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Wait Out AI Hyperscalers' False Start

Source: bloomberg.com

TL;DR

Merryn Somerset Webb argues investors should avoid AI hyperscalers amid their flawed build-heavy model.[[1]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money?embedded-checkout=true)[[2]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money)
Hyperscalers like Microsoft and Amazon plan $650-700 billion in 2026 capex, much via debt for data centers.[[3]](https://www.bloomberg.com/news/articles/2026-02-06/how-much-is-big-tech-spending-on-ai-computing-a-staggering-650-billion-in-2026)[[4]](https://futurumgroup.com/insights/ai-capex-2026-the-690b-infrastructure-sprint)
This super-spending risks massive capital misallocation; better to back firms like Apple that sat it out.[[2]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money)

The story at a glance

Merryn Somerset Webb's Merryn Talks Money newsletter calls the AI boom's current phase a "super-spending false start" driven by hyperscalers such as Microsoft, Amazon, Alphabet, Meta, and Oracle. She questions their aggressive data center investments, likening it to a "build, build, build" model that relies heavily on debt and may overbuild for large language models' (LLMs) limited reliability. This comes as new earnings season starts, with hyperscalers reporting capex plans topping $650 billion for 2026 amid doubts over returns.[[1]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money?embedded-checkout=true)[[3]](https://www.bloomberg.com/news/articles/2026-02-06/how-much-is-big-tech-spending-on-ai-computing-a-staggering-650-billion-in-2026)

Key points

Article opens by questioning trust in LLMs accurate only 98% of the time, tying this to what investors need from AI versus what it delivers so far.[[1]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money?embedded-checkout=true)
Hyperscalers' massive data center spending—projected at $660-690 billion combined in 2026 by top five firms—could be "one of the greatest misallocations of capital of all time," much funded by debt issuance surging to $230-240 billion this year.[[5]](https://www.cnbc.com/2026/02/23/big-techs-ai-bond-binge-shatters-unspoken-contract-with-investors.html)[[4]](https://futurumgroup.com/insights/ai-capex-2026-the-690b-infrastructure-sprint)
Buildout faces physical limits like power and labor shortages; not all announced projects advance, with delays common.[[6]](https://qz.com/ai-capex-spending-thinking-machines-yann-lecun-power)
Webb suggests skipping heavy spenders for those that "sat out the super-spending," naming Apple, criticized last year for slow AI entry but now positioned better.[[2]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money)

Details and context

Webb frames AI investment hype around three doubts: LLMs' error rates make them unreliable without human checks, current models demand huge compute that may not scale efficiently, and hyperscalers' debt-fueled capex outpaces free cash flow—90% of operating cash in some cases, up from historical 40% averages.[[7]](https://www.linkedin.com/posts/tomasztunguz_for-every-dollar-hyperscalers-earn-from-ai-activity-7439817189819514880-y7fn)

This echoes past tech booms like dot-com, where capex peaked relative to GDP before busts, though today's hyperscalers start from profitable bases. Power constraints hit hard: data centers could claim 8% of US electricity by 2030, with half of 2026 projects stalled.[[6]](https://qz.com/ai-capex-spending-thinking-machines-yann-lecun-power)

Key quotes

"Given the flaws of a build, build, build-business model, hyperscalers may be the wrong place for your money right now."[[1]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money?embedded-checkout=true)

"The massive spending by the hyperscalers (much of it via debt) on giant data centers might be one of the greatest misallocations of capital of all time."[[2]](https://www.bloomberg.com/news/newsletters/2026-04-04/waiting-out-ai-s-super-spending-false-start-merryn-talks-money)

Why it matters

Hyperscalers' AI bet reshapes global capital flows, pulling resources into infrastructure at the cost of other sectors and straining energy grids. Investors face risks if returns lag capex, hitting stock prices and bondholders, while sidelined firms like Apple gain if the frenzy cools. Watch Q1 2026 earnings for capex guidance revisions and AI revenue traction, though power bottlenecks could force cuts regardless.[[3]](https://www.bloomberg.com/news/articles/2026-02-06/how-much-is-big-tech-spending-on-ai-computing-a-staggering-650-billion-in-2026)