Did you know AI can make a whole song in just 40 seconds?
Pretty wild, right?
The Beatles even used AI to create a new song with John Lennon’s voice in 2025, decades after he died.
With AI music tools popping up everywhere, many musicians are worried.
Will computers take our jobs?
It’s not a simple yes or no. While AI can write tunes and even sing, it’s missing something special that only humans have.
Let’s talk about what AI can and can’t do, and why we still need human musicians.
Understanding AI in Music
Artificial intelligence (AI) in music is like having a super-smart assistant that helps musicians create and refine their work. It can write melodies, generate beats, clean up old recordings, and even suggest new ideas.
For example, The Beatles used AI to restore John Lennon’s voice “Now and Then,” which became the first AI-assisted track nominated for a Grammy in 2025. For the music industry, AI is a game-changer — it saves time, sparks creativity, and opens up new possibilities. But at its core, it’s still a tool that enhances, not replaces, the artistry of human musicians.
The Role of AI in Music Creation
Here are a few ways AI is being used in the music industry today:
Creative Assistance : Artists like Daniel Bedingfield are using AI to complete albums Restoration and Remastering : AI tools are being used to clean up and enhance old recordings. For instance, AI helped isolate John Lennon’s voice from a decades-old demo tape, making it possible to create a new Beatles song that sounds fresh and modern.Music Generation : Platforms like Suno and Udio allow musicians to generate entire tracks by inputting a few parameters
In short, AI is a powerful tool that’s helping musicians push boundaries, save time, and explore new creative possibilities—all while keeping the human touch at the heart of music.
Today’s music tools offer incredible capabilities:
Please note the ethical nature of tools like Suno and Udio and the pending lawsuits. Currently both tools train on copyrighted material, without compensating artists
Popular AI Music Software
Modern AI tools offer an impressive array of options for music production.
Lalal.ai stem separation tool Audioshake
When it comes to mixing and mastering, RoEx
For visual content creators, Neural Frames
Meanwhile, tools like Waves Online Mastering and Masterchannel
Case Studies of AI Compositions
The Beatles made history with “Now and Then,” using AI to clean up John Lennon’s vocals. Howard Jones is working with artist BT to develop an AI version of his voice
The Impact of AI on Musicians
This image is AI generated While some fear artificial intelligence will replace human musicians, many artists find ways to use it as a creative tool in their creative process. Imogen Heap created an AI twin called Mogen AI to create an entire album in 24 hours
Challenges Faced by Musicians
The music industry faces several key challenges with AI:
Copyright concerns over AI training data
Need to learn new technical skills
Market saturation from AI-produced music
Balancing human creativity with AI assistance
Opportunities for Musicians with AI
Despite challenges, AI offers exciting possibilities:
Faster production workflows
Access to professional-quality tools
New ways to collaborate
Ability to extend artistic legacy
Will AI Replace Musicians?
No – while AI can generate music quickly, it can’t replace the emotional depth and cultural understanding that humans bring to music. As Grimes notes, “There’s lots of room for AI in art
Limitations of AI in Creativity
While AI can write songs, it lacks the emotional intelligence and cultural context that makes music truly meaningful. Bloomberg columnist Dave Lee points out that AI can’t match human genius
Collaboration Between AI and Musicians
The best results come when humans and AI work together. Imogen Heap’s work with her AI twin Mogen and StyleFilter
Ethical Considerations in AI Music
The music industry is taking significant steps to protect artists’ rights in the age of AI, with organizations like GEMA and the RIAA leading the charge. GEMA, the German collecting society, has proposed a licensing model 30% of their income when using protected music to train their systems. This ensures that musicians are fairly compensated while allowing AI innovation to thrive. The model also includes a minimum payment guarantee, even if AI-generated music generates low revenue, ensuring creators are not left empty-handed.
Similarly, the RIAA has filed landmark lawsuits against AI music platforms Suno and Udio
Initiatives like Fairly Trained AI:OK
GEMA’s efforts, combined with the RIAA’s legal actions and industry-wide certifications, highlight a growing consensus: AI innovation must coexist with fair compensation for creators. This balance is crucial to preserving the value of human creativity in the music industry.
AI’s Influence on Music Genres
Machine learning and AI are revolutionizing how music genres are created and blended, making it easier than ever to experiment with new sounds. Tools like Suno , Udio , and Stable Audio allow artists to combine genres seamlessly, creating fresh and innovative styles. For example, you can mix electronic beats with classical strings or blend hip-hop rhythms with jazz harmonies — all with just a few clicks.
A great example of this is Daniel Bedingfield’s AI-assisted album, which showcases how artists can push boundaries while staying true to their unique style. By using AI, he was able to explore new musical territories, blending pop, R&B, and electronic elements in ways that felt both fresh and authentic.
AI music generators are particularly powerful for genre fusion. They analyze patterns from thousands of songs across different styles, enabling creators to experiment with combinations that might have been difficult or time-consuming to achieve manually. This opens up exciting possibilities for artists to break free from traditional genre constraints and create something entirely new.
While AI is a powerful tool for innovation, the human touch remains essential. Artists still need to guide the process, ensuring that the final product resonates emotionally and stays true to their vision. The result? A new era of genre-blending that’s as limitless as the creativity of the artists behind it.
