If U.S. stock prices continue to fall, wealthy consumers could slow their spending, putting further pressure on the U.S. economy and markets.
That could mean everything from fewer luxury cars and handbags being sold to reduced demand for top-end homes and fancy vacations.
Broadly, retail sales rose a less-than-expected 0.2% in February from January, the Census Bureau reported earlier this week. There are signs affluent consumers are holding back, too. Major airlines cut their guidance for the first quarter last week on expectations of weak demand. And U.S. credit-card spending on top luxury brands declined 5% year over year in February, Citi reported on March 11.
Though it’s “too early to tell” whether spending will contract, every dollar decline in the value of assets, such as stocks or real estate, leads to a two cent decline in spending among “upper-end consumers,” according to Joseph Brusuelas, chief economist at RSM U.S.
Brusuelas’ calculation describes the so-called negative wealth effect, when a decline in investment portfolio value affects consumer attitudes toward how much they can spend.
Today, the S&P 500 is struggling, down just over 1% on Tuesday , leading to a 4.5% decline year to date, after slipping into correction territory last Thursday.
Even that 10% decline doesn’t mean a pullback in spending by the affluent is imminent, Brusuelas told Barron’s .
But the “volatility, uncertainty, complexity, and ambiguity,” in geopolitical, economic, and market news coming out of the U.S. doesn’t bode well for luxury spending in particular, according to Erwan Rambourg, global head of consumer and retail research at HSBC.
“Luxury demand is holding up in the U.S., but I’m not sure for how long,” Rambourg told Barron’s . “There might be a lag between the data points, the markets, and the actual spending.”
In addition to sharp declines in stocks and cryptocurrency since mid-February, affluent Americans are facing a decline of 5.39% in the value of the U.S. dollar against the euro this year. By contrast, the euro lost 6.2% against the dollar last year.
The dollar’s decline not only affects the price of luxury goods—many of which are made in Europe—but the desire of U.S. consumers to travel and spend across the Atlantic, according to HSBC.
Another challenge is the uncertain trajectory of tariffs on goods from Canada, Mexico, and Europe.
“I’ve always thought that you bought luxury not because you were wealthy, but because you were confident about the future,” Rambourg said. “The whole tariff conversation—the reversals on Canada and Mexico—one day it’s 25%, the following day it’s postponed by a month, the following day, you have some exceptions…if you’re a business manager and if you’re a consumer, obviously that will affect your confidence in a big way.”
Still, wealthier consumers have a significant buffer in their investment portfolios, which have grown substantially over several years of upward equity returns, according to Katie Nixon, CIO of Northern Trust Wealth Management.
“In any given year, you expect to have 5% pullbacks almost routinely,” Nixon said. “It’s just that we haven’t had one in a while so this feels kind of extreme.”
Investors know that markets can fall significantly, as happened during the financial crisis in 2008 or during the early days of pandemic, according to Scott Zelniker, private wealth advisor at UBS Wealth Management. “More often than not, the market was up significantly 12 months later,” Zelniker told Barron’s .
One topic of conversation among Zelniker’s clients, however, is whether to buy the cars they are leasing when their agreements expire instead of re-leasing them as usual, considering the potential for tariffs to lead to higher-priced automobiles, he said. “They already have a contract with a price.” Why buy, or lease, a new car?
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
A 30-metre masterpiece unveiled in Monaco brings Lamborghini’s supercar drama to the high seas, powered by 7,600 horsepower and unmistakable Italian design.
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.
What gives?
U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.
The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.
All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.
But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .
Landing a job is tough for most everyone else.
Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.
Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.
Playing a different game
It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.
Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.
You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.
“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.
He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.
The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.
As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.
A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.
In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .
Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.
He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.
If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”
Overlooked
James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.
He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.
He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.
Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.
“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”
The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.
“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”
He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.
It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.
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