artist that they like, not just because they like their music, but because they like the person," Mike Pappas, CEO of Modulate, a company that has created AI music and deepfake detection software, told The Deep View. 

Though listeners are actively searching for imperfect sound, at first blush, the vast majority aren't actually able to tell the difference. A November study from music streaming service Deezer and market research firm Ipsos found that, of 9,000 people from eight different countries, 97% couldn't tell the difference between fully AI-generated music and human-created music. Around 71% of respondents were surprised by these results, and more than half, 52%, said they were uncomfortable not being able to tell the difference. Around 45% said they would like the option to filter out 100% AI-generated music from their streaming platforms. 

There are a number of efforts to increase transparency between what is and isn't AI-generated for listeners. The most prominent of those efforts is digital watermarking, such as with Google DeepMind's SynthID, Jeff Chang, director of product management at Google DeepMind, told The Deep View. The SynthID watermark is one of the most widely-adopted standards for detecting AI-generated content, adopted by labs OpenAI, Anthropic and ElevenLabs. 

"We're pretty proud of the SynthID standard that we've been evangelizing," said Chang. "We want to encourage a whole ecosystem to be transparent about this stuff, and so SynthID is our way of doing that, and we're glad that other parts of the ecosystem are signing up for that now too." 

However, because not every music generation model abides by SynthID standards, Modulate has created a different solution, said Pappas. In July, the company released an API for detecting AI-generated music without relying on picking out watermarks. The company's tool is 95% accurate, and detects AI in the specifics of the music itself. Pappas said that makes its tech "a lot more resilient as a new model comes out every single day," he said. "There's always a way to just work around that watermark."

But with constantly shifting ethical boundaries on where AI should or shouldn't belong in music, Modulate drew its own line in the sand: The company detects specifically whether vocals or instrumentals were synthesized by an AI model, rather than flagging if something was merely digitally altered, Pappas said. 

"We're trying to draw a line around: 'did a human actually perform this in some fashion, or was it completely manifested out of AI?'" Pappas said. 

The cultural shift 

Pappas has a point: The boundaries of where AI does and doesn't belong in music are constantly changing. And that means that the nature of music itself, both for its creators and consumers, is bound to change with it. 

Something we shouldn't forget, however, is that this is the nature of how technology and music have always interacted. Things like synthesizers, autotune, sample libraries and more created new sounds that weren't even conceivable before their invention. As Prey put it, "The music industry is one of the most interesting industries to look at, because it's constantly adapting to new technologies."  

Though the ethical lines are still being navigated, AI may have the same effect, supercharging the most creative artists among us to create new types of music that weren't previously conceivable. It may also light a fire that fuels human creativity as counter culture, influencing musicians to create sounds that may be outside of their comfort zone.  

That, at least, would be the best case scenario. The reality, like all things that AI touches, lies somewhere in the middle: Between the death of the arts and an entirely new era of inconceivable creativity.

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