Artificial intelligence is scrambling the traditional signals of value in music, from technical skill to the idea of authorship itself. As creation tools become widely accessible, the line between artist and audience starts to blur. Songs that once took years of practice or a full studio setup can now be generated in minutes. Effort is harder to see, scarcity is disappearing, and even "who made this?" is becoming a more complicated question. In a world where anyone can hit the "create" button, value starts to shift toward what actually makes people stop and listen.
Tina Houser, CEO and Co-Founder of Song Mates, LLC, doing business as Press Play – Music Lovers Unite, is focused on creating an artist-centric music ecosystem designed for this new era. A multi-company founder, she brings a track record of scaling businesses across industries. Alongside her is Dean Baldwin, Song Mates' Head of Product Development and Co-Founder and longtime on-air host for SiriusXM’s Classic Rewind, Classic Vinyl, and Deep Tracks. With experience spanning product, media, and audience engagement, Baldwin has spent his career immersed in music and listener behavior. Together, their perspectives point to one of the most immediate changes: the collapse of the boundary between artist and audience.
"Streaming has already destroyed music. AI is just building on top of that and further shifting the perceived value," says Baldwin. In his view, streaming redefined music from something owned to something accessed. Instead of paying for individual songs, listeners pay for unlimited availability, flattening the perceived value of any single track. AI accelerates that trend by dramatically increasing supply. Today, anyone can generate and release dozens of songs in a weekend, lowering the barrier to participation and decoupling creation from mastery. The result is an ecosystem where volume rises, but traditional signals of value become harder to identify.
- Six hours vs. six strings: Baldwin contends this change is what devalued the labor and skill behind the art, helping create a cultural environment where a song made in six hours could be perceived as equal to one crafted over a 30-year career. "I had someone on TikTok challenge me, asking how I feel knowing I've spent decades learning an instrument when they can create the same song in a couple of hours without even knowing how to play," Baldwin recalls. "They were dismissing the skill set."
- Digital dissenters: For many younger artists, this resistance appears rooted in economic reality, as they see their peers directly impacted. Their solidarity spills over into the cultural realm, where they face a new attitude from some listeners who, empowered with AI tools, are becoming dismissive of the very idea of hard-won skill. "Surprisingly, our younger indie artists are more against AI usage than our older, legacy artists are," Houser notes. "We were talking to Allie Colleen and she was saying how she's a little upset with AI because she sees that her session musician friends are no longer being used. And that to her is disappointing."
With an influx of machine-made content, one optimistic theory is that authentic human creation will become more valuable by comparison. Houser suggests that as AI floods the market with cheap "posters," the value of an original "Monet" will only increase, a vision championed by platforms that have started banning AI-generated music outright. The vision is hopeful, but the difficulty of distinguishing AI from human work is proving to be a major hurdle. "A notable musician released an album, and he waited until I was four songs in to let me know the whole thing was AI-generated," Baldwin counters. "He wrote the lyrics and then spent the last year working like a producer would, crafting every single track very meticulously. The quality of the audio is phenomenal."
- The Nickelback test: That ambiguity is now spilling into regulation. In the U.S., emerging interpretations of copyright law are beginning to require disclosure of AI involvement for a work to qualify for protection. At the same time, major players like Suno, Google, and UMG are moving quickly to establish licensing frameworks, while artists push for clearer provenance standards. But defining a clean boundary has proven difficult, and efforts to draw one often introduce new gray areas. "If a teenager can sit in their room and, with a simple prompt for a song about roses and breakups in the style of Nickelback, generate a complete track to upload to Spotify to make money, that is definitely a line for me," says Houser.
- One man band 2.0: Just when the battle lines seem clear, a real-world example emerges to scramble the narrative. Baldwin points to the story of Derek Palace, founding drummer of the legendary Australian rock band Little River Band. For a recent solo album, Palace used AI in the service of an uncompromising artistic vision, allowing him to achieve a more perfect version of his sound by eliminating the variable of human collaborators. "Derek told me that this is the first time he's been able to produce the album that he has written the way he wants it, without having to worry about session musicians trying to color the sound," Baldwin recalls. "The nuances in some of those tracks, like the acoustic guitar and the cello parts, are very dynamic. I was blown away that AI was able to do that. It fooled me."
With no simple technological or regulatory fix, the conversation circles back to the group that may ultimately determine the outcome: the listener. The future value of music will likely be determined not by regulators or technologists, but by a conscious choice from audiences who may ultimately decide to fight for human-created work. Baldwin offers a final, poetic thought, pointing to the unquantifiable "terroir" of music born from a specific time and place, an essence he calls the "Maple movement" in Canadian rock. "You have The Guess Who, The Band, Triumph, Rush, Loverboy, Bryan Adams, and all of them bring something very special into their sound that is consistent," he concludes. "Whatever that thing is, it's localized to the experience of the people that developed as musicians in that northern region. Can AI replicate that? I don't know. And that's what we're going to have to wait and find out."