The U.S. Now Has More Billionaires Than China. Musk Is Still Tops.
The U.S. now has more billionaires than China for the first time in a decade, driven by AI and a booming stock market.
3 min
The number of U.S. billionaires in the world reached 870 in mid-January, outpacing the number in China for the first time in 10 years, according to a snapshot of the wealthiest in the world by the Hurun Report.
The U.S. gained 70 billionaires since last year, powered by a rising stock market, a strong dollar, and the insatiable appetite for all things AI, according to the 14th annual Hurun Global Rich List . China gained nine billionaires overall for a total of 823. Hurun is a China-based research, media, and investment group.
“It’s been a good year for AI, money managers, entertainment, and crypto,” Rupert Hoogewerf, chairman and chief researcher of the Hurun Report, said in a news release. “It’s been a tough year for luxury, telecommunications, and real estate in China.”
Overall, the Hurun list—which reflects a snapshot of global wealth based on calculations made Jan. 15—counted 3,442 billionaires in the world, up 5%, or 163, from a year ago. Their total wealth rose 13% to just under $17 trillion.
In November, New York research firm Altrata reported that the billionaire population rose 4% in 2023 to 3,323 individuals and their wealth rose 9% to $12.1 trillion.
Elon Musk, CEO of electric-car maker Tesla and right-hand advisor to President Donald Trump, topped the list for the fourth time in five years, with recorded wealth of $420 billion as of mid-January as Tesla stock soared in the aftermath of the U.S. election, according to Hurun’s calculations.
The firm noted that Musk’s wealth has since nosedived about $100 billion, falling along with shares of Tesla although the EV car maker is benefiting on Thursday from Trump’s 25% tariff on cars made outside the U.S.
According to the Bloomberg Billionaires Index, Musk’s wealth stood at about $336 billion as of the market’s close on Wednesday, although measuring his exact wealth —including stakes in his privately held companies and the undiscounted value of his Tesla shares—is difficult to precisely determine.
The overall list this year contained 387 new billionaires, while 177 dropped off the list—more than 80 of which were from China, Hurun said. “China’s economy is continuing to restructure, with the drop-offs coming from a weeding out of healthcare and new energy and traditional manufacturing, as well as real estate,” Hoogewerf said in the release.
Among those who wealth sank was Colin Huang, the founder of PDD Holdings —the parent company of e-commerce platforms Temu and Pinduoduo—who lost $17 billion.
Also, Zhong Shanshan, the founder and chair of the Nongfu Spring beverage company and the majority owner of Beijing Wantai Biological Pharmacy Enterprise , lost $8 billion from “intensifying competition” in the market for bottled water. The loss knocked Zhong from his top rank in China, which is now held by Zhang Yiming founder of Tik-Tok owner Bytedance. Zhang is ranked No. 22 overall.
Hurun’s top 10 billionaires is a familiar group of largely U.S. individuals including Jeff Bezos, Mark Zuckerberg, and Larry Ellison. The list has France’s LVMH CEO Bernard Arnault in seventh place, three notches down from his fourth ranked spot on the Bloomberg list, reflecting a slump in luxury products last year.
Nvidia CEO Jensen Huang is ranked No. 11 on Hurun’s list as his wealth nearly tripled to $128 billion through Jan. 15. Other AI billionaires found lower down on the list include Liang Wenfeng, 40, founder and CEO of DeepSeek, with wealth of $4.5 billion and Sam Altman, CEO of OpenAI, with $1.8 billion.
Also making the list were musicians Jay-Z ($2.7 billion), Rihanna ($1.7 billion), Taylor Swift ($1.6 billion), and Paul McCartney ($1 billion). Sports stars included Michael Jordan ($3.3 billion), Tiger Woods ($1.7 billion), Floyd Mayweather ($1.3 billion), and LeBron James ($1.3 billion).
Wealth continues to surge across the globe, but Hoogewerf noted those amassing it aren’t overly generous.
“We only managed to find three individuals in the past year who donated more than $1 billion,” he said. Warren Buffet gave $5.3 billion, mainly to the Bill and Melinda Gates Foundation, while Michael Bloomberg —ranked No. 19 with wealth of $92 billion—gave $3.7 billion to various causes. Netflix founder Reed Hastings, ranked No. 474 with wealth of $6.2 billion, donated $1.1 billion.
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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
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