Artificial intelligence didn’t start with apps or smart speakers. It began as an idea. Something theoretical. Early researchers sketched it out as lines of code on paper, trying to show how a machine might “think”.
The term ‘artificial intelligence’ itself was first used in 1955 by John McCarthy. Who described it simply as the science and engineering of making intelligent machines. That one definition helped shape everything from today’s digital assistants to the algorithms quietly running in the background of our lives.
McCarthy believed machines could eventually think like humans, meaning they don’t just calculate but they reason. His focus was something he called “common-sense reasoning”, the kind of everyday logic people use without even noticing through pattern recognition. If a machine could store enough information and process it properly, he argued it could produce results that actually make sense to us.
AI was also developing alongside cybernetics. This field looked at how biological and mechanical systems communicate and respond to feedback. AI eventually grew out of this space, especially in the way it learns from data and adjusts its behaviour. Those early ideas still show through modern systems today. Even in something as creative as music.
How is AI used in music today?
in the modern day you’ll find AI everywhere in music even the parts you’d never expect.
One of the most well known uses is generative composition. Platforms like AIVA, Amper Music, and Soundraw let users create full songs in minutes. If you pick the mood, tempo, and style, The system does the rest. Its quick efficient and flexible witch is what makes it popular in arias such as advertising, gaming and other online content. Critics argue that while AI can produce music fast, it often lacks depth that only a human could add like the emotion and human edge.
AI isn’t just replacing tasks, it’s also assisting them. Tools like LANDR and iZotope help with mixing and mastering. They analyse huge amounts of data from professional tracks and make decisions on things like EQ, compression, and loudness. For independent artists, that’s a big win because it lowers the barrier to entry. However, there is a downside. when everyone is using the same AI systems which uses the same data, music can start to sound similar and predictable.
Then there’s AI voice synthesis. New systems can replicate human voices with impressive accuracy. Grimes has taken a different approach, openly allowing people to use AI versions of her voice, as long as she gets a share of the revenue. She sees it as a way to open up creativity and rethink ownership. Many strongly disagree. In 2023, AI-generated songs mimicking Drake and The Weeknd went viral before being taken down after only hours. Many artists had serious questions about consent, identity, and control following this.
AI shapes how we discover and listen to music too. Platforms like Spotify and Apple Music rely heavily on algorithms to recommend songs like the Spotify DJ feature. Many listeners like these features because it helps them find new artists easier. But some artists are starting to think about the algorithm when they create new music, which leads to shorter intros, Frequent releases, and Consistency over experimentation. This means that the system doesn’t just recommend music but influences it.
in the industry AI is often used as a tool, something to be used and not feared. but the catch is that without proper regulation, artists risk losing control over every aspect of their work (how it’s used, how it’s shared, and how it’s monetised). At the time of writing AI in music sits in a grey area. It can open doors for musicians without a very high budget and make the process a lot easier but in the process it also uses other songs to collect this data.
The future of AI in music
AI isn’t going anywhere for now, if anything its more likely to just get more embedded. So the real question is if AI does continue to shape music at this rate will the power be in humans hand or the computer programs.
One possible future is collaboration. AI working alongside humans, Acting as a tool for experimentation. This would be a good way to explore new sounds and ideas faster than ever before. In this scenario humans stay in control with AI just expanding possibilities.
Training AI on copyrighted material without permission is already a major issue. If it continues, it could seriously damage the livelihoods of artists, expessualy those just starting out.
There’s also the question of skill erosion. With AI doing more there won’t be any point in people learning the skills that could lead to a decline in both technical ability and musical understanding. Technology has always shaped music but this feels different because of the possibility’s and power its already showing
At the same time, AI makes music more accessible. People without formal training can now create full compositions. This raises the question what matters more? skill or intent.
Personally, as a musician and someone who’s going on to study music production, I think AI can be a positive thing. But only if it’s handled properly. The problem isn’t the technology itself but who controls and benefits from it. If it’s re-built on consent, fairness, and transparency, it could become a genuinely valuable tool that supports creativity.
Because at the end of the day, music should be human. It’s emotional. It’s expressive witch ai should not take away from