The Rich Got a Bit Poorer Last Year

The wealthy took a big hit last year.

The global population of billionaires sank for the first time since 2018, dropping 3.5% to 3,194, while their wealth declined by 5.5% to US$11 trillion, London-based Altrata, a data firm focused on the rich, reported in its annual Billionaire Census earlier this week.

The drop in wealth was the second-largest fall in the last decade, although Altrata noted that it only partially offset a double-digit jump in billionaire wealth in 2021. The company’s report draws from data collected by its Wealth-X unit.

Zooming out, the global population of those with US$1 million or more in assets fell by 3.3% to 21.7 million individuals, while their wealth sank by 3.6% to US$83 trillion, Paris-based Capgemini, an information technology and services consulting company, said in its annual World Wealth Report released on Thursday. The drops are the biggest in 10 years, Capgemini said.

The population of the ultra-rich, those with at least US$30 million in assets, fell the most, sinking 4.6% last year after a 9.6% surge in 2021, the company said. The wealth of this group of 210,000 individuals fell by 3.7% last year.

Altrata noted that billionaires represent just 0.8% of those with at least $30 million or more in net worth, yet they have a 24% share of this group’s total wealth.

Both Altrata and Capgemini credit slumping economies, falling stock markets, rising interest rates, and geopolitical tensions as contributing to the declines. The reports also both noted that many of the world’s richest responded by turning to wealth preservation strategies.

Among billionaires, this had mixed results, Altrata said. Those who made their money in technology, healthcare, and real estate lost more than 5% of their wealth last year, while those whose wealth accumulated through aerospace and defense, construction and engineering, and food and beverage, saw their fortunes rise, the company said.

According to Capgemini, two-thirds of those with US$1 million or more turned to wealth preservation by cutting their stock holdings by nearly six percentage points to 23% of their total portfolios and boosting their cash and cash-equivalent holdings by almost 10 percentage points to 34% as of January this year.

While global and domestic economies, capital markets, and currency movements affect all the rich, Altrata noted that gains or losses are also due to individual strategies for business and investments, wealth planning, taxes, and philanthropy.

“No billionaire’s asset structure is the same as another’s, and the impact on their wealth will be different for each person,” the report said.

The Billionaire Census also reported that the richest of all, those with US$50 billion or more, lost 23.2% of their wealth, while those at the bottom of the pyramid, with US$1 billion to US$2 billion in assets (representing just over half of all billionaires), lost 3.2%.

Most billionaires, 955, live in the U.S., although the population dropped by 2.1% last year. There are 357 billionaires in China, down by 10.8% and 173 in Germany, down by 1.7%. The only population gains reported last year were in Singapore, which now has 54 billionaires, up by four; and in Moscow, which has 76 billionaires, up by one.

The average age of the world’s billionaires is 67, with those under 50 accounting for just 10% of the total, Altrata said. There are more female billionaires under 50 than over, although they comprise just under one-fifth of the under-50 group.

While the population of rich individuals, and their total wealth, dropped in Europe, Asia Pacific, and North America last year, both the population of the rich and their wealth rose in Africa, Latin America, and the Middle East, Capgemini said.

The number of rich in Latin America rose by 4.7% as their wealth increased by 2.1%; Africa’s rich gained 4.3% new members who combined wealth increased by 1.6%, while the Middle East’s rich gained 2.8% new members as their wealth rose by 1.5%, Capgemini said.

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