Americans in Their Prime Are Flooding Into the Job Market

The core of the American labour force is back.

Americans between 25 and 54 years of age are either employed or looking for jobs at rates not seen in two decades, a trend helping to counter the exodus of older baby boomers from the workforce. Economists define that age range as in their prime working years—when most Americans are done with their formal education, aren’t ready to retire and tend to be most attached to the labor force.

In the first months of the pandemic, nearly four million prime-age workers left the labor market, pushing participation in early 2020 to the lowest level since 1983—before women had become as much of a force in the workplace. Prime-age workers now exceed pre pandemic levels by almost 2.2 million.

That growth is taking a little heat out of the job market and could help the Federal Reserve’s efforts to tamp down inflation by keeping wage growth in check.

Women lead the way

The resurgence of mid career workers is driven by women taking jobs.

The labor-force participation rate for prime-age women was the highest on record, 77.8% in June. That is well up from 73.5% in April 2020.

Men, however, tend to be employed at higher rates. The overall prime-age participation rate rose in June to 83.5%, the highest since 2002.

The big draw: a tight labor market. The unemployment rate has hovered near a half-century low for more than a year, and job openings outnumber the ranks of unemployed. Employers can’t be as choosy or selective, William Rodgers, vice president and director of the Institute for Economic Equity at the St. Louis Fed, said earlier this month.

Employers “are more apt to be willing to work with candidates—in this case it’s working with moms, or parents in general,” he said. “Tight labor markets can help to punish those who discriminate in hiring and compensation.”

Other factors are also at play. Women aren’t having as many children—there were about 3.66 million births in 2022, 655,000 fewer than the peak in 2007—so child-care responsibilities have decreased.

Julia Pollak, chief economist at ZipRecruiter, said it is possible for women’s participation to rise further if employers adopt or the government requires additional family-friendly policies. U.S. female participation lags behind that of other industrialised economies in part because of the cost of child care, which is subsidised elsewhere.

Rising wages lure workers, counter demographic shifts

Employers raised wages, offered employees more flexibility and improved benefits in recent years.

Average wage gains remain elevated this year and have recently surpassed inflation. And Americans are logging more hours of work from home than they did before the pandemic.

Employer recruitment efforts helped offset some broader demographic shifts, including an ageing population and rise in retirements.

The share of the population age 55 and over in the labor force climbed steadily from the mid-1990s through the 2008 financial crisis and remained elevated for more than a decade. The Covid-19 pandemic pushed many out of the workforce, and some older workers haven’t returned, particularly those over 65.

Much of the decline in the overall participation rate was anticipated as baby boomers aged out of the workforce, but the rise in prime-age workers meant the drop wasn’t as steep.

The Congressional Budget Office in January 2020, just before the pandemic hit, forecast the overall participation rate to deteriorate steadily through the 2020s, moving down to 62.4% in the second quarter of this year.

Instead, the rate was a couple of ticks higher in June at 62.6%, supported by prime-age workers.

“It seems like there is almost no cap on the supply of workers, only a speed limit on how fast we can bring them in,” Pollak said, referring to both rising prime-age participation and an influx of immigrants into the workforce.

Trends could turn if the economy cools

There are concerns that the Fed’s campaign to bring down inflation through higher interest rates will cause unemployment to rise too much and push some of the most vulnerable workers back to the sidelines.

The median forecast among Fed officials shows the unemployment rate rising to 4.1% by the end of this year and 4.5% next year from 3.6% in June, suggesting the economy will shed tens of thousands of jobs.

Labor-force participation tends to be cyclical, rising when the economy is strong and falling during downturns. A weaker labor market combined with structural barriers to employment could cap further gains.

With “current strength of labor demand set to fade, further progress from here will probably be more gradual,” Andrew Hunter, deputy chief U.S. economist at Capital Economics, said in a research note.

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