Picasso, Monet, Warhol, Basquiat, and Richter Lead Artists Powering the US$1 Million-Plus Market

Pablo Picasso, Claude Monet, Andy Warhol, Jean-Michel Basquiat, and Gerhard Richter top a list of 50 artists leading the momentum for works valued at US$1 million or more, according to a report released Tuesday by Sotheby’s and ArtTactic, a London art market analysis firm.

The list ranked artists with an average of five artworks of US$1 million or more that sold each year between 2018 and 2022 at Christie’s, Phillips, and Sotheby’s—a methodology aimed at showing consistency. The analysis also considers sales value, liquidity, average prices, bidder confidence, and market momentum for each artist, and draws on Sotheby’s internal data on bidders and private sales.

Works by the top five artists alone made up more than a third of all US$1 million-plus sales at these top global auction houses in those years, the report said.

Shifts may be afoot, however. A “Power Rank” of top artists in the US$1 million-plus category, based on data from July 2022 to June 2023, “aims to identify artists whose markets show signs of growing momentum and interest,” the report said.

The top artists of this 12-month Power Rank are Jasper Johns, Lucian Freud, Paul Gaugin, Wassily Kandinksy, and Willem de Kooning.

“The Artists Who Power the $1 Million+ Market” is the second report by Sotheby’s and ArtTactic to explore this segment of the auction world, which proved to be “especially resilient” in 2021 and 2022, during the height of the pandemic and the beginning of the war in Ukraine. Despite representing a “small fraction” of works sold at auction, art that fetches at least US$1 million has “a tremendous impact on the market at lower levels,” the report said.

The analysis considers auction results at Christie’s, Phillips, and Sotheby’s in four categories: contemporary (including Post-War), impressionist and modern, Old Masters, and Chinese works of art. The list of top 50 artists from 2018 to 2022 who are powering the US$1 million-plus sector also includes insights from Sotheby’s private sales and its bidding activity data. Though the latter information is from Sotheby’s alone, similar activity is likely taking place at other auction houses, the report said.

“We all know that the art market has never been as transparent as the financial markets, so any information we can give our clients in terms of trends, analysis, and insight will allow them to make more thoughtful and educated decisions about their purchases, whether they see them as an investment or are pursuing a passion,” Mari-Claudia Jiménez, Sotheby’s head of global business development, said during a roundtable discussion with her colleagues and ArtTactic CEO Anders Petterson that’s included in the report.

The rare insight into private-sale data revealed that works by Alberto Giacometti, in addition to Monet, Basquiat, Picasso and Warhol, made up nearly 80% of Sotheby’s private transactions in the first half of this year. From 2019 to the first half of 2023, these same artists represented only 44.7% of private sales.

Sotheby’s internal bidding data—also rare to see—shows a rise in bidding for works with estimates between US$20 million and US$50 million in the first half of this year. “Despite market uncertainty,” this lofty segment has attracted 6.1% of bidders in the market for works valued at US$1 million or more, up from 3.8% in 2022, the report said.

Nearly 75% of Sotheby’s bidders raised their paddles for works priced between US$1 million and US$5 million from 2018 to 2022, though the percentage slipped to 72.4% in the first half of the year as 13.8% of collectors bid on works valued between US$5 million and US$10 million (up from 12.5% in 2022).

ArtTactic dug deeper into this internal bidding data to understand what category of works these collectors favoured, where they live, and how old they are. The data “provides collectors with additional context to understand some of the drivers behind emerging trends,” the report said.

Among its findings: Contemporary art was favoured by 56.1% of bidders; North Americans bid the most, representing nearly 36.4% of those vying for works of US$1 million or more; and Generation X is making their mark, accounting for the largest share of bidders in the market at 40.2%.

This generational shift is significant. Younger collectors are more comfortable buying across art categories, from Old Masters to Contemporary, for instance.

“The data in the report shows that our collectors, even the youngest ones, are interested in the entire span of history,” Brooke Lampley, Sotheby’s head of global fine art, said during the roundtable. “Education is such an important factor in the art market, and people are learning about art history in many different ways today.”

These younger collectors are interested in art in part because they are more exposed to it than previous generations, Lampley said. Private collectors today are exposed through the numerous art fairs they attend in addition to public auctions, which generations ago were attended more by dealers and others in the trade who then sold the works, she said.

“There has been a great effort to make people feel included in the art world and to make it accessible, both by galleries and auction houses,” Lampley said.

Notably, there are no women artists among the top five of the list of 50 powering the US$1 million-plus market, although four made the larger list. Joan Mitchell ranks No. 17, Yayoi Kusama ranks No. 19, Cecily Brown ranks No. 39, and Helen Frankenthaler ranks No. 47.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion