Morgan Stanley has for the first time produced a complete map of where AI capital expenditure will flow by 2027, revealing a highly concentrated profit structure: of the $1.58 trillion in spending by hyperscale cloud providers, roughly two-thirds of the S&P 500 benefit amount flows to a single company, NVIDIA Corp (NVDA), while the other 499 index constituents together receive only about $339 billion.
Morgan Stanley strategists Nick Lentini, Mike Wilson and more than twenty industry analysts jointly published the report "Tracking the $1.6 Trillion AI Capital Flow: Mapping the Revenue Created by the Capex Boom," the first attempt to trace hyperscaler capital expenditure line by line into individual companies' income statements. The report's central conclusion: AI capital expenditure will directly drive roughly 25% of S&P 500 sales growth, and AI-related companies will contribute 78% of the index's earnings growth in 2027.
The report also exposes a long-overlooked hidden risk: hyperscalers have disclosed more than $1.1 trillion in lease commitments that have been signed but not yet commenced. This "synthetic capital expenditure" does not appear under the capex line of any cash flow statement, yet is economically equivalent to debt financing. Morgan Stanley credit strategists expect 2027 to be the year of the largest free cash flow deficit for hyperscalers, when debt financing pressure will rise significantly.
The Full Picture of $1.6 Trillion
The core of the Morgan Stanley report is a Sankey diagram that traces the combined $1.58 trillion in 2027 spending from nine major buyers — Alphabet, Amazon AWS, Microsoft, Meta, the lease pool, SpaceX, Oracle Corp (ORCL), CoreWeave and Nebius — layer by layer into semiconductors and servers, networking and optics, data center infrastructure, storage and international suppliers, ultimately landing on specific stock tickers.
Among the nine buyers, semiconductors and servers represent the single largest spending category, absorbing $672 billion, the vast majority of which flows to NVIDIA Corp (NVDA). The second-largest category is "international" suppliers at $511 billion, covering Samsung, SK Hynix, TSMC-related infrastructure and Taiwanese ODM manufacturers, none of which are S&P 500 constituents.
The report also notes that the entire map converts $1.6 trillion in capital expenditure into roughly $1.7 trillion in supplier revenue, with the gap arising from private emerging cloud providers and bitcoin miners disrupting customer splits, timing differences, and supplier price increases not yet reflected in capex forecasts. Morgan Stanley's interpretation: the next round of capex upgrades is already embedded in supplier models.
Nvidia Takes Two-Thirds Alone, the Other 499 Split the Remainder
Of the roughly $1.03 trillion in revenue that the S&P 500 absorbs from AI capital expenditure, 67% flows to NVIDIA Corp (NVDA), approximately $690 billion — equivalent to 44% of the entire $1.58 trillion capex budget landing on one company's income statement. Excluding Nvidia, the entire AI capex boom contributes only 1.6% to S&P 500 sales.
Roughly broken down: about $700 billion goes to NVIDIA Corp (NVDA), about $340 billion is shared among the other 499 S&P constituents, and another roughly $550 billion flows outside the index to Korean memory manufacturers, Taiwanese ODMs and various private companies.
At the individual stock level, Morgan Stanley examined the proportion of each company's 2027 revenue tied to AI infrastructure buildout. NVIDIA Corp (NVDA) leads at 91.7%, followed by Erock at 91%, Vertiv at 90%, Applied Opto at 83%, Broadcom Inc (AVGO) at 81% and Bloom Energy at 80%. Even Caterpillar Inc (CAT) has 21% of revenue tied to AI capex trends, while Seagate Technology Holdings PLC (STX) and Western Digital Corp (WDC) both reach 60%.
This structure means that for at least a dozen large companies, "AI capital expenditure" and "revenue" are almost synonymous — adding icing on the cake on the way up, and on the way down, any capex revision will translate directly into earnings revisions, with no other business to buffer.
