A Conversation With Penelope Sonder, COO Of NALA On How AI Is Quietly Reinventing The Art Industry

Why is discovery becoming the next frontier in AI?

AI has already transformed how content is created, but the next major challenge is how people discover what is meaningful to them. More than 34 million AI-generated images are now created every day globally, making it increasingly difficult for collectors to distinguish original quality and connection from the sheer volume of computer-generated noise.

Discovery is becoming a question of trust. The opportunity for art technology is not in replacing our natural tastes and preferences, but in helping us understand them better. Data-driven platforms like NALA are part of a broader shift toward using behavioural and visual preference data to help collectors discover pieces they genuinely connect with, making it easier to navigate culture with more confidence.

What does an artist-first digital eco-system look like? 

Placing artists first means designing the industry around the needs of creators, not the platforms. Most artists are not represented by galleries so social media is their primary method of visibility and income. The way in which social media rewards visibility, volume, and virality is placing pressure on many artists to become ‘content creators’ first, and artists second.

“The future of art tech will be based around widening access, without sacrificing artistic identity or control. Giving artists more influence over how their work is presented and monetised, helping them build direct relationships with collectors, and reducing dependence on follower counts and social media algorithms are the keys to a successful “artist-first” digital ecosystem.

How are recommendation engines are entering the art market?

In the same way they have shaped music, film, and fashion, recommendation engines are now taking hold in the art world. Netflix estimates that more than 80% of the content watched on its platform is driven by recommendations, showing how heavily digital discovery already relies on personalised algorithms. Buying art is a personal and emotive process, but it can also be intimidating. Knowing which pieces, you respond to the most may be easy to work out but understanding where to find them is a different matter. 

Recommendation technologies, like those that NALA use, help by surfacing works that someone is drawn to, works that fit their unique aesthetic. This does not mean art is going to be reduced to a simple shopping algorithm, though. Matching collectors with work beyond what is trending in established galleries is where recommendation engines can have the biggest role to play.
 

Why might the future of culture become hyper-personalised? 

Increasingly, digital experiences are expected to immediately understand someone’s preferences and our broader culture is moving in this direction too. Research found that 71% of consumers now expect personalised interactions from the platforms they use. Thanks to its highly personal appeal, art is no exception. The same piece that feels transformative to you may leave your friend completely unmoved.

The challenge for the art world is going to be ensuring that hyper-personalisation does not narrow our tastes but broadens them. If a platform simply repeats what someone else of the same demographic likes, the risk is that taste becomes homogenous. Using taste as a starting point and then recommending new perspectives is where technology can be powerful in making culture feel more personal whilst keeping it expansive.

Why are people moving away from social-media-led discovery? 

Social media has been an incredibly powerful tool for visibility, but it was not built with artists, collectors, or cultural discovery in mind. Its tendency to reward speed, engagement, and virality can distort how art is valued. Work with in-depth heritage and long-term significance does not often perform well on an Instagram feed. 

Especially as AI-generated imagery makes our platforms even more crowded, artists need to reconsider if these platforms are still serving them as best they can. Research now suggests people only correctly identify AI-generated imagery around 62% of the time, reinforcing how difficult digital trust and authentic discovery are becoming. Collectors need more than just picture and a caption to fully understand a piece of art; they need context, provenance, and a deeper sense of connection. Artists need an eco-system where they are judged not by follower counts and likes, but by genuine preference.