Morgan Stanley pegs 2027 AI spending at US$1.58T
Treating leases as capex materially inflates measured AI investment and shifts scrutiny onto off-balance-sheet financing structures that most revenue models ignore. The supplier split also shows how much of the spending leaks beyond US-listed names to Korean memory and Taiwanese hardware manufacturers. Investors tracking AI capex sustainability, and neocloud credit risk in particular, get a clearer map of where the financing strain concentrates.
Morgan Stanley projects 2027 hyperscaler and neocloud AI spending at US$1.58 trillion once data-center leases are counted as capex. Hyperscalers hold over US$1.1 trillion in leases that have not yet begun, which function like debt-funded purchases but never appear as capex. About 65% of the 2027 total, roughly US$1.03 trillion, lands in S&P 500 revenue, with Nvidia capturing about US$690 billion, or 44% of the entire budget. Roughly US$340 billion goes to the other 499 index members, while about US$550 billion flows outside the index to Korean memory makers, Taiwanese ODMs and private companies. With 2027 projected as the peak cash shortfall year, GPU-rental neoclouds funding builds through project debt and convertibles face the highest financing-cost exposure.
Morgan Stanley puts 2027’s hyperscaler and neocloud AI spending at $1.58T after counting data-center leases as capex.
Hyperscalers hold over $1.1T in leases that haven’t begun, which work like debt-funded purchases but never appear as capex.
About 65% of the 2027 total, roughly $1.03T, lands in S&P 500 revenue, and Nvidia takes about $690B of it, or 44% of the entire budget.
That leaves roughly $340B for the other 499 index members, while about $550B flows outside the index to Korean memory makers, Taiwanese ODMs and private companies.
With 2027 the projected peak cash shortfall, GPU-rental neoclouds funding builds through project debt and convertibles are the most exposed to financing costs.
