“Artistic intelligence” is quickly becoming a new keyword in European policy discourse. The European Commission increasingly invokes it in conversations around innovation, culture and artificial intelligence. The term signals something important, but what does it actually mean?

At first glance, artistic intelligence may seem like a natural extension of artificial intelligence applied to creative domains. Yet reducing it to a technological capability misses the point entirely. Artistic intelligence is not a property of machines. It is a way of thinking, questioning and navigating complexity, one that places the human, and specifically the artist, at the centre.

The relationship between art and technological disruption is not new. Photography once challenged painting, altering not only artistic techniques but also the very purpose of representation. Digital tools have long reshaped music, design and visual culture. Each time, the question has not been whether technology replaces artistic practice, but how it transforms the conditions under which art is produced.

Artificial intelligence is part of this lineage, but it introduces a qualitative shift. Unlike previous tools, AI systems can process vast amounts of data, identify patterns and generate outputs that appear autonomous. They offer a new way to navigate complexity, particularly in a world increasingly shaped by data, interconnection and uncertainty.

This is why AI matters. Not because it creates, but because it expands the space of possibilities.

What distinguishes AI from earlier technologies is its ability to operate within systems of complexity. It does not simply extend human capacity; it reshapes how problems can be explored. Data, relationships and emergent behaviours can now be approached in ways that were previously inaccessible.

However, this expanded capacity does not diminish the role of the artist. On the contrary, it makes it more critical.

At the centre of any meaningful process remains the artist: the human who formulates the question, applies critical thinking and determines what is worth investigating. This initial act cannot be delegated. It establishes the direction, scope and meaning of the entire process.

The artist is not merely a curator. While curation implies selecting from existing options, the artist operates at a more fundamental level: they construct the conditions under which possibilities emerge. They define the inquiry, structure the process and continuously exercise judgement.

When working with AI, this role becomes even more pronounced. The system may generate outputs, but it does not decide why those outputs matter. Control is not a rigid command over the machine, but an ongoing negotiation between intention and outcome.

If the artist defines the “who” of artistic intelligence, artistic research defines the “how.”

Artistic research is not simply the application of creativity to an existing method. It is the invention of methods themselves. Inquiry unfolds through making, through experimentation, material engagement and iterative processes that shape both the question and its possible answers.

Unlike conventional research, which often relies on predefined frameworks, artistic research operates in conditions where the question is not fully formed at the outset. It evolves through interaction with tools, materials and systems.

Creativity, in this context, is not decorative. It is methodological.

It operates at multiple levels:

• In the formulation of questions, enabling unconventional and open-ended inquiries
• In the construction of methods, where hybrid and evolving strategies replace fixed procedures
• In the engagement with tools, including AI, where unexpected uses generate new insights
• In the interpretation of results, where meaning is constructed from ambiguity

This process also implies a tolerance for uncertainty. Artistic research does not aim for linear problem-solving. It embraces divergence, failure and unpredictability as productive conditions. Creativity becomes the mechanism through which uncertainty is navigated, not eliminated.

If artificial intelligence expands possibilities, and artistic research structures exploration, then artistic intelligence ultimately resides in interpretation.

It is the capacity to read, contextualise and assign meaning to what emerges. Outputs, whether images, systems or behaviours, do not constitute knowledge on their own. They become meaningful only through interpretation.

This interpretative layer is where artistic intelligence fully manifests. It is what transforms data into insight, process into understanding and experimentation into knowledge.

Even when a machine generates an output, it is the artist who recognises significance, amplifies certain directions and filters others. The artist defines what resonates, what matters and what carries meaning within a broader social and cultural context.

From our perspective, artistic intelligence can be understood as the interaction of four elements:

1. The artist (who): the critical agent who formulates and reframes the question
2. Artistic research (how): the evolving set of methods and practices through which inquiry unfolds
3. Artificial intelligence (tool): an enabling mechanism that amplifies possibilities without replacing direction
4. Artistic intelligence (meaning): the interpretative capacity that transforms outputs into knowledge

In this framework, value does not reside solely in what is produced. It lies in how questions are constructed, how processes are designed and how results are understood.

The growing attention to artistic intelligence reflects a broader shift. As societies face increasingly complex challenges, from climate transitions to digital transformations, there is a need for ways of thinking that can engage with uncertainty, ambiguity and interconnected systems.

Artistic intelligence offers such an approach. It does not provide definitive answers, but it enables more meaningful questions. It does not simplify complexity, but creates ways to navigate it.

This is why the artist remains essential. Not as a peripheral figure in technological innovation, but as a central actor in shaping how knowledge is produced, interpreted and shared.

If artificial intelligence changes what can be done, artistic intelligence determines what should be done, and why.