Ultra-Contemporary Art Falls Flat at London Sales
4 min
Art by young contemporary artists performed well at auctions in London this week, but few flew off the auction blocks in a frenzy as had been the case through early last year.
That led the total value of evening sales of works by artists under the age of 45 to sink 80% from a year ago to £1.9 million (US$2.41 million), according to the London art analysis firm ArtTactic. The total value of young contemporary art sold at evening auctions this week was also 63% lower than at the London evening auctions in February, which itself represented a 25% drop in value from a year earlier.
An uncertain global economy, high inflation, and persistent geopolitical conflicts, combined with the fact these sales come at the tail end of a brisk season of art buying at both auctions and fairs, likely all contributed. Also, the evening sale totals this June didn’t include Phillips, which opted to only offer a day sale.
At least a quarter of Phillips “20th Century to Now” auction on Friday of more than 100 works were by ultra-contemporary artists, a category the auction house has long led. But four lots on the block failed to find buyers, including paintings by Shara Hughes and Harold Ancart. With only a few exceptions, most others sold within presale estimates.
A standout was the very last lot of the sale: Belgian artist Albert Willem’s All in All Not Bad For His First Attempt, 2021, depicting an airplane with plumes of black smoke that landed in the middle of a city intersection, sold for £180,000, before fees, several multiples of a £15,000 high estimate.
All-in-all, Phillips’ auction realised only £7.15 million, before fees, below a presale estimate range between £8.6 million and £12.3 million, according to ArtTactic. With fees, the sales brought in £9.1 million, with 84% of lots sold, Phillips said.
Overall evening sale results at Christie’s and Sotheby’s declined 22.1% from a year ago to nearly £219 million, before fees, with only five lots selling for more than £5 million, including Gustav Klimt’s Lady with a Fanfor a record price of US$108 million at Sotheby’s on Tuesday.
One reason ultra-contemporary works didn’t spark lofty bidding at this week’s sales is that many of the works weren’t the best examples from these artists, says Morgan Long, managing director of the Fine Art Group, a London art advisory.
According to Long, galleries have been cracking down on “flipping,” that is, buying works on the primary market and selling them soon afterward via the auction houses. The result: “You’re not getting access to and putting into auction really great primary material,” she says.
And, Long says, “most people who want good primary [works], have access” to them. A buyer who wants to see great works by Caroline Walker—a popular Scottish contemporary artist—can find high-quality examples at her gallery, Stephen Friedman in London. Lesser quality examples head to auction, she says.
There were three works by Walker sold at Phillips, including Reception, 2013, which sold for a price before fees of £140,000, below expectations.
Buyer hype for younger contemporary artists also cycles in and out of fashion. In May 2022, works by Anna Weyant led three evening sales in New York. This spring, sightings of Weyant works were scarce. Cloud Hill, a 2020 portrait by the artist sold for £225,000, before fees, at Phillips, below a £250,000 low estimate.
Currently, artists such as Michaela Yearwood-Dan, Julien Nguyen, and Sahara Longe are gaining more attention. “There are all these new ones that have cropped up in between the old guard of the young and the new guard of the young,” says Naomi Baigell, managing director at TPC Art Finance in New York.
Buyers, Baigell says, “are probably looking to see what they can get that doesn’t fly out of the saleroom. And because we’re still in this political and financial environment, the eye is much more discerning when they’re thinking of acquisitions.”
And, she says, collectors “want to start with artists that are going to increase in value, not ones that have increased in value.”
The price points for most works by young contemporary artists often fit the bill. During the London evening sales tracked by ArtTactic, three of the top five performing works were by young contemporary artists Louis Fratino, Yearwood-Dan, and Guglielmo Castelli. The top-selling young artists were Walker, Amoako Boafo, Fratino, Ahmed Mater, and Yearwood-Dan.
But newer collectors to the market are also drawn to newer works and to the access to the art world buying these pieces can provide. Since the start of the pandemic, these combined factors have drawn in a wider group of newer, often younger collectors in addition to seasoned buyers, Baigell says. That’s a far broader swath of individuals than those able to buy a Klimt for US$108.4 million.
Galleries are responding to this trend by seeking out and bringing in younger artists. For all these reasons, Baigell believes the ultra-contemporary art segment will continue to thrive and drive interest in the market.
“We’re going to be seeing a lot more of this 21st-century [art] be what is exciting to watch at auction,” she says.
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From making unpopular decisions to learning when to listen, leaders from five businesses reveal what nobody prepared them for — and how running a company has challenged their expectations.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA 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
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
All three vehicles will form part of a broader charitable initiative benefiting Big Brothers Big Sisters of America, the American Red Cross and Starlight Children’s Foundation
