The Sandwich Generation Is Stressed Out, Low on Money and Short on Time

At 34, Kait Giordano is juggling her job, a newborn and two parents with dementia.

Just over a month into motherhood, she tends to her infant son and her live-in parents in the morning and afternoon, some days with the help of a rotating cast of paid companions at their Tucker, Ga., home. In the evenings, her husband, Tamrin, takes over while she colours hair.

They had already delayed starting a family when Kait’s father moved in a few years ago. Her mother moved in this year. “We chose to take this on,” she says. “We didn’t want to wait any longer.”

More Americans shoulder a double load of caring for their children and at least one adult , often a parent. The “sandwich generation” has grown to at least 11 million in the U.S., according to one estimate, and shifts in demographics, costs and work are making it a longer and tougher slog.

People are having children later, and they are living longer , often with care-intensive conditions such as dementia. That means many are taking care of elderly parents when their own kids are still young and require more intensive parenting—and for longer stretches of their lives than previous generations of sandwiched caregivers.

As the oldest millennials start to hit middle age —and baby boomers near their 80s—the number of Americans caring for older and younger family makes up a significant part of the electorate. Vice President Kamala Harris invoked the sandwich generation when she recently proposed expanding Medicare benefits to cover home healthcare.

“There are so many people in our country who are right in the middle,” the Democratic presidential candidate said on ABC’s “The View” this month. “It’s just almost impossible to do it all, especially if they work.”

Responding to the Harris proposal, former President Donald Trump ’s campaign said he would give priority to home-care benefits by shifting resources to at-home senior care and provide tax credits to support unpaid family caregivers.

The growing burden on this sandwich generation weakens careers and quality of life, and has ramifications for society at large. It is a drag on monthly budgets and long-term financial health.

A 40-something contributing $1,500 a month over five years to support an aging parent stands to lose more than $1 million in retirement savings, according to an analysis by Steph Wagner , national director of women and wealth at Northern Trust Wealth Management.

“It’s become incredibly expensive to manage the longevity that we’ve created,” says Bradley Schurman , an author and demographic strategist, who says that the demands of caring for older generations could push more people in midlife to retreat from the workforce, particularly women. “That’s a massive risk for the U.S. economy.”

Career goals on hold

Not too long ago, the typical sandwich caregiver was a woman in her late 40s with teenage kids and maybe a part-time job. Now, according to a 2023 AARP report, the average age of these caregivers is 44, and a growing share are men. Nearly a third are millennials and Gen Z. They are in the critical early-to-middle stages of their careers and three-quarters of them work full or part time.

Diana Fuller, 49, says being the go-to person for her 83-year-old mother’s care for more than four years has been stressful, even with her mother now living in a nearby, $10,000-a month memory-care centre in Charlotte., N.C. (Long-term-care insurance covers 75%; the rest is paid out of her mother’s savings.)

She has put on the back burner career goals such as ramping up the leg warmer business she started with her sister. She has missed moments such as her 9-year-old son’s school holiday concert last year because of her mother’s frequent hospital stays.

Her husband picks up a lot of the child care duties when her mom is in the hospital. Still, she says, “it often feels like everything is about to implode.”

The financial pressures are also growing for the sandwich generation. According to a Care.com survey of 2,000 parents, 60% of U.S. families spent 20% or more of their annual household income on child care last year, up from 51% of families in 2021. Meanwhile, the median cost of a home health aide climbed 10% last year to $75,500, data from long-term-care insurer Genworth Financial show.

Caregivers often risk paying for such costs in their own old age, financial advisers say. More than half reported in a 2023 New York Life survey that they had made a sacrifice to their own financial security to provide care for their parents on top of their children.

Long-distance care

Many in the sandwich generation say they feel torn between the needs of their kids and parents. Liam Davitt , a public-relations professional, and his wife, Lisa Fels Davitt , recently moved from their Washington, D.C., condo to suburban New Jersey so that their 7-year-old son could be closer to cousins and go to a good public school. (They had previously paid for private school.)

That meant moving away from his 84-year-old mother in an independent living community. The long distance has made helping her even with little things more complicated, such as troubleshooting glitches with her iPhone. He recently enlisted a nearby fraternity brother to help her assemble a new walker.

An avid runner, he says he finds himself taking care of himself—avoiding potentially ankle-twisting mud runs and keeping up with his doctors’ appointments, for example—out of fear he won’t be able to care for his younger and older family.

“If all of a sudden I’m less mobile, then I’m more of a burden on my own family” says Davitt. He is planning to move his mother closer by.

The Giordanos, in Georgia, have made adjustments, too. With their newborn keeping them busy, they installed cameras and door chimes to help monitor Kait’s parents.

Her parents enjoy pushing their grandson in the stroller around the house while supervised, she says. When Tamrin comes home from work, he gives his in-laws dinner and medications while holding the baby.

The couple isn’t sure when they’ll have another child, which would require paying for more help.

“We may have to wait,” Kait said. “We’re very much living in the moment.”

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