The Impact of Artificial Intelligence (AI) on Music Production
1. Introduction
This essay will examine the use of AI in music, providing an understanding of its evolution and impact on the music industry. As we increasingly witness the use of AI in music production software, I will also examine the beginnings of AI in the sector, explore the tools used in music production, and consider what the future holds.
Artificial Intelligence (AI) is already prominent in all our lives. AI and machine learning-enabled technologies are used in medicine, transportation, robotics, science, education, the military, surveillance, finance and regulation, agriculture, entertainment, retail, customer service, manufacturing, and our lives, like ChatGPT and Co-Pilot for text creation based on large language databases. AI use in the Music Industry is inevitable, although some see this as encroaching on creativity in what a person creates and what is artificially created.
From a personal perspective, I do not like the use of AI in music creativity and production. It stifles creativity and raises ethical concerns about who owns the music-created creativity and the potential devaluation of a human musician.
2. History of AI in Music
The potential for AI to revolutionise sound engineering is a source of inspiration for the future of music. David Cope, a Composer and Professor of Music at UC Santa Cruz, is known for his research into artificial intelligence and music. He created new pieces of music based on analysing existing music (Cope, 2025). In the early 1980s, David Cope was asked to compose an opera and had a deadline to meet. He procrastinated and began a new project, creating a music composition program he called EMI (Experiments in Musical Intelligence). Eight years later, he had what we could see as an AI program that created an opera in 2 days based on his composing style. He then applied the same method to his program to other composers like Chopin and Beethoven by updating the program to write in their styles. With the software he created, Emmy Beethoven 2 Beg (Cope, 2012), he demonstrated the potential of AI to revolutionise sound engineering, sparking excitement and intrigue about the future of music. In 2003, Cope started creating a software program called “ Emily Powel.” This program could be regarded as the start of AI in music. Instead of feeding a database of works that already existed, he gave the program a collection of works that EMI had produced to get it going, and from there, she began working on her musical style. (Jacqui Cheng, 2009) Emily “hears” feedback from listeners and builds their musical compositions from a source database derived from EMI.
3. Music Production and Music Distribution
Music Production, particularly sound engineering, including Arrangement, Tracking, Editing, Mixing, and Mastering, can now be managed by AI algorithms, and these tasks are fully automated, often in real-time. Studio production software allows you to create, master, and distribute music that uses large learning models and then applies them to improve new recordings. This saves time and makes high-quality production more accessible to independent artists.
AI’s role in software for composing and fine-tuning audio perfection in production studios has transformed music production. Artificial intelligence possesses a vast potential to innovate and enrich creativity through production. Indeed, it transforms the sounds beyond previous capabilities, thereby taking sound engineers to thresholds in their imagination, not a piece of imaginable news in the past. Such a thing could revolutionise sound engineering and provide a golden opportunity for even higher horizons for creativity in musical production.
Understanding the current use of AI, what producers think of the technology and tools available, and how this evolved A 1500 sample size survey in 2023 showed that 34.0 % of Music Producers felt positive for integrated AI, and 47.9% in favour of neutral utilisation. The study conducted by (Zlatic 2023) looked at the perceptions and attitudes of music producers on their thoughts on using AI. The results showed that many more respondents had responded positively and neutrally to this end. There is an increasing acceptance of using AI in the industry. This growing acceptance is a testament to the potential of AI in Music Production, providing reassurance about the future of AI’s use.
In distribution and consumption, AI is used by Music streaming platforms such as Spotify and Apple Music, which use AI algorithms that analyse user behaviour and recommend tracks and playlists based on the same. These algorithms consider everything from listening history and preference to even mood when creating playlists and recommending newer artists. This has helped listeners discover more niche genres and up-and-coming artists, but it also narrows down the music they listen to, as the algorithms expose users to music that fits their current tastes.
A report on the growth of generative AI in music production (market.us, 2024) showed that the AI music market was valued at $294M in 2023 and expected to grow to £3,421M by 2033. As can be seen, this is a tenfold increase in a short time.
4. Music Production Software Tools
Music production has changed in the past few decades. This has been due to the development of digital audio workstations (DAWS) and software synthesisers, making the instruments readily available to musicians worldwide with Professional Tools like Ableton Live, Logic Pro X and Cubase. However, with AI, the landscape is now set to change radically again. Numerous software programs are available for music production for both home and professional users, with major software companies entering this arena with easy-to-use click-and-go tools such as Avia, Soundraw and Boomy. (Tousley, 2024),(DI++O, 2024)
One of AI’s most significant contributions is to music creation. AI-powered tools like OpenAI’s Jukedeck, Amper Music, and Google’s Magenta enable musicians and producers to generate melodies, harmonies, and even full compositions with minimal human input.
