The Rise of AI Artists: Trends & Key Innovators to Know
1. The State of Play: What’s New in AI Art in 2025
Data as medium: Artists are treating data (climate, city sensors, archives) as raw material, turning abstract inputs into immersive visual forms.
Hybrid workflows: More creators mix AI + hand finishing, code + analogue, or physical installations layered with generative visuals.
Ethics, rights, and authorship: Concerns about models scraping artist work, copyright debates, transparency and ownership are more urgent than ever.
AI in galleries & public art: More institutions are commissioning AI projects, integrating them into exhibitions or immersive shows.
Better tools for non-experts: Interfaces, plugins, and platforms are making it easier for newcomers to experiment without needing to code.
2. Key AI Artists to Watch / Follow
Here are several standout artists doing compelling work in AI / generative art:
Refik Anadol — Pioneer of data-driven art and immersive installations. His “data paintings” transform architecture into living, breathing light sculptures.
Mario Klingemann — One of the earliest neural network artists. Known for Memories of Passerby I, the first AI artwork sold at Sotheby’s.
Sofia Crespo — Explores “speculative biology” through AI, creating dreamlike creatures and ecosystems that blend nature with neural networks.
Niceaunties — Uses AI to celebrate “auntie culture,” blending domestic surrealism, identity, and generational storytelling.
Emi Kusano — Japanese artist and musician merging AI, retro-futurism, and fashion; known for collaborations with Gucci and cutting-edge NFT projects.
Sougwen Chung — Blurs the line between human and machine co-creation, using robotic arms and AI systems as collaborators in her painting practice.
Ahmed Elgammal — Founder of AICAN, an autonomous creative system that produces original fine art without human prompts.
These artists are pushing different edges: data, biology, identity, social commentary. They each show how AI art can be more than novelty.
I would then also seriously recommend some of the digitalist artists that we worked alongside at the British Art Fair, including Ricardo, David Sheldrick, Fredrik Jonsson, Julien Durand and Mr Relative. As well as our own Lula B, Lula Julian and Darien Davis.
3. What to Learn from Their Work
Narrative + constraint: Great AI art isn’t just outputting wild images, it’s choosing constraints, prompt design, curatorial decisions.
Layering human + machine: Many of these artists don’t let AI do “all the work.” They intervene, refine, contextualise.
Concept over spectacle: The strongest works use AI to say something, about identity, memory, ecology, society, not just to “look cool.”
Join conversations: Follow their interviews, essays, talks, open source releases. Many share process, code, or prompt strategies.
4. How to Get Your Hands Dirty (If You’re Learning)
Start with tools like Midjourney, Stable Diffusion, RunwayML, etc.
Reverse engineer prompts from work you like.
Try combining AI output with manual edits, collage, layering, physical media.
Participate in challenges, residencies, or open calls in AI art communities.
Read debates on ethics, copyright, training datasets to stay informed (not just aesthetic).
5. Where AI Art Might Head Next
More cross modal art (sound + visuals + motion) designed by AI + humans working in tandem.
Adaptive / real-time art that reacts to environmental data or audience.
Tools that protect creators from style mimicking or unlicensed dataset scraping. (E.g. work like Glaze aiming to shield artists’ styles).
More regulatory / legal clarity about AI-output ownership and how platforms credit original creators.