AI and AI in music production
How artificial intelligence is finding its way into our everyday lives
Regardless of whether it is about converting a frequency response into a tonal balance to the music direction, using a limiter with the right settings, adjusting the stereo width of a signal, or automatic EQ corrections in tonality and resonant frequencies to perform. With the help of intelligent algorithms, AI, i.e. artificial intelligence, has managed to simplify work significantly, make it easier and sometimes even take it off completely.
Whether these are manufacturers AI-based VST plugins such as Isotopes, Sonible or baby audio ultimately plays a subordinate role. The fact is that the algorithms have now become very good and allow us to improve the work process in the Music Production or in mixing or mastering and relieve us of decisions for which we may have previously had to create several versions of a mix in order to compare which setting we prefer for our project.
Amazingly but at the same time the demand increases after tutorials and lessons in music production, mixing and mastering. We personally see a direct connection here. Of course, the number of music enthusiasts is constantly growing due to the affordable conditions for music production, mixing and mastering. If you think back 15 or 20 years, hardly any normal mortal could own their own musical equipment or a reasonable one Audio PC afford because the costs were extremely high. But technology has continued to evolve over the past few years and has become affordable for almost everyone. Be it the audio interface, the microphone, the acoustic elements or the monitoring monitors. Due to the further development of technology, you can already get high quality for a relatively low price compared to the price level of 15 years ago.
Nevertheless, we see a direct connection between the decrease in decisions in music production, mixing or mastering and the increase in knowledge gaps, which processes in the background artificial intelligence takes over for us and why the AI makes certain decisions for us.
AI-generated music also raises new legal questions: Who actually owns a song created by AI? You can read about this in our guide. Copyright of AI songs. Since July 2026, there has also been a new labeling standard of the music industry for AI music.
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How do we deal with technological progress?
When decisions are made for them, people tend to no longer question them, provided they are positive, and to deal with the reasons for the decisions made. We suspect the same for music production and its techniques and possible applications.
So maybe we don't ask ourselves why anymore Compressor set a very short attack time and a very long release time for our piece, but just accept it. Basically, as long as the sound sounds good to us, that's not a bad approach, but as soon as we go into detail and know exactly where we want to go with the sound and what the end result should look like or sound like, we need understanding again for the processes that run for us in the background. Add to that the possibility that the result we hear may sound good, but do we really know if it is Maximum is that we can achieve according to our idea of sound?
Reviewing the artificial intelligence results, can we really be sure that a VCA compressor would be a better fit on our master bus than an opto compressor?
Do we really know if it is necessary to increase the bass range so much monofy, as suggested and set by the Stereotool with the help of artificial intelligence?
In order to judge this from a purely musical point of view, we need to understand where and why the artificial intelligence made this decision. From a technical point of view, we need to understand which reference values are the right ones in our analysis tools such as metering or goniometers.
Our conclusion on artificial intelligence in music production, mixing and mastering
Artificial Intelligence, or AI for short, can definitely be an advantage in music production be. Basically, we advise not always accepting the given as it is, but rather questioning processes and decisions made. This is the only way to ensure a continuous increase in your own productivity and quality in music production, mixing and mastering.
Does AI replace the work of a mastering engineer in the mastering process?
No. AI-powered tools like iZotope or Sonible analyze frequency response, levels, and stereo width, providing quick starting points. However, they make decisions based on averages and don't know your precise sound preferences. Genre context, reference tracks, and targeted detail corrections still require a trained ear. AI accelerates the workflow, but it doesn't replace an understanding of the underlying processes.
Which AI plugins are used in mixing and mastering?
AI-based VST plugins from iZotope, Sonible, and Baby Audio are widely used. They handle tasks such as automatic EQ correction of resonant frequencies, limiter settings, tonal balance, and stereo width adjustment. The algorithms analyze the audio material and suggest settings. The specific manufacturer is secondary; what matters is that you can understand the suggested adjustments and correct them if necessary.
Why should I learn mixing and mastering when AI automates so much?
Because AI makes decisions for you without explaining them. If you don't understand why a compressor uses a short attack and long release, or why an EQ reduces resonance, you can't control the result effectively. As long as the sound happens to be right, automation is sufficient, but for specific sonic goals, you need to understand the processes. That's precisely why the demand for instruction is increasing alongside the spread of AI.
Who owns the rights to a song generated with AI?
The copyright situation for AI-generated music is complex and depends on the amount of human creative input and the terms of service of the AI service used. Purely automatically generated content without human creation often does not enjoy full copyright protection. Peak-Studios addresses the details and specific pitfalls in a separate guide to the copyright of AI songs.
How can I tell if AI mastering has reached its sonic maximum?
An AI-generated result can sound good but still not be optimal. Compare the result with high-quality reference tracks of the same genre on multiple listening systems and critically examine the tonal balance, dynamics, and stereo image. Only with a clear understanding of the sound and the underlying processes can you judge whether the automatic adjustments have already achieved their goal or whether targeted manual interventions can yield noticeably better results.
