Masterworks Research · Thematic Research | Fine Art Market Strategy
1. Introduction
What does artificial intelligence change about scarcity? On the supply side, AI is slashing the cost of producing goods and services, so the value of anything that can be mass-produced falls, and the few things that cannot, including the singular, authenticated, human-made artwork, are worth more by comparison. On the demand side, the AI boom is minting a new generation of large fortunes, and new wealth has historically flowed into a tight supply of blue-chip art.
2. Two kinds of scarce assets
When Goldman Sachs published The HALO Effect this past March, most investors responded with thoughts about silicon and oil.¹ However, there are really two different types of scarce assets, and it helps to separate them. The first is scarce inputs: staying with AI as an example, this would include the chips, copper, power, and land that AI consumes as it grows. These can rise in value, but they do so because they are used in production, and their prices turn on industrial demand. The second is positional, or Veblen, goods: things valued precisely because they are owned and scarce, from a Birkin to a blue-chip painting. Their value comes not from being consumed but from being held and from the fact that others cannot easily have them. This note is about the second kind. Our argument is that AI acts on it through two forces, which the next sections take in turn.
3. Force 1: AI generates wealth
The same boom that is competing away the profit in production is creating private fortunes at a pace with few precedents. According to Crunchbase, global venture funding reached about $300 billion in the first quarter of 2026, roughly 80% of it going to AI, the largest venture quarter on record and up more than 150% from a year earlier; four of the five biggest funding rounds in history closed in that quarter alone.² Gartner expects worldwide AI spending to reach about $2.5 trillion in 2026.³ These figures are founder stakes and early-employee payouts, which is to say the raw material of prospective collectors.
That wealth reaches the art market on a delay. Technology fortunes have historically taken a decade or more to turn into serious collections, as an earlier software generation did before it came to shape the contemporary market. The AI cycle looks similar, with larger fortunes and possibly a shorter lag, and events like the anticipated SpaceX listing would convert paper wealth into cash that can be spent. When it arrives, it may meet a supply of blue-chip work that cannot immediately grow to greet it, which is the condition under which prices rise.
A software product that once earned a high multiple because it was hard to build can be rebuilt in a weekend by a few engineers and an AI agent, and the profit that used to reward building it is competed away.
4. Force 2: AI shifts desire toward luxury goods
As people grow wealthier, they have tended to spend a rising share on goods prized for scarcity and status, the pattern economists associate with luxury and positional goods; a larger population of the wealthy competes for a roughly fixed set of trophy assets, and that competition tends to push prices up long-term. A second effect may reinforce the first. As AI makes ordinary output abundant and hard to tell apart, evidence of the human hand may become part of what buyers are paying for, much as "handmade" and "organic" came to carry a premium once machine-made and mass-farmed became the default. We would not overstate either effect, but both point in the same direction: toward the things AI did not produce.
5. Why blue-chip art embodies this kind of scarce asset
Why should a painting that a poster reproduces for thirty dollars, and that an AI now renders for free, sell for millions? Because a blue-chip work's price has little to do with pure aesthetics. We have conviction the market is paying mostly for validated cultural significance, an artist's place in history settled by critics, museums, and decades of sales, a judgment that takes a long time to form and cannot be manufactured on demand; along with the status a famous work confers and its role as a durable store of wealth. Importantly, supply is limited for those artists no longer producing. However cheap AI makes images, it cannot add one work to the supply of authenticated originals the market actually prices, nor can it manufacture its way in. An AI image "in the style of" an artist is only the newest kind of copy, and copies have never materially threatened originals: a Starry Night print has cost the price of lunch for a century and done nothing to the value of van Gogh. Additionally, since January 2025 the U.S. Copyright Office⁴ and the D.C. Circuit, in Thaler v. Perlmutter, have held that purely AI-generated output cannot be copyrighted.⁵ Something anyone can copy and no one can own cannot be scarce. There may be a further effect at the very top. As wealth widens access to ordinary luxury, the genuinely singular could become more sought after still, and art sits at that extreme, since even a scarce handbag exists in numbers while a given painting exists only once.
6. Implications and conclusion
For us this is a way of underwriting, not a marketing line. If the durable premium goes to work that is singular, physical, made by a person, and well documented, then the task is to find the pieces that best fit that description and buy them with discipline before the wider market re-prices. There is also a point about access. A market for irreplaceable originals has mostly been the preserve of the very wealthy, closed to everyone else by price rather than logic. Masterworks was built to change that, letting investors invest in a fractional stake in the same assets without buying a whole Picasso.
For a long time, value has tended to drain away from whatever became easy to make and to collect in whatever stayed scarce. AI is a powerful engine for making things easy to make, which is part of why it may strengthen the case for owning what it cannot. When a machine can produce almost anything, the things it cannot produce are the ones worth watching.
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Notes and sources
- Goldman Sachs - The HALO Effect: Heavy Assets, Low Obsolescence in the AI Era.
- Crunchbase - Q1 2026 Shatters Venture Funding Records as AI Pushes Startup Investment to $300B.
- Gartner - Worldwide AI Spending Will Total $2.5 Trillion in 2026.
- U.S. Copyright Office - Copyright and Artificial Intelligence, Part 2: Copyrightability.
- CNBC - Thaler v. Perlmutter: appeals court affirms AI-generated art cannot be copyrighted (D.C. Circuit).
