Tech Giants Double Down on Their Massive AI Spending

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 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