How AI Is Changing the Way We Create and Listen to Music

Before generative AI, Googling new music was largely a waste of time. Typing “motivational rap song before important meeting” would turn up a few Reddit subthreads, but little to match the mood.

Today, that same search brings listeners down a rabbit hole of relevant tracks, complete with vocals, instrumentation and lyrics. It also opens the door to creating something entirely new just for that moment – even if you can’t carry a tune.

Can Anyone Create Music Today?

AI has drastically lowered barriers to entry for music creation. Platforms such as Suno and Udio have turned creating music within a minute into reality, bringing it within reach of anyone with an idea and an internet connection. No musical training, no expensive studio time, just a creative (or curious) prompt, translated into sound. Modern AI music systems go far beyond basic generation; they also understand mood, genre, structure, and even artistic identity.

This accessibility has led to an explosion of AI music. Streaming platforms are now seeing tons of AI-generated songs uploaded. Deezer has revealed that roughly 10,000 fully AI-generated tracks land on its platform daily, a volume significant enough that the service has chosen to exclude such content from its algorithmic recommendations and editorial playlists, in an effort to protect visibility for human artists.

The trend goes beyond individual tracks: entirely AI-built acts are now winning over real audiences. The Velvet Sundown, an AI country band, topped Spotify’s charts in 2025 and has over 1.4 million monthly listeners, despite being entirely machine-made. Similarly, Sienna Rose, an AI artist drawing comparisons to Norah Jones and Alicia Keys with jazzy guitar lines and silky vocals, has built a following among listeners who had no idea they weren’t hearing a real person.

For creators, this can be disruptive, and for new artists, empowering. AI is no longer just a tool; it’s a collaborator.

Using AI as a Studio Partner

For musicians and producers, AI can act as a studio partner, helping to accelerate production while preserving their unique voice, instrumentation, and creative direction. AI tools like iZotope Ozone simplify the mastering process, delivering professional results in minutes. iZotope Neutron assists with intelligent mixing suggestions and track balancing. Meanwhile, platforms such as Loudly offer stem separation, allowing creators to break down existing tracks (usually vocals, drums, and other instruments), and rework them. 

These tools enhance creative workflows without replacing them, accelerate technical tasks, and allow artists to stay focused on their own musical ideas.

Listening to the Algorithm

AI is not only changing how music is made, but how it’s discovered. Music streaming platforms like Spotify, Tidal, or Apple Music have evolved into highly personalised services. Recommendation engines analyse listening habits, moods, and behaviours to deliver curated experiences rather than static libraries. These changes have made listening more convenient, but also more algorithm-driven.

Spotify introduced AI Playlists, which allows users to type a unique prompt into a chat in order for the AI tool to organise lists suited to that specific request. Emojis or even colours can be used to generate these playlists.

Online radio is also progressing alongside these changes. While streaming platforms rely heavily on algorithms, tools like Airtime Pro give creators full control over how music is presented. With Airtime Pro, users can build and manage their own online radio stations, schedule shows, and combine AI-generated tracks with human curation.

Ethical Questions Around AI in Music

The rise of AI in music raises serious and valid questions. Should AI be trained on artists’ work without consent? Who should be paid when AI generates music in someone’s style or based on existing material? And should listeners be informed when a song is AI-generated?

Generative AI models are often trained on vast datasets sourced from the internet and music platforms, sometimes without clear licensing, raising concerns about potential copyright infringement. These systems can produce works that closely resemble existing music, blurring the line between inspiration and imitation. In response, major record labels have taken legal action, pushing for licensing agreements and clearer regulation.

At present, there is no single global law specifically governing AI-generated music, but the demand is growing for more defined rules and industry standards.

It isn’t all bad for creators. AI could help artists safeguard their work against intellectual property violations by tracking the unauthorised use of copyrighted music. Using advanced audio recognition technology, it can identify plagiarism and copyright infringement through detailed track-to-track analysis and comparison. AI-driven copyright detection supports artists in maintaining control over their work, ensuring they receive proper credit and compensation.

A New Era of Sound

The future of music is being changed by AI, which is accelerating creation, expanding who can make music, and transforming how listeners experience it. Even as the volume of music grows, the human touch remains essential, guiding curation, storytelling, and the connections, feelings, and emotions that give meaning to what we hear.