Health Is Wealth When Tariffs Are Denting Profit Forecasts

President Donald Trump’s imposition of tariffs on trading partners have moved analysts to reduce forecasts for U.S. companies. Many stocks look vulnerable to declines, while some seem relatively immune.

Since the start of the year, analysts’ expectations for aggregate first-quarter sales of S&P 500 component companies have dropped about 0.4%, according to FactSet. The hundreds of billions of dollars worth of imports from China, Mexico, and Canada the Trump administration is placing tariffs on, including metals and basic materials for retail and food sellers, will raise costs for U.S. companies. That will force them to lift prices, reducing the number of goods and services they’ll sell to consumers and businesses.

This outlook has pressured first-quarter earnings estimates by 3.8%. Companies will cut back on marketing and perhaps labour, but many have substantial fixed expenses that can’t easily be reduced, such as depreciation and interest to lenders. Profit margins will drop in the face of lower revenue, thus weighing on profit estimates. The estimates dropped mildly in January, and then picked up steam in February, just after the initial tariff announcements.

“We are starting to see the first instances of analysts cutting numbers on tariff impacts,” writes Citi strategist Scott Chronert.

The reductions aren’t concentrated in one sector; they’re widespread, a concrete indication that the downward revisions are partly related to tariffs, which affect many sectors. The percentage of all analyst earnings-estimate revisions in March for S&P 500 companies that have been downward this year has been 60.1%, according to Citi, worse than the historical average of 53.5% for March.

The consumer-discretionary sector has seen just over 62% of March revisions to be lower, almost 10 percentage points worse than the historical average. The aggregate first-quarter earnings expectation for all consumer-discretionary companies in the S&P 500 has dropped 11% since the start of the year.

That could hurt the stocks going forward, even though the Consumer Discretionary Select Sector SPDR exchange-traded fund has already dropped 11% for the year. The declines have been led by Tesla and Amazon.com , which account for trillions of dollars of market value and comprise a large portion of the fund. The average name in the fund is down about 4% this year, so there could easily be more downside.

That’s especially true because another slew of downward earnings revisions look likely. Analysts have barely changed their full-year 2025 sales projections for the consumer-discretionary sector, and have lowered full-year earnings by only 2%, even though they’ve more dramatically reduced first-quarter forecasts. The current expectation calls for a sharp increase in quarterly sales and earnings from the first quarter through the rest of the year, but that’s unrealistic, assuming tariffs remain in place for the rest of the year.

“The relative estimate achievability of the consumer discretionary earnings are below average,” Trivariate Research’s Adam Parker wrote in a report.

That makes these stocks look still too expensive—and vulnerable to declines. The consumer-discretionary ETF trades at 21.2 times expected earnings for this year, but if those expectations tumble as much as they have for the first quarter, then the fund’s current price/earnings multiple looks closer to 25 times. That’s too high, given that it’s where the multiple was before markets began reflecting ongoing risk to earnings from tariffs and any continued economic consequences. So, another drop in earnings estimates would drag these consumer stocks down even further.

Industrials are in a similar position. Many of them make equipment and machines that would become more costly to import. The sector has seen about two thirds of March earnings revisions move downward, about 13 percentage points worse that the historical average. Analysts have lowered first-quarter-earnings estimates by 6%, but only 3% for the full year, suggesting that more tariff-related downward revisions are likely for the rest of the year.

That would weigh on the stocks. The Industrial Select Sector SPDR ETF is about flat for the year but would look more expensive than it is today if earnings estimates drop more. The stocks face a high probability of downside from here.

The stocks to own are the “defensive” ones, those that are unlikely to see much tariff-related earnings impact, namely healthcare. Demand for drugs and insurance is much sturdier versus less essential goods and services when consumers have less money to spend. The Health Care Select Sector SPDR ETF has produced a 6% gain this year.

That’s supported by earnings trends that are just fine. First-quarter earnings estimates have even ticked slightly higher this year. These stocks should remain relatively strong as long as analysts continue to forecast stable, albeit mild, sales and earnings growth for the coming few years.

“This leads us to recommend healthcare and disfavour consumer discretionary,” Parker writes.

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.

Health Is Wealth When Tariffs Are Denting Profit Forecasts

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

Playing a different game

Overlooked