Das Bild zeigt die KI in der Musikindustrie in Form einer wellenartigen Struktur.

The Added Value of AI in the Music Industry

With the increasing availability of AI (Artificial Intelligence) in the music industry, there is an opportunity to save a lot of work and streamline various processes. You can use them to simplify and optimise various tasks in your label, but also as a self-publisher and artist.
The tools presented here are only examples and we encourage you to do your own research as everyone has different needs and requirements.

AI Analysis

AI analytics tools offer many ways to analyse large amounts of data and extract information from it. For example, AI systems can analyse data from streaming platforms and social networks to find out which artists are trending and which music is popular with which audiences. This can help to target advertising and marketing more effectively and reach audiences more efficiently.
Examples of AI music analytics


Offered as a complete solution (database, desktop, mobile apps & API). It combines real-time and historical music consumption data (social media, charts, playlist, airplay monitoring) to improve project management, reporting and artist scouting.
Chartmetric: Provides a modern way to track, measure and analyse music data. It helps answer key questions about the evolution of music, so you can spend less time on analysis and more time on strategy.

AI Talent Scouting

Similarly, AI can help identify new talent. Artificial intelligence systems can use data analysis to identify which artists are most promising and what their potential is. In this way, new talent can be discovered and developed more quickly and efficiently.

Example of Talent Scout AI:


The developers call it the “hit potential algorithm” and claim it is not only able to classify and categorize new music, but also to accurately measure hit potential and filter out the tracks that are most likely to become a real hit, regardless of who or where they come from.

Image AI Design

The use of image AI’s on labels can help to create a unique selling point and visual identity. Cover artwork can be created that is tailored to the specific preferences of the target audience, ensuring better marketing of the music. By personalising the cover artwork, users can be targeted and feel an emotional connection to the music and the label. It can also save time and money by automating processes and speeding up the workflow.

Examples of AI Image Creation Tools


Promt-based AI for image creation that allows you to use a general or fine-tuned AI model to create all types of production-ready images. With a few clicks, you can train your own AI model and create thousands of variations and deviations from your training data.


An online graphic design tool that can be used for social media posts, cover art, posters, videos, logos and more. There are many pre-designed templates and design elements.

Adobe Sensei:

Sensei uses artificial intelligence and machine learning to deepen experiences, improve creative expression, accelerate tasks and workflows, and make real-time decisions.

AI on streaming platforms

AI systems can also make recommendations about what music might be of particular interest to users, based on their musical tastes and listening behaviour. These systems on various streaming platforms use machine learning algorithms to create personalised music recommendations for their users. They analyse the user’s listening behaviour and preferences and suggest new music that the user is likely to like.


In addition to these benefits, there are also challenges to the application of artificial intelligence. For example, the quality of the algorithms is highly dependent on the quality of the data used. Care must also be taken to ensure that the music label processes its users’ data in a privacy-compliant manner. Overall, however, the application offers many opportunities to make your work easier and better. By using AI, music labels can optimise their promotions and marketing, better reach their target audiences and shape their label identity. With the right strategy and the use of high-quality algorithms, it is possible for music labels and self-publishers to reap the benefits of the many different AI tools.

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