Moody’s warns AI spending threatens credit quality of Amazon, Meta, Alphabet
Moody’s Ratings has issued a sharp warning this week, stating that the “unprecedented” scale of artificial intelligence (AI) spending by major technology companies threatens their credit quality. The ratings agency highlighted that this investment spree is eroding free cash flow and significantly increasing balance sheet risks for industry giants like Amazon (AMZN), Meta Platforms (META), and Alphabet (GOOGL), Google’s parent company.
The report, released this week and widely reported on July 24 and 25, 2026, also included Microsoft (MSFT), Oracle (ORCL), and specialized AI cloud provider CoreWeave (CRWV.US) among the companies facing heightened financial scrutiny. This financial shift marks a departure from the asset-light models that previously defined the tech sector, pushing these cash-rich corporations towards more aggressive financing strategies.
AI investment shifts tech from asset-light to asset-heavy
The core of Moody’s concern lies in a fundamental transformation within the tech industry. Historically, these firms thrived on asset-light business models, relying on software, intellectual property, and scalable cloud services that demanded relatively modest capital investment.
But the rapid ascent of generative AI has upended this paradigm. It necessitates a vast physical footprint, requiring enormous investments in data centers packed with expensive, energy-intensive servers and specialized AI chips. This transition “demands unprecedented levels of investment and financing,” Moody’s explained in its research note.
Capital expenditure projections surge
The sheer volume of projected capital expenditures (CapEx) underscores the scale of this shift. Moody’s forecasts that hyperscalers’ CapEx will reach an astounding $785 billion in 2026. This figure is then expected to climb even higher, hitting approximately $1 trillion next year.
Such massive outlay is forcing tech giants to increasingly turn to Wall Street for funding. This includes relying more on debt, issuing new stock, and engaging in complex off-balance-sheet financing arrangements to fuel their AI ambitions.
Mounting debt and off-balance-sheet liabilities
The race to build out AI infrastructure is translating into significant increases in financial commitments for these companies. Moody’s report details how both direct debt and less visible liabilities are growing across the sector.
Combined direct debt across the six identified hyperscalers has already reached approximately $460 billion. Beyond traditional loans, companies are also tapping public markets, as seen with Alphabet’s recent $85 billion equity financing plan.
The burden of off-balance-sheet commitments
A particularly noteworthy aspect of this trend is the surge in off-balance-sheet financing. Hyperscalers are increasingly using long-term data center leases to acquire the necessary infrastructure without immediately impacting their direct debt figures. Moody’s states that these lease commitments across the group have ballooned to an eye-watering $1.2 trillion.
A significant portion of this — over $820 billion — relates to data centers that are still under construction and not yet operational. While these leases don’t appear as conventional debt on balance sheets, Moody’s views them as “debt-equivalent liabilities,” obligating companies to substantial future rent payments.
Free cash flow takes a hit across tech giants
The aggressive investment in AI hardware and infrastructure requires massive upfront capital, while the associated revenues materialize over a longer time horizon. This mismatch is placing considerable pressure on free cash flow across the sector, according to the ratings firm.
Several of the world’s most prominent tech firms are already seeing their free cash flow (FCF) metrics deteriorate dramatically. This marks a stark contrast to their historical financial performance, where robust FCF was a hallmark.
Alphabet’s significant free cash flow swing
Alphabet provides a clear illustration of this trend. The company reported its first negative free cash flow quarter since its initial public offering (IPO), plunging from a positive $101 billion in the first quarter to a negative $5.86 billion in the second quarter. This FCF reversal came despite an impressive 82% surge in Google Cloud revenue.
The search giant also raised its 2026 CapEx guidance by $15 billion at the midpoint, setting a range of $195 billion to $205 billion, and indicated further increases for 2027. Alphabet’s contracted future spending commitments jumped by nearly $500 billion in just three months, reaching $811 billion by the end of June.
Divergent impacts among tech giants
Other leading tech companies are also feeling the pinch. Amazon is projected to report negative free cash flow of approximately $7 billion when it releases its results on July 30, following a negative $18.2 billion in the first quarter. Meta is likewise expected to post its first negative free cash flow quarter in over a decade, with estimates hovering around negative $1.2 billion.
Microsoft, however, stands out with a more resilient financial position, forecast to maintain a comfortably positive free cash flow of roughly $15.8 billion. This divergence highlights that while the AI spending imperative is widespread, individual companies possess varying capacities to absorb these costs.
Credit ratings and the circular AI ecosystem
Despite the warnings, Moody’s emphasized that Microsoft, Alphabet, Amazon, and Meta still maintain some of the strongest corporate balance sheets globally. This strength means their investment-grade ratings aren’t under immediate threat, but the situation bears close watching.
The immediate credit pressure is more acute for companies with lower existing ratings. Oracle, for example, holds a Baa2 rating with a negative outlook, placing it just two notches above “junk” status. CoreWeave, operating in the high-yield market with a Ba3 rating, relies on complex private debt structures to finance its extensive GPU hardware fleets.
Interdependencies in the AI supply chain
Moody’s also highlighted a “structural circularity” within the booming AI sector. Many of the multi-billion dollar revenue backlogs reported by hyperscalers originate from strategic investments in pre-IPO artificial intelligence labs such as OpenAI and Anthropic. These AI labs, in turn, become significant customers, spending heavily on cloud computing services provided by those same hyperscalers.
This creates a self-reinforcing, albeit interconnected, ecosystem. But it also heightens risks, as many of the industry’s largest players become increasingly dependent on the same AI customers and shared assumptions about future demand. If those assumptions prove overly optimistic, the ripple effects could be significant.
Investor focus shifts to return on AI investment
While the financial strain is evident, the tech giants do possess substantial strengths that can help mitigate some of these risks. The demand for AI computing remains robust, and their cloud businesses continue to experience growth. Furthermore, hyperscalers have secured hundreds of billions of dollars in long-term customer contracts, which should provide a degree of predictable revenue.
These contracts are crucial in supporting the generally strong credit profiles of the industry, even amidst the current spending surge. However, Moody’s concluded that investors need to recognize this as a structural shift in the tech industry’s financial profile, unlike anything observed during the initial cloud computing era.
Jeff Marks, portfolio director at the CNBC Investing Club, summed up the sentiment: “Capex trends are going to be the number one focus.” The emphasis for investors will increasingly be on these companies’ ability to generate an adequate return on their massive AI investments, rather than just their capacity to spend.
This shift could redefine how Wall Street evaluates the long-term viability and financial health of the sector’s biggest players.