Why Are Hyperscaler Stocks Still Struggling After Strong Q3 Earnings?

As expected, AI hyperscaler stocks enjoyed an exceptionally strong Q3 earnings season on Wall Street. But despite their dominance, US artificial intelligence leaders are continuing to struggle for momentum. Have

In terms of earnings alone, Wall Street has never had it so good. Top-line performance has been surging among the biggest AI spenders in the US, with cloud revenue and overall sales rallying at a robust rate from Microsoft’s (MSFT) Azure and Amazon’s (AMZN) AWS posting growth of 48% and 39%, respectively. Meta (META) also beat its revenue expectations for the year.

Given that major hyperscalers like Microsoft, Amazon, Alphabet (GOOGL), Meta, and Oracle (ORCL) account for around one-fifth of the S&P 500 by market capitalization, this sign of earnings growth should’ve been a catalyst for more investor optimism. But earnings outperformance has so far failed to translate to growth on Wall Street.

Shockingly, more than $2 trillion was wiped from the Nasdaq-100 market value in October 2026, pointing to a deeper disconnect between markets and the AI stocks that have been pushing the S&P 500 to new heights since late 2022.

Looking more specifically at the artificial intelligence sector, the Global X Artificial Intelligence & Technology (NASDAQ:AIQ) ETF recorded a loss of 8.42% throughout the month of October.

So what’s going wrong for the hyperscalers that have supported Wall Street for so long since the beginning of the AI boom?

Capex Continues to Shape Sentiment

Capital expenditures have weighed heavily over investor sentiment when it comes to hyperscaler stocks, and it appears to be casting a shadow over Q3 earnings during the final months of the year.

After all, much of Wall Street’s top-line revenue growth has continued to serve up the same impressive figures that have helped to propel the S&P 500 92% higher between the launch of OpenAI’s ChatGPT large-language model (LLM) on November 30, 2022, and the beginning of Q4 2026.

But spending is coming under intense scrutiny in 2026, especially after estimates have suggested that hyperscaler capex is set to hit $835 billion annually this year when incorporating Oracle’s fiscal 2027 guidance.

This represents a seismic increase in financing. For instance, Alphabet’s debt balance has accelerated from $16 billion a year ago to around $100 billion in 2026. The company also announced an $80 billion equity raise in June, which was comprised of a $30 billion underwritten offering of common stock and mandatory convertible preferred shares, a $40 billion at-the-market program, and a $10 billion private placement with Berkshire Hathaway, according to an SEC filing.

To further quantify the turnaround in sentiment, capital expenditures among the four hyperscalers plus Oracle are expected to rise from 50% of operating cash flow in 2024 to almost 90% by 2027, according to analyst estimates.

This means that as the AI boom shifts further towards building the infrastructure to meet high expectations, the emphasis is increasingly on companies to show that their investments are paying off.

AI Growth to Make an Impact

At this stage, it’s important to emphasize that artificial intelligence is an unprecedented technological revolution that’s likely to add value to the economy in a way that’s difficult for investors to fully take stock of today.

The World Economic Forum has estimated that generative AI alone has the potential to add the equivalent of between $2.6 trillion and $4.4 trillion to the global economy each year, a value that would potentially surpass the total GDP of the United Kingdom.

SpaceX CEO Elon Musk has been a little more ambitious with his estimates, suggesting that AI could add between $20 trillion and $30 trillion a year to the global economy.

The reality will be critical for understanding whether the sheer scale of hyperscaler spending is justifiable over the long term, but we can already see evidence of artificial intelligence optimizing core processes in a way that can support its own buildout.

In construction, contractors are using generative AI tools to tackle the same inefficiencies that cause 80% of large projects to go over budget and 20% to overrun when it comes to scheduling.

With attention turning towards infrastructure projects and the buildout of data centers, these metrics could point to snowballing cost savings as new efficiencies contribute to saving time in the construction process.

Controlling Capex

Looking to 2027, it’s unlikely that capital expenditures will cause AI bulls to cool down in their enthusiasm for the future of the sector, but Wall Street is increasingly eager to see some sign of cash flow management that can recapture the optimism that drove the artificial intelligence boom since late 2022.

Hyperscalers remain adamant that their spending is justified. But for now, more sideways trading appears to be the most likely outcome for AI stocks until we begin to see these ambitious infrastructure projects begin to pay off.

Disclosure: On the date of publication, Dmytro Spilka did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer. Dmytro Spilka does not intend to make a trade in any of the securities mentioned above in the next 72 hours.

Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga’s reporting and has not been edited for content or accuracy.