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Magnificent Seven Step Up AI Infrastructure Spending, but Only Microsoft, Nvidia and Apple Expected to Grow Free Cash Flow

4 reports · First detected 2026-02-24 · Last active 2026-06-30

Free cash flow is the money left after capital expenditure that companies can use to repay debt, buy back shares and reinvest. It is also a key measure of whether AI investment can translate into shareholder returns. Evercore ISI estimates that capital spending by the Magnificent Seven and Oracle, as a share of operating cash flow, rose from no more than 40% over the previous three years to nearly 50% in 2025 and will exceed 60% in 2026–2027.

Evercore ISI estimated on February 17, 2026, that AI capital expenditure would total about $650 billion over the next 12 months, with Amazon’s full-year capital spending reaching $200 billion. Its latest report on February 23 further forecast that free cash flow at Amazon, Alphabet and Meta would decline year on year in 2026. Only Microsoft is expected to post growth of 5%, while Nvidia and Apple could deliver double-digit increases.

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Big Tech Boosts AI Spending as Free Cash Flow Comes Under Pressure2026-08-01 · 3 reports · similarity 0.81

Amazon, Microsoft, Alphabet and Meta have made data centers, advanced AI chips and power infrastructure central to their push into generative artificial intelligence. The buildout is expanding computing capacity and supporting cloud growth, but it is also extending investment payback periods. That has shifted investor attention from the scale of AI ambitions to capital efficiency and the companies’ ability to convert new capacity into sustainable revenue and free cash flow.

The four U.S. cloud giants have spent more than $1.1 trillion in aggregate since the AI investment cycle began and are expected to commit about $745 billion in 2026, largely to data-center construction and advanced chip purchases. Despite mounting pressure on near-term free cash flow, the companies plan to keep increasing investment in the second half of 2026 and over the coming quarters, putting greater scrutiny on utilization, AI revenue growth and returns on capital.

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