What is Microsoft's projected capital expenditure for AI?

Microsoft is projected to spend $80 billion on data centers this year for AI infrastructure.

Are Alphabet and Meta's AI investments concerning?

Meta and Alphabet have shown increasing returns on invested capital (ROIC), easing concerns about their AI spending.

Why are hyperscalers like Amazon spending so much on AI?

Hyperscalers are building massive cloud infrastructures to power AI models and handle huge data workloads efficiently.

Home / Business and Economy / Mag 7 AI Spending: Overkill or Growth Engine?

Mag 7 AI Spending: Overkill or Growth Engine?

30 Dec

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Summary

Hyperscalers like Microsoft may exceed $100B AI CapEx by 2026.
Microsoft's current CapEx is projected at $80B for data centers this year.
Meta, Alphabet, and Amazon show rising ROIC, easing spending concerns.

Mag 7 AI Spending: Overkill or Growth Engine?

Major tech companies, including Amazon, Alphabet, Meta, and Microsoft, are facing scrutiny over their substantial AI investments. These hyperscalers are constructing vast cloud infrastructures essential for AI and data-intensive services, a necessity for ultimate speed and accuracy. Investors are questioning if this immense capital expenditure, projected to exceed $100 billion annually for AI infrastructure by 2026, is value-destroying.

Microsoft stands out with an estimated $80 billion in data center spending for the current year, significantly boosting its capital expenditures. However, despite elevated spending, Microsoft's return on invested capital (ROIC) has stabilized around 23%. Encouragingly, Meta, Alphabet, and Amazon have reported increases in their ROIC, with Meta at 29%, Alphabet at 31%, and Amazon nearing 20%.

Amazon's profitability shows a marked improvement, bolstered by positive earnings estimate revisions for fiscal years 2025 and 2026. While Alphabet has also seen strong EPS revision uptrends, its stock price has already reflected this growth. The rising ROIC figures for these companies suggest that the market's fears about their significant AI capital expenditures may be overblown for the time being.