Another popular tool is LANDR, which analyses the track’s audio file, considering the genre and production characteristics, and applies algorithms to optimise the sound. LANDR’s AI has been trained on a vast collection of mastered tracks, allowing it to make precise adjustments based on data from real-world examples. While LANDR does not fully replace human mastering engineers, it offers a quick and affordable solution for musicians who do not have the budget for professional mastering.
The tools enable everyone to be a potential creator. This approach to music production can make the audience feel more involved and part of the creative process.
5. Future of AI in the Music Industry
As technology evolves and becomes more sophisticated, AI’s role in the music industry will expand with impact, and we may find it harder to see the difference between human-made music and AI-produced music. It will help musicians generate ideas and variations quickly and can provide new techniques and ideas that enhance human creativity. AI is changing how we create, discover, and enjoy music in ways we never imagined possible.
As of 2024, the generative AI in the music market (market.us, 2024) is expanding rapidly as more artists and producers embrace AI-driven tools to enhance their workflows. The growing interest in AI-powered plugins and platforms is evident, with 28.6% of music producers identifying AI tools for mixing and mastering as the most valuable. Aiva Technologies, Ecrett Music, Google LLC, LANDR, Meta, Microsoft, OpenAI and Stability AI hold the largest market share.
While AI tools offer incredible potential for generating samples and sounds, they are most potent when used in collaboration with human creativity. Rather than replacing traditional music production methods, AI serves as an augmentation. The tools help with the creative process by generating ideas that producers can refine and incorporate into their work.
Producers can use AI tools by inputting specific preferences and then adjusting the generated samples to fit their artistic vision of what they are looking for. This blend of machine-driven innovation and human oversight creates a dynamic workflow where AI and the artist contribute to the final product. In this way, AI and human creativity coexist, with AI offering new ideas and possibilities while the producer maintains control over the artistic direction. (Sample sound, 2024)
6 Conclusion
When I decided to look at AI in music, I did not realise the significance of AI in the music industry over the last 50 years; I was very against technology due to ethics and copyright concerns and ongoing debates about copyright and the originality of AI-generated music. Issues arise over who holds the music rights created by AI and how musicians should be compensated when their work is used to train the AI models. I am now neutral; as we can see, in 1980, David Cope was using AI to create music, and as I saw with Music production software, this has advanced the Music Industry.
It has opened and expanded possibilities for innovation and efficiency unprecedented thus far; it also introduces challenges regarding the creativity, ownership, and value of human artistry. As technology continues to evolve, the industry needs to strike a balance between embracing the potentialities of AI and preserving qualities that make the experience of music a personal and a human experience in creating music. Researching this topic has made me realise I am more open to using AI in music production. As I embark on the next chapter at university, it will be interesting to see the changes AI will bring over the next four years.
AI for Music Production: 10 Tools to produce like a pro (2024) AI for Music Production: 10 Tools to Produce Like a Pro. Available at: https://dittomusic.com/en/blog/ai-for-music-production-tools-for-musicians
References
Ai is revolutionising sample creation and music production (2024) AI is Revolutionizing Sample Creation and Music Production. https://www.samplesoundmusic.com/blogs/news/how-ai-is-revolutionizing-sample-creation-the-future-of-music-production
Cope, D. (2012) David Cope Emmy Beethoven 2 beg, YouTube. Available at: https://www.youtube.com/watch?v=CgG1HipAayU
Cope, David (2025) Wikipedia. https://en.wikipedia.org/wiki/David_Cope
Cheng, Ars Technica (2009) Virtual composer makes beautiful music and stirs controversy, Ars Technica. https://arstechnica.com/science/2009/09/virtual-composer-makes-beautiful-musicand-stirs-controversy/
Generative AI in the music market (2024) Market.us.https://market.us/report/generative-ai-in-music-market/
Tousley, E. (2024) Best AI tools for Music Makers: Top 20 picks for 2024, Best AI Tools for Music Makers: Top 20 Picks for 2024. Available at: https://denovoagency.com/blogs/insights-and-strategies-for-the-modern-musician/best-ai-tools-for-music-makers-top-20-picks-for-2024
Zlatic, T. (2023) AI Music Survey: How 1,500 Music Producers use AI for music production, Bedroom Producers Blog. https://bedroomproducersblog.com/2023/05/30/ai-music-survey/
Cameron Rhodes 2025