The $195 Billion in Hidden Liabilities
One of the report's most important methodological adjustments is incorporating leases into capex statistics. Morgan Stanley used companies' disclosed signed-but-not-yet-commenced leases, analyst forecasts for new capacity, and the lease capex ratio per gigawatt of new capacity to add $195 billion to 2027 capex and $246 billion to 2028 capex.
This raises total 2027 AI capital expenditure from $1.39 trillion (cash capex) to $1.58 trillion, a year-on-year growth rate of about 60%; for 2028, it rises from $1.57 trillion to $1.81 trillion.
In terms of lease scale, Oracle Corp (ORCL) leads at $57 billion, followed by Microsoft at $45 billion, Meta at $37 billion, Amazon at $28 billion and Alphabet at $27 billion. As of the second quarter of 2026, the pipeline of signed-but-not-yet-commenced leases had swelled to $1.118 trillion, more than doubling in just two quarters, with Microsoft at $329 billion, Oracle Corp (ORCL) at $288 billion and Meta at $279 billion as the main signatories.
Morgan Stanley's qualitative judgment: leasing data centers is economically identical to debt-financed capital expenditure, merely bypassing the GAAP capex line item.
Debt: The Underestimated First Link
Morgan Stanley credit strategists Fernanda Lima and Vishwas Patkar expect free cash flow at hyperscalers and emerging cloud providers to hit its most negative level in 2027, with the funding gap growing even larger when lease payments are included.
Hyperscalers have issued about $255 billion in unsecured bonds year to date, roughly 30% of their estimated 2026 capital expenditure, led by Amazon at $98 billion and Alphabet at $81 billion, while composite yields have risen 100 to 180 basis points since the start of the year. Oracle Corp (ORCL) 10-year bond spreads have widened the most, by 180 basis points.
Morgan Stanley's stress test shows that if AA-rated hyperscalers issue $400 billion in bonds at a 7% rate, interest coverage would fall from 30.7 times to a still comfortable 11.9 times; but if Oracle Corp (ORCL) and SpaceX raise $120 billion at 8.5%, their combined interest coverage would plunge from 4.0 times to 1.8 times.
The report explicitly states that emerging cloud providers are the most dependent on debt financing, "relying almost entirely on debt issuance to support their capital expenditure ambitions." Days before the report was published, CoreWeave shares had already fallen sharply, and the company corresponds to $47 billion in spending on Morgan Stanley's capex map.
Slowing Growth and the "Power Wall"
Morgan Stanley expects AI capital expenditure growth to slow sharply from about 60% in 2027 to about 14% in 2028. Against this backdrop, the report screens for names that still have pricing power when capex growth decelerates, with power equipment dominating, alongside storage, hard drives and cooling equipment.
Power supply is another structural constraint. Morgan Stanley's own "AI power supply" model shows that even accounting for various rapid power delivery solutions (covering 34% of the 97GW needed), the United States still faces a net shortfall of 32GW before 2028, widening to about 72GW before 2029. The report characterizes this as a timing mismatch rather than a demand collapse, but notes that storage, networking, optics and ODM construction are most sensitive to power supply pauses.
On downside risk, Morgan Stanley is unusually blunt: there is currently a "fear of missing out on procurement" mentality, with buyers snapping up at high prices today because they expect even higher prices tomorrow. Once supply catches up with demand, this logic reverses. The report cites the 2022 NAND memory cycle as an example — shipments fell only about 5%, but prices dropped 20% to 30% — and concludes: "We believe the market is currently underestimating the risk of simultaneous volume and price declines."
Morgan Stanley's report provides the market with the first dollar-by-dollar map of AI capital expenditure flows, clearly showing that roughly 25% of S&P 500 sales growth and 78% of earnings growth depend on a $1.6 trillion capital expenditure budget — and within that budget, two-thirds of the index-level benefit is concentrated in a single company, with an ever-larger share supported by leases that do not count as capital expenditure and by debt that will only become visible when it needs refinancing.
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