#
Is the AI hype
cooling down?
A composite reading of physical build-out and platform economics. Higher means the expansion is still intensifying; lower means the momentum is fading. Here's what goes into it.
See the breakdown
What the answer is built from #
Five independent signals, each weighted by how directly it reflects real, committed demand. Each is scored from 0 (contracting) to 100 (surging).
The trajectory #
Where the money and the megawatts are actually going.
Combined infrastructure spend, per quarter
Billions of dollars### Spend by operator
$B / quarter### New data-center power queued
Gigawatts / year### Total new power capacity queued
Gigawatts / year### Where data-center load is landing
GW in queue, top regions## The latest print
The charts above stop at the March quarter. Alphabet is the first hyperscaler to report the June quarter, and the print did nothing to suggest a cooldown: cloud revenue up 82%, quarterly capex roughly doubled, and full-year capex guidance raised again. Microsoft and Meta report July 29 and Amazon July 30, so this section fills in as each one lands.
Total revenue
$119.8B
+24% vs last year
Google Cloud revenue
$24.8B
+82% vs last year
Cloud operating income
$8.8B
up from $2.8B a year ago
Capex, this quarter
$44.9B
~+100% vs last year
Operating income
$40.8B
+30% · 34% margin
2026 capex guidance
$195–205B
raised from $180–190B
One caveat on the headline: reported net income leapt to $112.1B and diluted EPS to $9.11 (both up roughly 295%), but that is flattered by a one-time $99B unrealized gain on equity investments, booked below the operating line. Operating income ($40.8B, +30%) is the clean read on the business. The two figures that matter most for this page, cloud growth and capex, both accelerated. Source: Alphabet Q2 2026 earnings release (quarter ended Jun 30, 2026), reported Jul 22, 2026.
Funding the build-out #
The spending is enormous, but is it being paid for out of pocket or on credit? The cash-flow statements answer that. Between them the five operators throw off about $649B of operating cash a year and are now plowing roughly three-quarters of it straight back into capex. The giants still generate tens of billions in free cash flow after they spend; but at the frontier the build has overtaken the cash, and Amazon and Oracle are now spending more than they earn, filling the gap from reserves and debt.
Operating cash flow, capex & free cash flow, combined
$B · fiscal years 2020–2025Summed across all five operators. Operating cash flow keeps hitting records, but capex is accelerating faster: combined free cash flow peaked near $246B in 2024 and slipped to about $198B in 2025 even as operating cash flow set a high, and the latest snapshot (~$159B TTM) extends that slide.
Snapshot view: trailing twelve months from the operators’ cash-flow statements. History view: annual fiscal-year figures combined across the five (2021–2025 from filings via stockanalysis.com, 2020 from company 10-Ks). Free cash flow here is simply operating cash flow minus purchases of property and equipment; companies’ own free-cash-flow measures differ (Amazon and others adjust for equipment finance leases, which also means all-in capex runs higher than the cash figure shown), and Amazon’s capex mixes AWS with retail logistics. Fiscal years are offset for Microsoft (ends June) and Oracle (ends May); snapshot periods end Mar 31, 2026 except Oracle (May 31, 2026). Illustrative, not investment advice. Sources: company 10-Q / 10-K cash-flow statements via stockanalysis.com (2020–2026).
The picks and shovels #
The hyperscalers get the headlines, but the chipmakers, memory houses and foundries behind them are in a capex super-cycle of their own, together laying out well over $130B a year to build the fabs, HBM lines and tools the AI build-out physically runs on. Trace that capital back through their filings and you can see exactly how the build-out got here.
The multi-year climb in chip capex
Annual capex, $B · 2019–2025One line per filing trail (10-K / 20-F / 6-K). Memory (SK Hynix, Micron) shows the deep 2023 downturn cut and then the HBM-driven surge; TSMC keeps setting records; Intel is the one line bending down, pacing its foundry build to demand.
Annual capital expenditure compiled from company filings (10-K / 20-F / 6-K and quarterly reports); the latest point is FY2025 guidance, earlier points are reported actuals, converted to USD at period rates. Fiscal years and treatment differ (Micron’s ends in August; Intel’s figures are gross additions, before the partner offsets and CHIPS grants that lower net capex materially). “Samsung” is its semiconductor (DS) division. CXMT only began reporting publicly with its July 2026 Shanghai listing, so its bar is the 2026 equipment-procurement plan rather than an audited capex history, and it is absent from the 2019–2025 chart above for the same reason. Two kinds of company carry small capex by design and should not be read as small spenders: equipment makers, whose revenue is the mirror of everyone else’s capex, and fabless designers (AMD, Broadcom, Nvidia), who buy foundry capacity instead of building it, so R&D is the figure that matters and their volume lands on TSMC’s capex line. Illustrative, not investment advice. Sources: company filings & investor releases (2019–2025).
The sovereign money #
It isn't only US hyperscalers writing the checks anymore. Governments and sovereign wealth funds now treat AI compute as strategic infrastructure, and have pledged hundreds of billions to build it, buy into it, or avoid being left behind. Here's who's committing what, and how each region's playbook differs.
Headline announcements, not deployed cash, a mix of state programs, sovereign wealth funds and public-private ventures, so they aren't strictly comparable (European figures overlap; * South Korea's cluster runs to 2047). Illustrative, not investment advice. Sources: government announcements, Global SWF, IEA and press reporting (2024–2026).
Where it could actually jam #
Demand is only half the story. Even with the money flowing, the build-out slams into hard limits, from the accelerator itself (a market chokepoint as much as a physical one), through raw silicon and the machines that pattern it, packaging, passives, optics and the network fabric, out to water, power, the skilled trades who build it, and the export politics that can throttle any link overnight. Here's how binding each chokepoint becomes year by year through 2030, and the companies with the most leverage over it.
Company names indicate supply-chain exposure to each bottleneck, illustrative, not investment advice. Trajectory synthesized from IEA, McKinsey, SemiAnalysis, TrendForce, Yole, SK Group and industry commentary (2024–2026).