Millennial Women Are Catching Up to Men by Leaps and Bounds When It Comes to Wealth, Report Finds

Millennial women’s wealth is outpacing men’s as a new generation inherits and grows their assets at a wider scale than ever before, according to RBC Wealth Management.

In a survey of roughly 2,000 men and women with at least $1 million in investable assets, millennial women respondents had an average of $4.6 million, compared with $3.8 million for women of all age groups and $4.5 million for all men.

Inheritance is one part of the picture, as baby boomers are expected to transfer $124 trillion to the next generation, but so is the progress millennial women have made in the world of business, investment and lucrative professional careers as they close the gap with men.

“Millennial women are catching up, or have outpaced the males as far as their wealth building,” said Angie O’Leary, head of wealth strategies at RBC. “We know that’s coming from a more diversified set of investments, such as entrepreneurship, real estate and of course, investments [in financial markets].”

Millennial women, now in their 30s and 40s, tend to differ from earlier generations of women more than they do from men in terms of their source of wealth. While investments were the largest driver of wealth across all categories, millennial women cited business ownership, innovation, and executive roles far more than Gen X or boomer women.

More than 60% of millennial women cited business ownership and more than 40% mentioned executive roles, but neither exceeded 22% for either Gen Xers and Boomers. Younger women also grew their fortunes from professional sports or arts 39% of the time, compared with just 6% and 1% for Gen Xers and Boomers, respectively.

In terms of inheritance, the gap between generations was smaller. About 37% of men and 35% of women cited family money as a source of wealth overall, breaking down to 44% of millennials, 30% of Gen X and 33% of boomer women.

With women controlling so much wealth, their spending and investments as a group are evolving and extending into areas previously considered stereotypically male such as real estate, cars and watches, O’Leary said. “Women are starting to look a lot like their male counterparts when it comes to investments, real estate, philanthropy,” she said. “That’s a really interesting emerging female economy.”

In real estate, for example, single women made up 20% of home buyers in 2024 up from 11% in 1981, when the National Association of Realtors began tracking the data. By contrast, single men make up 8% of the market and have never exceeded 10%, according to NAR.

While men and women shared largely similar priorities overall in terms of well-being, relationships, legacy and personal drive, younger generations of women were successively more likely to value drive and personal power, and successively less likely to rank relationships and social bonds—though that could also be a function of age and stage of life.

“This generational shift suggests evolving societal norms and responsibilities, where younger women seek personal achievements, while older cohorts value nurturing connections and community stability, affecting their financial and lifestyle choices,” the report 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