The rapid development of artificial intelligence is presenting the creative industry with one of the biggest upheavals since digitalization. Tools such as generative music AI, image generators, and text models produce content in seconds – often in a quality that imitates or even surpasses human work. But this raises a crucial question: What is "art" today – and who is an "artist"?

The dissolution of classical definitions of art

Traditionally, art was considered an expression of human creativity, experience, and emotion. An artist was someone who created works through talent, practice, and individuality. In the age of AI, this boundary is becoming increasingly blurred.

If a machine generates new content based on millions of existing works, is the result still original? Or is it an algorithmic recombination of existing ideas?

The problem lies at the heart of the technology: AI models don't learn in a vacuum. They are trained with gigantic amounts of data – including music, texts, and images from real artists. This content forms the basis for new, AI-generated works.

The invisible influence of true artists

Many creative people today face a paradoxical scenario:
Their work is part of the training data without their knowledge – let alone being compensated for it.

This leads to a silent shift in value:

• Artists unconsciously provide the creative basis
• AI companies are monetizing systems built on this technology.
• End users generate content without direct reference to the original creator.

This is particularly critical in the music industry. Style copies, AI-generated vocals, or "inspired by" tracks are often based on real artists without naming or involving them.

Why collecting societies are in demand now

Organizations such as GEMA, SUISA or BMI are facing a new challenge:
They must not only manage existing uses, but also capture invisible, data-driven uses.

One possible approach would be:

• Introduction of AI training licenses
• Compensation for the use of works in datasets
• Transparency obligations for AI companies
• Participation models for style-based use

This would allow collecting societies to expand their role – from the classic exploitation of rights to the data economy of creativity.

New definitions: Artists as a data source?

In the age of AI, the definition of the artist could shift:

• From sole creator → to co-creator of a collective data system
• From producer of works → to style leader and source of inspiration
• From author → to data supplier with a claim to participation

This does not mean that human art loses value – on the contrary.
Authenticity, personality, and genuine emotion become even more important because they cannot be fully reproduced.

The opportunity: Fairness instead of loss of control

The current situation is not an inevitable loss of control, but an opportunity for new, fair models:

• Micro-compensation for AI training
• Blockchain-based rights enforcement
• Opt-in/opt-out systems for artists
• New licensing models for generative content

Once these systems are established, AI can become a tool that empowers rather than replaces creative people.

Conclusion: The future of art is hybrid.

Art in the AI age is neither purely human nor purely machine-based – it is hybrid.
However, for this system to work sustainably, it needs clear rules and fair compensation.

Collecting societies must play a key role in this:
As an intermediary between technology, creatives and business.

Because one thing remains unchanged:
Without the original creative work of real artists, there would be no database – and therefore no AI art.