Google Fails to ‘Wow’ as AI Bills Mount

It’s good to be Google these days. But it isn’t easy, and it will keep getting harder.

Second-quarter results from parent company Alphabet on Tuesday afternoon showed strength in advertising and cloud revenue along with a record high in operating profit as the Silicon Valley titan, once known for lavish employee perks, continues to clamp down on most costs, save for those designed to build out generative artificial intelligence capabilities .

But the results also offered “no excitement,” in the words of Jefferies analyst Brent Thill . Overall revenue exceeded Wall Street’s consensus projection by just 0.6%—the lowest beat percentage in at least five years, according to FactSet. YouTube advertising revenue also came in lower than analysts expected. Alphabet’s previous report, three months ago , offered bigger positive surprises in both revenue and earnings growth, with the announcement of the company’s first-ever dividend thrown in for good measure. Alphabet’s stock had jumped nearly 17% since that report; the shares gave up about 4% in premarket trading on Wednesday.

Tuesday’s results also set the stage for what might be a more challenging second half of the year. For one, comparisons will be tougher as the second half of last year had Google nearly recovered from an earlier advertising slump. Google also didn’t fully ramp up its spending on AI infrastructure until well into the second half of 2023; capital expenditures in the first half of 2023 were barely half of the $25.2 billion the company has spent in the first half of this year.

That spending won’t be taking a breather any time soon, even as Google has pared back other costs and even brought its head count down by more than 1,300 positions in the most recent quarter. Alphabet said Tuesday that capex will be at or above $12 billion a quarter for the second half of the year, likely leading to a total outlay of more than $49 billion for the year—84% higher than what the company has averaged annually over the past five years.

“Look, obviously we are at the early stage of what I view as a very transformative area,” Alphabet Chief Executive Sundar Pichai said during Tuesday’s earnings call when asked by an analyst about the company’s AI investments. He added that “the risk of underinvesting is dramatically greater than the risk of over investing for us here,” not mentioning the record amounts of capex that tech rivals Microsoft , Amazon.com and Meta Platforms are pouring into the same thing.

Google has the resources: Alphabet’s net cash pile of nearly $98 billion is substantially bigger than those of even its deep-pocketed peers. But putting that money to work is getting to be a challenge. The Wall Street Journal reported Monday that Google’s talks to acquire cybersecurity startup Wiz have fallen apart. The purported $23 billion deal would have been Google’s largest ever and most certainly would have drawn the type of close regulatory scrutiny that has lately been keeping tech mergers in limbo for 18 months or more. Such an uncertain payoff reportedly was a concern among Wiz and its investors; Google’s acquisition of Fitbit in 2021 for less than one-tenth that price took nearly 15 months to close.

Google is also going back to the drawing board on a long-running plan to phase out the use of internet tracking technology known as “cookies,” despised by privacy advocates but depended upon by advertisers. Google was building up an alternative technology called “privacy sandbox,” but that plan drew a lot of opposition from advertisers and regulators worried that it would further cement the company’s internet advertising dominance. Google said Monday it would instead offer users a prompt to allow them to opt out of cookie tracking.

That move is unlikely to dent Google’s powerful search ad business. But that and the failed Wiz talks show the growing constraints the company is operating under as regulators look even more closely at big tech’s position, and judges and juries start weighing in. A verdict in the federal government’s antitrust case against Google is expected before the end of the year and could result in a ruling that would seek a breakup of the $250-billion-a-year advertising juggernaut.

Google’s latest results were good, but good isn’t always enough.

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