In the late 2000s and early 2010s, technologies to produce art digitally became increasingly affordable, while new platforms made it possible for creative work to be distributed and discovered online without relying on the traditional gatekeepers of the arts and entertainment industry.
It was the era of bedroom musicians getting discovered after posting songs on MySpace, independent filmmakers building audiences by publishing their work on YouTube and Vimeo, and photographers, illustrators and designers developing their craft while sharing it through Instagram.
Having more democratic access to creative tools did not replace creativity. It expanded who could participate in it. The barriers to creating became dramatically lower, but creating still required skill and knowledge. The tools still had to be mastered. Behind every artist were countless hours spent learning a craft before anyone was paying attention.
Fast forward to 2026, and anyone with a subscription to ChatGPT or another generative AI platform can generate something that resembles a song, an illustration, a screenplay or even a video in a few minutes.
Notice that I said generate, not create.
Because what these tools produce is a mashup of pre-existing creative work used as source material, without proper credit, consent or compensation. They assemble patterns learned from countless artists, writers, musicians and filmmakers into something that resembles an original creation.
The result may be convincing enough for someone scrolling through social media, but it is unlikely to have the same lasting cultural impact as human-made art because it lacks the experience, intention and perspective behind the work.
When art becomes a machine
The debates around whether art must come from traditional methods, individual craftsmanship or years of technical training are not new.
In the 1960s, Pop Art transformed the definition of what could be considered art. Andy Warhol took images from advertising or consumer products and turned them into works displayed in galleries and museums. His paintings of Campbell’s soup cans and celebrity portraits questioned ideas of originality, authorship and mass production.
In 2022, a documentary series for Netflix produced by Ryan Murphy used artificial intelligence to recreate Andy Warhol’s voice, raising new questions about whether technology can reproduce the presence of an artist without the artist themselves.
Warhol embraced repetition, used existing imagery and reproduced work through the mechanical processes available at the time, but he was making a statement about the culture that produced those images.
I don’t think the AI-generated content that floods our feeds today is trying to make any statement.
AI automates creativity
The first generation of digital creative tools expanded access, without eliminating the need to develop creative skills. The tools themselves did not create the ideas. They lowered financial and technical barriers while preserving the need to experiment and, most importantly, have a point of view.
Generative AI represents a different shift. These tools allow users to generate finished-looking work without developing the skills traditionally associated with the creative process.
Generating an image, song or video can now happen without the years of trial and error that usually shape an artist’s voice. The distance between having an idea and producing something that resembles a finished work has become dramatically shorter.
That does mean generative AI produces something that emerge from a process where the software takes over parts of the work that required human practice.
A prompt does not make an artist
AI-generated content is increasingly appearing across the digital platforms where audiences discover art today, often without being clearly labelled as machine-generated.
It rarely represents a breakthrough in artistic expression that deserves more than a few seconds of attention. However, it masters the existing mechanics of online engagement: familiar aesthetics, recognizable formats and content designed to capture attention quickly.
AI-generated content may become increasingly polished, but it lacks the emotional connection that audiences have historically found in art.
Someone can prompt their way toward something that resembles the external qualities of creativity, but the human experience behind artistic choices will always be missing. The result can feel like a soulless imitation of existing work: something without a genuine perspective, personal history or emotion to communicate.
Art is not only about producing something. It is about expressing something that comes from someone experiencing the world.
Who gets the flowers?
If we completely overlook the environmental impacts of generative AI, one could argue that these tools can save time, reduce production costs and allow people without traditional training to experiment with creativity.
Even I had an early draft of this blog post that explored a couple of recent examples of AI-generated content that were difficult to identify as machine-generated and, as a result, gained significant popularity online or even mainstream media attention.
I was going to highlight the teenage boy in his bedroom dreaming of a career as a music producer who had his first viral song through an unofficial World Cup anthem for his country generated with AI, or the unsuccessful actress and filmmaker who generated an AI actress and received the opportunities that her original work never had.
But I won’t.
Because generative AI did not invent painting, photography, illustration, music or filmmaking. Its ability to produce convincing results comes from enormous collections of existing human-made work that it incorporates without giving credit, compensation or recognition to the original creators.
Many artists argue that their images, writing, music and other creative output have been absorbed into commercial AI systems without their knowledge, permission or compensation. For them, the issue is not simply whether AI can be used as a creative tool. It is whether companies should be allowed to build those tools using the work of creators who never agreed to participate.
A person who studies another artist’s work develops their own interpretation, influenced by their experiences, limitations and intentions, creating something referential but new. A commercial AI system designed to automate creative production operates differently: it extracts value from the work of the very people whose careers depend on that production.
We need a thoughtful debate about copyright law, intellectual property and the relationship between technology and creative communities.
The next generation
Every artist was as a beginner. Musicians spend years learning instruments before developing their own sound. Illustrators study techniques before creating a style that feels personal. Filmmakers make unsuccessful projects before learning how to tell meaningful stories.
Those years are not simply preparation for creativity, they are the process through which creativity develops.
Generative AI challenges that relationship by offering a shortcut around many of the stages that traditionally shaped artists.
Someone might ask:
Why spend hundreds of hours learning illustration if software can generate a finished image in seconds? Why study composition if an algorithm can suggest different visual approaches? Why struggle through writing exercises if a chatbot can immediately generate a screenplay, article or poem?
These questions raise concerns about what happens when fewer people develop the skills that previous generations considered fundamental to artistic practice.
If the incentive to develop artistic skills decreases because software can imitate the final result, the consequences may not appear immediately. They may become visible years later, when fewer people have the experience needed to create something genuinely new.
We risk raising a generation with access to instant generation tools that no longer sees value in the difficult process of learning how to create.
You can still experience art
Every major technological shift has been accompanied by predictions that older forms of creativity would disappear. Yet history has repeatedly shown something more complicated. New technologies change culture, but they also create renewed appreciation for experiences that feel distinctly human.
Vinyl records continue to attract listeners despite the convenience of streaming. Film photography has found new audiences among people who grew up with smartphone cameras. Independent bookstores continue to survive alongside digital publishing. Live concerts remain powerful experiences despite the fact that almost any performance can now be recorded and shared online.
These experiences preserve something technology struggles to reproduce: presence.
A live performance can contain mistakes. A photographer can miss the perfect moment. A singer’s voice can break during an emotional song. Those imperfections are not flaws. They are evidence that another human was there, making art in real time.
As digital culture becomes increasingly polished and automated, traces of human involvement may become more meaningful.
Audiences should value not only the final result, but also the knowledge that another person spent time, effort and experience creating and performing it.
Artists against AI
The internet’s greatest creative achievement was not replacing professional artists. It was allowing millions of new ones to emerge.
People who never had access to recording studios, publishing companies or traditional media institutions could finally share their work. That expansion was one of the most significant cultural changes of the digital era.
Generative AI represents a different possibility: producing the appearance of creative work without the same investment in learning the craft.
Artists have always adopted new tools, from photography to digital editing software to streaming platforms.
Creativity has never depended on preserving old methods.
But generative AI is the first widely adopted technology built around replacing parts of the creative process itself while relying on a vast collection of existing human work. It does not only give more people access to artistic tools. It challenges the value of the human effort that made those tools possible.
The internet made it possible for more people to become artists.
But will we continue valuing the people who spend years working on their craft to become great in their field? I hope so.
Oriol Salvador 