Yayoi Kusama Tops 2023 List of 21st-Century Artists

Artworks by Yayoi Kusama collectively sold for nearly US$81 million last year at the major global auction houses, making her the top-selling 21st-century contemporary artist, according to the Hiscox Artist Top 100 report.

The boost in sales for Kusama’s works pushed David Hockney, the previous year’s top-selling artist, to second place. Hockney’s art garnered US$50.3 million in sales last year, down from US$74.7 million in 2022, said Hiscox, a London-based specialty insurer.

The second annual ranking, compiled with research and analysis from London-based ArtTactic, also showed Kusama’s No. 1 ranking was consistent with a strong showing by women artists overall last year. Joining Kusama among the top five last year was Cecily Brown, who ranked fourth with US$31.7 million in sales.

Yoshitomo Nara, ranked third with sales of US$36 million and George Condo ranked fifth with sales of US$29.5 million.

Total sales of contemporary art made after the year 2000 fell 17% to US$955 million last year from US$1.5 billion in 2022, according to the report. Though sales of contemporary art by women fell 8% to US$306 million, the number of works sold rose 21%. And sales by their male peers fell a much sharper 20%, the report said.

“The market for female artists has been much more resilient than that for male artists,” the report said.

The results go beyond ultra-contemporary art. Earlier this year, ArtTactic reported that overall sales of art by women at the major auction houses hit a record US$825.8 million last year, up 7% from a year earlier.

Another mark of progress: Art by women comprised 32% of 21st-century art auction sales last year, up from 29% in 2022, as the number of women artists behind these sales continued to climb. There were 728 women artists represented last year, up 179% from 2019, the report said.

“Contemporary female artists have always been undervalued and underrepresented,” Robert Read , head of art and private clients at Hiscox said in a news release. “Meaningful progress has been made in recent years, as the market gradually begins to recognise the importance and value of their work, but we are still some way from parity.”

Following Kusama and Brown, the top female artists by sales value were Julie Mehretu, with sales of US$21.4 million; Jadé Fadojutimi, with sales of US$8.5 million; and Jenny Saville, with sales of US$7.8 million.

The Hiscox report just examined the auction market for works created in the 21st century and sold at Christie’s, Phillips, and Sotheby’s. This segment was stronger than much of the art market last year, with sales still 26% above pre-pandemic levels. Sales of art made before 2000 have fallen 22% since 2019, the report said.

This segment of the market is also making up a larger share of all post-war and contemporary art sold at auctions, reaching 70% last year from 63% a year earlier.

The Hiscox report was consistent with other analyses of the art market last year that found large-ticket sales, over US$1 million, declined in favor of sales of works with price tags of US$50,000 or less.

Within the 21st-century art category, the number of lower-priced works sold gained 25% while the number sold above US$1 million fell by 12%. The trend is backed by a near doubling in the number of artists making 21st-century works that end up at auction since 2019, the report said.

The benefits of so-called flipping—or the practice of selling art made by young artists within two years of their creation—fell dramatically, bringing in US$39 million in sales last year from US$67 million in 2022. That’s despite the number of lots with this newly made art at 662 was about the same as the previous year.

Though Kusama is 95 years old, 41% of those making 21st-century art are under age 45, unsurprisingly. Leading this group of younger artists last year was: Nicolas Party, whose works sold for US$20.2 million; the late Matthew Wong, whose works sold for US$16.5 million; Fadojutimi; Caroline Walker, whose works sold for US$7.5 million; and Dmitri Cherniak, whose works sold for US$6.7 million.

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