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AI compute demand structurally outruns power supply.

78/100 conviction▲ +4 strengtheningUpdated 8 Jul 2026

For two years the constraint on AI was compute — whoever had the GPUs won. That era is ending. Capital is now colliding with physics: you can order the chips, you can’t order the power. Hyperscaler capex is scaling faster than grids can deliver interconnection, and the binding constraint is migrating off silicon onto the unglamorous hardware that energises a data centre — transformers, switchgear, substations.

What’s driving it

The bear case

The same capex is cash-funded by trillion-dollar balance sheets, and supply is responding — capacity expansions and Chinese transformer imports as easing vectors. Hyperscalers can also sidestep the grid queue via on-site generation (bring-your-own-power).
What would prove us wrong: transformer lead times contracting below ~80 weeks within 12 months; a material cut to hyperscaler capex guidance; or the power-constraint story failing to reappear in a second independent quarter.

Where the exposure sits

Companies described by what they do in the affected layer — not securities we’re selecting, and nothing here is a buy or sell.

Sources: Microsoft FY26 Q2 (Investor Relations); Wood Mackenzie Q2 2025 transformer lead-time survey (pv-magazine, POWER Magazine); 2026 hyperscaler capex aggregation (Tom’s Hardware, CNBC).

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INFLCT publishes macro awareness, not financial advice. Conviction scores reflect our own structural positioning — not price targets — and are not a recommendation to buy or sell any security. Do your own research.
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