Tech Giants Double Down on Their Massive AI Spending
Amazon, Google, Microsoft and Meta pour billions into artificial intelligence, undeterred by DeepSeek’s rise
Amazon, Google, Microsoft and Meta pour billions into artificial intelligence, undeterred by DeepSeek’s rise
Tech giants projected tens of billions of dollars in increased investment this year and sent a stark message about their plans for AI: We’re just getting started.
The four biggest spenders on the data centers that power artificial-intelligence systems all said in recent days that they would jack up investments further in 2025 after record outlays last year. Microsoft , Google and Meta Platforms have projected combined capital expenditures of at least $215 billion for their current fiscal years, an annual increase of more than 45%.
Amazon.com didn’t provide a full-year estimate but indicated on Thursday that total capex across its businesses is on course to grow to more than $100 billion, and said most of the increase will be for AI.
Their comments in recent quarterly earnings reports showed the AI arms race is still gaining momentum despite investor anxiety over the impact of China’s DeepSeek and whether these big U.S. companies will sufficiently profit from their unprecedented spending spree.
Investors have been especially shaken that DeepSeek replicated much of the capability of leading American AI systems despite spending less money and using fewer and less-powerful chips, according to its Chinese developer. Leaders of the U.S. companies were unbowed , touting advances in their own technology and arguing that lower costs will make AI more affordable and grow the demand for their cloud computing services, which AI needs to operate.
“We think virtually every application that we know of today is going to be reinvented with AI inside of it,” Amazon Chief Executive Andy Jassy said on Thursday’s earnings call.
Here is a breakdown of each company’s plans:
Amazon said a measure of its capex that includes leased equipment rose to a record of about $26 billion in the final quarter of 2024 , driven by spending in its cloud-computing division on equipment for data centers that host AI applications. Executives projected it would maintain the fourth-quarter spending volume in 2025, meaning an annual total of more than $100 billion by that measure.
The company—which gets most of its revenue from e-commerce and most of its profit from cloud computing—also projected overall sales for the current quarter that missed analysts’ expectations. Its shares slid about 4% in after-hours trading Thursday. The stock rose more than 40% in 2024 and was up nearly 9% this year before its earnings report.
Jassy said AI has the potential to propel historic change and that Amazon wants to be a leader of that progress.
“AI represents for sure the biggest opportunity since cloud and probably the biggest technology shift and opportunity in business since the internet,” Jassy said.
Google shares are down about 7% since its earnings report Tuesday, which showed disappointing growth in its cloud-computing business. Still, parent-company Alphabet said it is accelerating investments in AI data centers as part of a surge in capital expenditures this year to about $75 billion, from $52.5 billion in 2024. The spending will go to infrastructure both for Google’s own use and for cloud-computing clients.
“I think part of the reason we are so excited about the AI opportunity is we know we can drive extraordinary use cases because the cost of actually using it is going to keep coming down,” said CEO Sundar Pichai .
AI is “as big as it comes, and that’s why you’re seeing us invest to meet that moment,” he said.
Microsoft has said it plans to spend $80 billion on AI data centers in the fiscal year ending in June, and that spending would grow further next year , albeit at a slower pace.
Chief Executive Satya Nadella said AI will become much more extensively used , which he said is good news. “As AI becomes more efficient and accessible, we will see exponentially more demand,” Nadella said.
Growth for Microsoft’s cloud-computing business in the latest quarter also disappointed investors, leaving its stock down about 6% since its earnings report last week.
Meta, too, outlined a sizable increase in its investments driven by AI, including $60 billion to $65 billion in planned capital expenditures this year, roughly 70% higher than analysts had projected. Shares in Meta are up about 5% since its earnings report last week.
CEO Mark Zuckerberg said investing vast sums will enable it to adjust the technology as AI advances.
“That’s generally an advantage that we’re now going to be able to provide a higher quality of service than others who don’t necessarily have the business model to support it on a sustainable basis,” he said.
A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.
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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.
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.”
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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