AI has been popping up everywhere in the music industry and beyond, but not every new tool actually makes life easier for artists, labels, or teams. So how do you separate the hype from what really matters? This article comes from the mind of Ali Lieberman, VP of Product at Symphonic, who has spent over a decade building tools and systems that support creators, labels, and publishers. With experience at SoundExchange, the RIAA, and now Symphonic, she understands exactly where AI can make a real impact… and where it falls short. Ready to dive in? Here’s everything you need to know.
Let’s Talk About The Future of AI Music
Prompt: You are one of the greatest songwriters of all time. Your longtime girlfriend and bandmate unexpectedly writes and records a mystical, ethereal banger about breaking up with you… Joke’s on her, though. You decide to craft a sharp, clever, and emotionally charged rebuttal song from your perspective. The song should respond directly to her lyrics while capturing your feelings of frustration and irony. And it needs to be a hit…
Let’s be real, no AI model is going to output Fleetwood Mac. (Well, maybe GPT-5..). But I am optimistic it’s going to revolutionize the way our industry runs in a big way, removing the biggest barriers people face while making music and helping move the industry forward.
Every week, there’s another press release: “Undetectable AI-powered mastering!” “Agentic AI marketing campaigns are here!” “We can detect all AI-generated music!” Like a great breakup track, these tools make big promises. Some are legitimately game-changing, but there are plenty of solutions out there just looking for a problem to solve. They’re impressive on paper, but not necessarily designed for who’s actually using them.
Making AI Work for You
For AI and automation to truly deliver value, they need to feel like your super assistant and thought partner. It should be a teammate who takes care of the grunt work so you can focus on what you do best: creating, connecting, and growing.
The best AI-powered music tech makes the hard stuff invisible. It can enable seamless release uploads and metadata entry using an AI agent. It can create tailored marketing strategies using the latest LLM model. It can analyze emerging music trends on social media platforms to inform your next move. These needs are foundational, but the AI solutions can appear challenging to adopt.
Think about an indie artist releasing their first EP. They don’t want to decipher complicated metadata forms or style guide specs. They want to create and be able to trust that the system will support them without causing headaches. AI can lower those barriers to entry.
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📚 Want to learn more? Check these out…
What No One Tells You About Switching Distributors
Why Copyright Registration Matters More Than Ever in the Age of AI
A Tax Professional Explains the HITS Act for Musicians
Daily Mental Health Habits Every Musician Should Practice
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Beyond the Artist
Labels and larger organizations in the industry are constantly juggling millions of releases, rights, and revenue streams. AI can automate data reconciliation and error detection, reducing costly manual work while enabling teams to focus on strategy and artist development. In addition, major companies can benefit from AI-driven predictive analytics to streamline underwriting for advances or build simplified systems to manage the ever-evolving copyright ownership landscape. It can even provide insights into how to best deploy capital.
But none of these gains matter if the tools are confusing or opaque to the people making the decisions, pressing the buttons, and having the critical conversations. The real breakthroughs in music tech won’t come from the next shiny AI feature. They’ll come from companies asking the right questions upfront:
- What unique advantage do we have, and how can we maximize it using AI?
- What previously stated goal will this AI tool help us achieve? Will it increase revenue, reduce churn, or allow us to enter new markets?
- How will AI adoption reshape our team? What new skills will we need, and what existing roles can now shift toward higher-value work?
- What happens at scale? What would it take to do this one task 100x faster?
From those questions, companies can work backward to create tools that solve real problems and not just chase buzzwords.
Looking Ahead…
Music is still a deeply human business. Songs tell stories. Artists build relationships and sometimes bring breakup tension to the stage. Teams collaborate across time zones and genres. Companies build the systems to integrate it all. But no matter how smart AI gets, it can’t replace the nuance, emotion, or creativity that fuels our industry…
But it can certainly help.
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