Trump and SoftBank Promise to Create 100,000 AI Jobs. It Won’t Be Easy.
2 min
SoftBank Group CEO Masayoshi Son stood besides President-elect Donald Trump at Mar-a-Lago on Monday, and announced a commitment to invest $100 billion in the U.S. over the next four years—and create 100,000 jobs. The investments will be concentrated in AI.
“My confidence level to the economy of the United States has tremendously increased with his victory,” Son said at the news conference.
SoftBank is an investment holding company with a range of technology investments all over the world, but especially in the U.S. At the end of September, the total value of its investments was $136 billion, so the new commitment would represent a substantial expansion of SoftBank’s balance sheet.
Raising that sort of money may prove difficult, but the bigger obstacle could be the commitment on jobs—the focus on AI companies, in particular, complicates the goal. AI companies spend a lot on salaries, but these are some of the most expensive employees in the world right now. And they don’t tend to employ a lot of people overall
OpenAI, which has raised $18 billion and has a private market value of $157 billion, has 1,372 employees. To fulfill Trump and Son’s commitment, in other words, the investments would have to create 73 AI companies on the scale of OpenAI.
“A lot of advanced tech these days, including AI, is capital intensive and also highly dependent on high-paid skilled workers,” labor economist Guy Berger of the Burning Glass Institute told Barron’s . “I’m not sure how much head count $100 billion spread out over four years gets you.”
A selection of a dozen AI start-ups with valuations over a billion dollars reveals the uphill climb to the 100,000 jobs goal. These companies have raised a combined $42 billion and have an aggregate private market value of $309 billion, according to FactSet. Anthropic, which has raised almost $12 billion, has only 425 employees. All told, these companies employ less than 10,000 workers, an average of 785 workers per start-up.
Databricks, a data analytics start-up with a valuation of $43 billion, accounts for almost half of those employees. Excluding Databricks, the per start-up employee count falls to 399.
Other barriers in the labor market exist, as well. The overall unemployment rate is 4.2%, but narrow that down to workers with masters and doctoral degrees who are most likely to be AI employees, and the rate drops to 2.0% and 1.0%, respectively. In all, there are only 483,000 workers with advanced degrees looking for work, and most of them aren’t AI engineers.
“The labor market is not super loose right now,” Berger said. “A lot of gross jobs created here might simply involve reallocating people who already have jobs.”
Monday’s press conference recalled a similar one from 2016, when Trump and Son stood in the lobby of Trump Tower and promised $50 billion in U.S. investment and 50,000 jobs. SoftBank didn’t reply to a request for comment about the progress of that 2016 commitment.
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Nvidia’s earnings will test Wall Street’s confidence in the AI boom.
3 min
Chip makers are fighting to assure investors that the artificial-intelligence boom is racing forward. Wall Street might not believe it until Nvidia’s NVDA -0.98%decrease; down pointing triangle Jensen Huang says so.
When Huang steps up to the mic for his company’s earnings call Wednesday, he will have the world’s attention. What he says about Nvidia’s present will preview the future of AI, dictate the path forward for a tech-crazed stock market and influence an American economy increasingly tethered to hopes that the boom won’t go bust.
The $5 trillion chip maker has provided the key building blocks for AI since the launch of ChatGPT in 2022 set off a race for dominance among OpenAI, Anthropic and established Silicon Valley giants. Now, as Nvidia backstops sprawling data-center projects and an exotic money pipeline to boost chip demand, the company’s influence is arguably bigger than ever.
But there are signs of trouble ahead. Political pushback to AI is growing. A bond selloff propelled borrowing costs to their highest levels in years. The hyperscalers that include some of Nvidia’s key customers—once cash-printing machines—are relying more on debt. OpenAI recently told investors its revenue rose by a tepid 18% in the second quarter while its losses deepened.
Nvidia is increasingly stepping in to shore up potential weak points across the market. Earlier this month, the company teamed up with six of Wall Street’s biggest firms on a $500 billion AI-financing plan, pledging to backstop lending to customers that can’t afford its chips otherwise. The chip maker last week also took a stake in Cloverleaf Infrastructure, which arranges power for data centers, and struck a $6 billion deal with startup Poolside aimed at developing a powerful open-weight AI model.
After watching shares in other chip makers and the so-called Magnificent Seven tech companies swing wildly in recent months, Wall Street is hoping Nvidia can beat expectations—again. The countdown is on.
“It’s kind of becoming more and more like the World Cup final than the Super Bowl at this point,” said Brian Mulberry, chief market strategist at Zacks Investment Management. “It’s just gotten to be that big.”
The company has smashed analysts’ earnings estimates for each of the 14 quarters since the AI boom kicked into high gear. Nvidia posted 210% annual growth in net income in its last three-month period, according to FactSet, making Wall Street’s 126% projection look pedestrian.
Expectations for a blowout second quarter have risen rapidly over the course of this year. All Nvidia will have to do to beat this target: outrun 95% annual earnings growth to more than $51.5 billion. Analysts project the chip maker will report record sales of $92 billion for the period, up from a forecast of $78 billion at the start of this year.
In July, big-tech earnings sparked volatility. Concerns about runaway capital spending spread across the sector after Alphabet’s and Tesla’s results, driving a $890 billion wipeout that contributed to the unwind of hedge fund Situational Awareness. Microsoft posted the largest one-day gain in market capitalization by any company, ever, after a quarter proving that it could still show investors the money. SpaceX rocketed higher after a record-breaking initial public offering, only to see $1 trillion in value evaporate.
Surging memory prices and borrowing costs have fueled fears that those and other companies will be unable to keep plowing more money into supplies including Nvidia chips. Shaia Hosseinzadeh, founder of OnyxPoint Global Management, has recently bought dips in AI-infrastructure stocks when Wall Street has strained to absorb massive debt issued by Silicon Valley.
“The macro data is really quite robust,” he said. “Of course, there’s a level at which everything breaks.”
Investors have kept pumping money into the AI trade despite concerns around chip consumers—and to the benefit of chip producers. That is why Nvidia’s outlook for semiconductor demand could send ripples through counterparts such as Micron Technology and Sandisk, developers of the data centers in which their chips reside, and a supply chain of power producers, contractors and other specialists that underpin the globe-spanning AI build-out.
“We joke internally that we’re all Nvidia analysts now,” said David Lefkowitz, head of U.S. equities at UBS Global Wealth Management.
The irony is that investors have tended to sell Nvidia stock immediately after blockbuster earnings, with shares falling each trading session after its four past quarterly reports. Some are betting that will be the case this time around, too.
The options market is pricing in a 5.3% swing, higher or lower, in Nvidia shares during the session following earnings, according to Option Research & Technology Services. That is higher than the 4.8% average move in Nvidia’s stock over the last 12 months after the company reports quarterly results.
In recent days, some of the most actively traded Nvidia options have been put contracts tied to the stock falling from its Friday value of $214.75 to $205 and $210 apiece, according to Cboe Global Markets data. Put options give the right to sell a stock by a set price and typically represent a bearish wager.
Many analysts remain optimistic. Frank Lee, global head of tech hardware and semiconductor research at HSBC Global Investment Research, recently raised his price target for Nvidia shares to $360 from $325, citing, among other things, Nvidia’s strategic partnerships with suppliers and its role as a top contributor to open-source AI.
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