When Alphabet and Tesla kicked off tech earnings season on Wednesday, one theme became immediately clear: AI spending is under a microscope.
Both companies reported negative free cash flow for the latest quarter and told investors to prepare for higher capital expenditures. They both also reported better-than-expected revenue, but that wasn't enough to prevent an after-market selloff, with Tesla shares sliding 4% and Alphabet down more than 3%.
It's a potentially ominous sign for the tech industry, particularly the other megacaps, which are mostly set to report quarterly results next week. Meta and Microsoft are scheduled to report next Wednesday, followed a day later by Amazon and Apple.
Much of the AI boom to date has been fueled by historic levels of infrastructure spending among a small crop of companies, including hefty investments into model developers OpenAI and Anthropic. But the recent emergence of cheaper open-source models, largely out of China, along with signs that corporate America is getting more frugal when it comes to spending on AI services, has raised concerns about the future returns on investment.
Heading into Wednesday's reports, Alphabet's stock was already on pace for its third straight monthly decline after surging in April, while Tesla shares were down 11% in July and 17% for the year. The tech-heavy Nasdaq has dropped about 5% since reaching a record in early June.
While Alphabet and Tesla are both spending at unprecedented levels, their numbers vary dramatically.
Google's parent company forecast capex for this year of $195 billion to $205 billion and warned of higher numbers in 2027. Prior guidance was for spending of $180 billion to $190 billion. At the top end of the new range, Alphabet could be the biggest spender in tech this year, as Amazon's latest guidance was for more than $200 billion, though that number may increase when the company reports results next week.
Google and its hyperscaler peers are building out data centers packed with advanced chips so they can provide the computing power necessary to build and run the leading AI models and the services they power.
Mizuho analysts wrote in a note that Google's capex increase was "broadly anticipated," and that the overall story is positive, largely due to the surge in cloud revenue, which jumped 82% from a year earlier, blowing past estimates. Cloud margins expanded and usage of Google's Gemini model accelerated.
"As such we are surprised the stock is trading off after hours and would expect it to recover in trading tomorrow," wrote the analysts, who recommend buying the stock.
'As fast as we can spend'
Tesla reiterated expectations for more than $25 billion in capex this year, which would represent about 200% year-over-year growth. In the second quarter, capex soared 142% to $5.79 billion. The company boosted spending on self-driving technology, AI and robotics initiatives that CEO Elon Musk has been touting for years.
Tesla is now retooling its factories to make the two-seater driverless Cybercab, and to manufacture Optimus humanoid robots, which are still being developed, while also preparing to start construction of a sprawling AI chip-manufacturing plant in Texas.
"We should be spending on capex as fast as we can spend, as fast as we can without it being too wasteful," Musk said on the earnings call. He added, "It's ok to be a little less capital efficient if we get things done sooner."
For both companies, the aggressive growth plans are resulting in a major hit to their cash holdings.
Free cash flow at Tesla turned negative in the quarter, with a deficit of $1.1 billion after the company generated $146 million in free cash flow a year ago and $1.44 billion in the first quarter of 2026.
"This is a massive capex year but we are confident that all the things that we are investing in will yield incredible returns," Musk said. He compared Tesla's spending and building in "many different arenas simultaneously," to that of Henry Ford with the Model T.
"I think probably this is the fastest industrial scale-up since World War II in America," Musk said.
The numbers at Alphabet were even more stark, with free cash flow sinking to negative $5.9 billion after the company, which is lauded for its fat margins from online ads, generated almost $25 billion in free cash flow a year ago.
"We expect the free cash flow will remain under pressure, driven by our investments in technical infrastructure, which enables us to capitalize on the AI opportunity and continue to drive attractive returns," CFO Anat Ashkenazi said on the earnings call.
Most of the company's $44.9 billion in capex in the second quarter went to infrastructure to support the AI buildout, Ashkenazi said.
In addition to building its own data centers, Google executives said they also plan to rely on capacity from third-party cloud providers to meet feverish computing demand, building on a recent compute deal with Musk's SpaceX, which now owns xAI and its Memphis data centers.
The results on Wednesday did nothing to squash the enthusiasm of bullish analysts and investors.
Keith Fitz-Gerald, principal at investment consulting firm Fitz-Gerald Group, said that at Tesla, "profitability is being sacrificed for infrastructure" just as it was previously at companies including Amazon and Netflix.
"I expect it to pay off in spades over the next 12-24, even 36 months," Fitz-Gerald wrote in a note after the report.
And Rebecca Wettemann, CEO of tech research firm Valoir, said in an email that Google's core business remains strong and that its AI investments are generating returns.
"Google's momentum should calm some market fears about AI overspending," she wrote. "Strong performance across its businesses show search isn't dead, advertising still matters, and cloud investment is still a good bet."
Facts Only
* Alphabet reported negative free cash flow of $5.9 billion.
* Tesla reported negative free cash flow of $1.1 billion for the quarter.
* Both companies indicated a need to prepare for higher capital expenditures.
* Alphabet's Q2 capex was $44.9 billion, mostly directed toward AI infrastructure.
* Google forecasts capital expenditures between $195 billion and $205 billion for the year, with guidance for 2027 being higher than prior estimates.
* Tesla reiterated expectations for over $25 billion in capital expenditures for the year.
* Tesla's Q2 capex reached $5.79 billion, a 142% increase from the previous quarter.
* Google's cloud revenue jumped 82% year-over-year.
* Google executives planned to rely on third-party cloud providers for computing demand.
Executive Summary
Full Take
The narrative emerging is one of a structural tension between aggressive, high-spending AI infrastructure buildout and the immediate financial constraints of cash generation among tech giants. The pattern observed suggests that massive expenditure, particularly in areas like data center expansion, becomes the central metric, potentially eclipsing traditional profitability measures for some leaders. This dynamic echoes historical patterns where growth is fueled by asset accumulation rather than immediate margin capture.
The divergence between Alphabet's large negative free cash flow and Tesla's focus on reinvestment in physical assets (factories, chips) illustrates two distinct approaches to scaling technological advantage under pressure. The market reaction suggests a fundamental skepticism about whether the current spending trajectory will translate into sufficient future returns, especially given external shifts like open-source technology. This points toward an underlying systemic question: whether the increased expenditure in AI infrastructure represents genuinely sustainable competitive advantage or merely accelerated depreciation of capital that may face obsolescence from new, cheaper alternatives. The need to reconcile promises of "incredible returns" with the reality of declining free cash flow suggests that future market stability will depend less on current spending rates and more on the demonstrable efficacy of these investments against evolving competitive dynamics.
Bridge Questions: If infrastructure spending continues at this pace, what tangible metrics should be prioritized over immediate free cash flow to gauge long-term technological leadership? How do fluctuating consumer and corporate attitudes toward AI services influence the perceived risk associated with capital expenditure in the hyperscaler space? What structural shifts are necessary for current models of reinvestment to generate returns comparable to historical benchmarks?
Sentinel — Human
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