Listener Perception of AI-Generated Music
Listeners are slowly warming up to AI-generated music, especially when it’s used as a tool by human artists. A great example is the Beatles’ song “Now and Then,” which used AI to restore John Lennon’s voice. Fans loved it because it felt authentic and emotionally connected to the band’s legacy.
However, most listeners still prefer music with a real human touch. While AI can create catchy melodies or polished tracks, it often lacks the depth, emotion, and storytelling that come from personal experiences. People connect with music that reflects real feelings — joy, heartbreak, or hope—and that’s something AI can’t fully replicate.
That said, AI is gaining acceptance in areas like background music for videos, games, or ads, where emotional depth isn’t the main focus. But for mainstream music, listeners still value the authenticity and creativity that only human artists can bring. The key is finding the right balance between AI innovation and human artistry.
Economic Impact of AI on the Music Industry
The AI music market is experiencing explosive growth, projected to reach $3.1 billion by 2028
New platforms are emerging to address these concerns. SpaceHeater, launching in early 2025, uses AI attribution technology to track how artists’ music is used in AI training models LANDR’s Fair Trade AI program
To protect creators’ rights in this rapidly evolving landscape, two major initiatives have emerged. Fairly Trained certifies AI models that respect creators’ rights, with 16 companies already certified including Beatoven Endel
How to Integrate AI in Music Production
Integrating AI into your music production process doesn’t have to be overwhelming. Start small, experiment, and gradually incorporate AI tools into your workflow. Here’s a step-by-step guide to help you get started:
If you’re new to AI, begin with tools that simplify repetitive tasks. For example:
RoEx : Use this AI-powered tool for mixing and mastering. It analyzes your track and automatically adjusts levels, EQ, and compression to give it a polished, professional sound.Forte! : This tool helps you import and organize audio files
Step 2: Experiment with Stem Separation Stem separation is a game-changer Lalal.ai and Audioshake can isolate vocals, drums, bass, and other elements from a track. This allows you to:
Remix existing songs.
Extract acapellas for new projects.
Reuse specific parts of a track in your compositions.
Step 3: Explore Music Generation AI can help you generate new ideas when you’re stuck. Try tools like:
Suno or Udio : These platforms let you create full tracks by inputting a few parameters. They’re great for brainstorming or creating backing tracks. (Please note the ethical nature of these tools and the pending lawsuits. Currently both tools train on copyrighted material, without compensating artists ).AudioCipher : Turn text into MIDI files and chord progressions. Type in a phrase, and the tool converts it into musical notes, sparking fresh ideas for melodies and harmonies.
Step 4: Dive into Advanced Features Once you’re comfortable, explore more advanced AI tools:
Neural Frames : Create AI-generated music videos by inputting your song. The tool generates visuals that match the mood and rhythm of your track.Voice Swap or Kits AI : Experiment with voice cloning to replicate vocals or create entirely new vocal styles.
Step 5: Combine AI with Your Creativity Remember, AI is just a tool. Use it to enhance your creativity, not replace it. For example:
Use AI-generated melodies as a starting point, then add your personal touch.
Let AI handle mixing and mastering, but fine-tune the results to match your vision.
Step 6: Stay Updated AI tools are evolving quickly with advancements in machine learning. Keep an eye on new developments and experiment with emerging technologies to stay ahead in the industry.
Skills Musicians Need in an AI-Driven World
To succeed with AI, focus on:
Learning basic AI music tools
Developing your unique style
Building strong fan connections
Staying curious about new technology
Understanding what AI can and can’t do
The Future of Musicians in the Age of AI
AI is changing how music is made, but what does this mean for musicians? Based on recent research and industry trends, the future holds both challenges and opportunities for those willing to adapt.
How AI is Reshaping Music Creation
The music industry has always changed with new technology. Now AI is the latest tool reshaping how we create and share music. By 2028, the market for AI music solutions is expected to grow to over $3 billion. This growth is happening across all areas of music production – from writing songs to mixing and mastering tracks.
Many musicians are already using AI in their work
Finding Balance Between AI and Human Creativity
Despite rapid growth, most experts agree that AI will help musicians rather than replace them. AI works best as a collaborator that handles technical tasks, giving artists more time to focus on the creative aspects that require human emotion and experience.
Some established artists are already finding this balance. Musicians like Imogen Heap are working with AI companies
Others are allowing their voices to be used in limited ways for new creators to experiment with.
Concerns About the Future
Many musicians worry about their livelihood. About 71% fear AI could make it harder to earn a living from music
The majority of musicians (89%) want AI-generated music to be clearly labeled. They also want proper credit and payment when their work is used to train AI systems.
How Musicians Can Thrive with AI
The most successful musicians will be those who learn to use AI as another tool in their creative process. This means:
Using AI for technical tasks like mixing or mastering
Exploring new creative directions with AI assistance
Focusing on the human elements that AI cannot replicate
Understanding both the capabilities and limitations of AI tools
The future of music isn’t about humans versus machines. It’s about finding the right partnership between human creativity and AI technology to create something neither could make alone.
