Artificial Intelligence (AI) is becoming an increasingly exceptional yet controversial influence on creatives, particularly in music production.
As AI tools become increasingly accessible, they challenge long-held notions of authenticity, creativity and artistic ownership. In turn, this is forcing the industry to confront urgent ethical, legal and emotional questions about what it means to create music in the digital age.
In Greater Manchester, businesses are already exploring how AI can reshape the music industry. For example, Sineco, a local startup in Tameside, is developing adaptive audio that responds in real time to biometric data, creating personalised music for fitness, wellbeing and performance. Read more about Sineco’s story here.
For businesses and creators in the region’s thriving music and digital sectors, understanding the opportunities and risks of AI in music production is becoming increasingly important. From composition tools to copyright concerns, Oliver Witty from our Innovation team shares what you need to keep in mind.
How AI Is Used in Music Production
AI-powered software is now capable of automating various aspects of music production. From mixing and mastering to composing entire tracks, these tools use algorithms and machine learning to assist or even lead the entire creative process.
These tools feed off datasets of existing music and provide the foundations for algorithms to identify patterns, or arguably “influences”. Generative AI will then create new parts of songs, such as drum rhythms and template vocal melodies, or even full songs tailored to a specific genre.
One example of AI tools used in music production is Suno (which means “listen” in Hindi). Suno is a generative AI tool designed to produce “realistic” songs, and was widely available in 2023 after it was included as a plug-in to Microsoft Copilot.
Despite its relatively recent launch, a Suno user known as “imoliver” signed a contract with Hallwood Media in July 2025, marking the first time an AI-based creator joined a traditional music label. This is just one example of how rapidly AI is infiltrating the music industry.
Is AI Different From Sampling?
Sampling and AI-generated composition are fundamentally different. According to Jones Walker LLP, sampling “incorporates existing recordings into new musical works.” It involves deliberate, creative choices – selecting, editing and recontextualizing segments of original songs to craft something new. This process requires a deep understanding of music production to achieve the right sound.
Though a new piece of music will be created, sampling will still require permission from the copyright holder of the original track. The Musician’s Union offers guidance on how to sample legally and effectively.
Problems arise when samples are obtained without clearance. For instance, Lalal.ai, a “vocal remover and music source separation” service, allows users to extract vocals or instruments from existing tracks without permission. This would be considered an “uncleared sample” and could lead to legal consequences.
Though sampling and AI are different, this doesn’t mean that AI doesn’t have a place in sampling. Creators often use AI-assisted tools like LANDR to mix and master tracks, including those with samples. These tools can adjust audio levels for each instrument, enhance sound quality and reduce the need for expensive studio equipment.
Legal and Ethical Concerns
Whether AI merely acts as an assistant or is solely responsible for the writing and production process, the problem of copyright infringement remains. If an AI-generated melody closely resembles the original works it was trained on, legal disputes may arise.
Legal disputes surrounding AI in the music industry have been widespread, and platforms like Suno have been fending off lawsuits from record labels and independent artists alike. In October 2024, Radiohead frontman Thom Yorke and actress Julianne Moore were among 10,500 signatories of a statement warning companies like Suno that “the use of creative works for training generative AI is a major, unjust threat to the livelihoods of the people behind those works and must not be permitted.”
But legal disputes aren’t the only issue when it comes to AI – there are also concerns relating to AI algorithms, and if they are to perpetuate stereotypes and biases in music. If data sets that are fed into AI contain biases, then so will the music that is generated out of it. This could lead to a lack of representation and diversity in the industry.
However, it’s not entirely fair to ignore the ethical benefits of AI. High production costs and limited access to professional studios have previously been barriers to talented individuals hoping to break into the music industry. By providing easy access to these tools, AI helps break down these barriers and opens up a much more diverse cohort of music creators.
Whatever your angle on this ethical dilemma may be, it’s undeniable that anyone anticipating using AI to aid in their music production must tread with caution.
Should I Use AI to Create Music?
As generative AI continues to evolve, it’s not always clear which tools may pose risks down the line. What you do with your work may influence which AI-powered tools you can or should use. Do you intend to publish your work, or are you just experimenting for fun?
One thing is certain: AI lacks the human emotion and lived experiences that songwriters bring to their work. While one could argue that AI can help spark ideas, the passion and vulnerability of a songwriter often make the difference between something that feels generic and something that feels truly original.
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