Gen X Is Stuck in the Middle and Financially Squeezed. How One Financial Adviser Is Helping.

Gen X families, including affluent ones, face a hornet’s nest of financial challenges, from helping out their adult children to providing care for ageing parents to managing careers in a perilous job market.

Zach Mangels, a senior vice president at Wealthspire Advisors in San Rafael, Calif., estimates a quarter of his clients are in the Gen X demographic.

“Mortgage rates are higher, carrying costs are higher, educational costs are higher, groceries are higher, eldercare is higher—all of that stuff eats into cash flow. And even people with higher incomes are feeling that,” says Mangels, 40.

Barron’s Advisor spoke with Mangels about the financial challenges facing his Gen X clients, people between the ages of 46 and 61.

Mangels touched on how he creates short-term plans for clients concerned about career setbacks, why he recommends boundaries for Gen X parents who want to financially support adult kids, and how he guides clients with ageing parents.

How has financial planning for Gen X clients changed?

Typically, when you create a financial plan, you’re looking at long-range goals.

But now I look at more immediate needs because of the pressures Gen X families are dealing with.

For example, I see more clients whose children are coming back home after graduating from college, needing financial support for a much longer period of time than previous generations expected to receive.

How should help for adult children be structured?

If they need to support their child, I want to understand the nature of what the support will look like.

I have a client whose kids just graduated and whose majors don’t lend themselves to a high income right now.

They knew their kids would be coming back home after graduation and we talked about what the nature of their help would look like.

First we looked at their financial plan to see what kind of support they could provide and we defined the maximum amount.

Then we designed the support in a way that would be planned, explicit, and with purposeful boundaries.

That’s very important for the younger generation. Parents need to know how to help their kids without them becoming dependent.

The children need to have agency and to know they don’t have access to an unlimited piggy bank.

What was the plan?

The clients had a conversation with their kids about what to expect.

The kids could live rent-free for three years, with a small stipend, an amount that didn’t disincentivise them from looking for a job.

In this environment, entry-level jobs are increasingly hard to come by, but any job that moves you closer to a career you want is worth looking at. In this case, their daughter got a job as an assistant to a personal shopper, which was related to the direction she wanted to follow.

Do you help the parents practice what to say?

I didn’t provide a ton of details to the parents with what exactly to say. But I coached them on the basics—having a clear, purposeful, intentional conversation and getting buy-in from their kids.

How do you advise clients with ageing parents?

The cost of long-term care for seniors has increased dramatically.

One of the conversations I have with my clients is how they perceive their parents’ financial circumstances and to what degree they might have to provide a layer of financial support. My dad was in memory care for a few years and we paid maybe 15 grand a month.

My clients’ parents are usually relatively stable financially. But the most important issue is the use of the family residence to help provide support. A lot of people in California who have owned homes a long time have a lot of equity in those homes. That’s the ultimate backstop, the last line of defence.

What about the job market?

Gen X is also dealing with career and income volatility. We’ve seen all the headlines about tech layoffs and the rise of AI. A lot of my clients work in the tech industry.

The conversations I have more frequently focus on clients’ concerns about their ability to continue earning at the same level.

We look at diversifying their equity component more quickly, getting it out of company stock, especially for those in tech.

For example, some clients at Amazon have restricted stock units they can sell periodically. But now they’re selling those (Amazon) stocks and then deploying the [cash into other equities] more slowly.

We’re hearing about how quickly AI is going to change things. For people in software on the front lines, they’re pretty anxious about it.

Can you provide an example?

One client who works at Google told me he expected a lot of change with AI as the disruptive force.

A few companies will benefit, he feels. A lot won’t. So he’s actively selling his company shares.

Historically we would reinvest the proceeds as they’ve come in. But now he wants to slow that down. Hold cash a little bit longer and slowly deploy it.

His perception is that change is coming quickly. He doesn’t know what that will look like but it probably won’t be good.

In behavioural finance, we know you feel a loss much more significantly than you feel a gain. And he’s trying to avoid putting money in the market right before there is a big correction.

It sounds stressful.

It’s super stressful. And as we go into 2026, especially in the tech sector and among those with high incomes, I see a lot of anxiety.

I have another client who works in finance, but the nature of his job moves with economic cycles.

He was laid off at the start of Covid and he’s getting nervous again. It’s a “vibecession” that a lot of people are feeling right now.

How do you help someone worried about a job loss?

Over a year ago, we restructured where his investments are held, so that if he gets laid off and ends up spending his emergency fund, the next thing he’ll tap is a more conservative account we created.

It’s not that we took his overall asset allocation and made it more conservative. We just put more investments in this other account. It’s a matter of asset location and it gives him peace of mind knowing he has a fallback he can tap.

That strategy would be helpful for anybody today. The challenge is if you have accounts with a lot of capital gains.

Does multigenerational planning help?

My work with baby boomer clients often involves conversations about supporting their Gen X and older millennial children.

I’ve seen a lot of parents and grandparents of Gen Xers looking for ways to accelerate their generational wealth transfer, trying to provide assistance now when it’s more impactful on their kids’ lives.

For example, a baby boomer client was looking for ways to help her Gen X son, who is married with a child in middle school, but had started accumulating a lot of debt after he was laid off.

We worked together to model the level of support she could provide and how to structure the assistance so it wouldn’t impact her son’s sense of independence.

Ultimately, she decided on a one-time gift that would cover about six months of living expenses. I call this indirect Gen X planning.

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