Could Magnus Resch’s AI App Expose the Art Market’s Transparency Problem?

The lack of transparency in the art industry, especially in terms of pricing and final transactions, has been cited by many as an important factor preventing the market from growing its collectors and reaching the new buyers it needs to continue its rapid growth in the world. Several apps and startups have tried to tackle this problem, but none have succeeded in democratizing the industry that has become a virtual lifestyle while still operating at a level of secrecy and exclusivity.

Art market economist and entrepreneur Magnus Resch builds an entire body of work on the blind spot of the art market, writing extensively about the systems that determine art success, gallery sustainability and collector behavior. His latest venture is renovating and re-releasing an app called Magnus, which he calls the “Shazam of art.” Launched in 2013 as a regularly updated guide to art world events, the app is offline during the COVID-19 pandemic when museums and galleries close their doors. Resch recently launched a new AI-powered version, currently in beta, built on the original foundation with image recognition and a large database of art values. Take a picture of a work of art and you’ll find, in seconds, information about the artist, the subject and—most importantly—the price.

“The art market doesn’t have an attention problem. It has a conversion problem,” Resch told the Observer. “People visit art galleries and shows, but many don’t buy because they don’t feel they have enough information. You see a younger generation who are interested in art but are not sure how and when to buy, not only because prices are invisible and transaction costs are high, but also because the buying process can feel intimidating and exclusive.

The research leading to the redesign of his eponymous app confirmed how diverse knowledge in the industry is but also shed light on how value is created. He said there was a lot of boots-on-the-ground gruntwork involved. For more than 15 years, he and his team have been visiting galleries around the world to collect values ​​in person. “That’s data that’s not accessible anywhere else. We’ve put together over 50 years of auction results,” he added, asserting that the app gives users access to “the world’s most extensive database of art prices,” with millions of gallery prices paired with secondary market sales data.

“We cleaned it up [the data]duplicates are linked together and form a unique identifier for every work of art,” explains Resch. On most databases, if a work is sold twice, you see two entries; Magnus shows the complete history of that work of art, including where it was shown, when it appeared at auction, sale prices and whether it was previously offered by a gallery. Context, in this sense, is what makes Magnus and the app different from the content of the data: it represents Magnus the artist, where the work is displayed, the museum owns it, how comparable works are made and how momentum develops over time.”

As for why Magnus is being brought back now, recent advances in AI have greatly improved the speed and accuracy of image matching. Art ID’ing is easy when someone is looking at a famous painting or sculpture, but it is more difficult in the art market, where works may be duplicated, different, underwritten or similar to other works by the same artist. Artists also influence each other and may have similar visual languages, Resch noted. “Training a model with a thousand works by Basquiat does not mean that it can recognize a thousand and one. It must also distinguish it from thousands of similar works by other artists.”

Another challenge was how to track identities, as there is no universal identifier for works of art comparable to ISBNs for books. “We had to build that ourselves,” Resch said, but once he and his team had a database of millions of uniquely identified artworks, Magnus’s matching accuracy improved significantly. “Google Image Search, ChatGPT or Claude can identify the name of the artist, but they never give you a price.

Discussions about the impact of AI on the art world often focus on image production and writing questions, but Resch sees artificial intelligence as the key to reaching market transparency. He maintains that it is a business plan, not a creator. “As we have shown in our Science study, an artist’s success depends less on the work of art itself than on reputation, visibility and professional networks. AI may produce beautiful images, but it cannot replace the human relationships that create cultural and economic value.”

Except, perhaps, the relationship between the collector and the mentor. “Magnus learns what users like and recommends artwork based on their preferences, budget and location,” continued Resch. (If someone is constantly scanning affordable green abstract paintings, an app can recommend similar green works to nearby galleries or anywhere else in the world.) “No human advisor can continuously monitor the entire art market. AI can. That’s using AI at its very best. It gives people access to information and discovery tools that used to be available only to insiders.”

Ultimately, what the AI ​​version of Magnus provides is knowledge; what people do with that information is up to them. More informed consumers, Resch admitted, can be more skeptical. “I think that’s healthy. Transparency doesn’t weaken the art market. It grows it,” he said. “More people will buy art if they understand what they’re looking at and feel like they’re participating in an open system rather than a closed one. The art market doesn’t need more visitors. It needs more buyers. Transparency is how we get there.”

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