Industry View · Cooling & Electrical
The bottleneck in artificial intelligence has migrated from chips to the unglamorous physical layers beneath them: thermal management and electrical distribution. Data-center electricity use jumped 17% in 2025 and high-power transformer lead times now stretch to as long as five years, turning cooling and electrical suppliers into the gatekeepers of the AI build-out.
All capex/backlog/chokepoint; build-out and pricing power, no demonstrated AI ROI
High-power transformer lead times have blown out from 24-30 months pre-2020 to as long as five years, with costs up 70-100% by 2025 — the hardest physical constraint on AI build-out.
Switchgear, UPS and busway makers are co-designing reference architectures with NVIDIA, collapsing the boundary between the substation and the rack.
At 120kW+ per rack, direct-to-chip and immersion cooling shift from niche to mandatory; the segment is the fastest-growing layer of the AI stack.
Reinforcement-learning controllers tune chillers, pumps and setpoints in real time — DeepMind cut Google's cooling energy ~40% — turning cooling itself into an AI workload.
Waterless and warm-water designs plus heat-reuse are emerging as siting and sustainability differentiators as water and power permits tighten.
01 · The thesis
For two years the AI trade was about GPUs. In 2025-2026 it is about whether you can power and cool them. NVIDIA's GB200 NVL72 rack draws roughly 120kW and ships with no air-cooled variant — direct-to-chip liquid cooling is mandatory, not optional. That single architectural fact has converted thermal management from a facilities line-item into a strategic chokepoint, and pulled an entire electrical supply chain — transformers, switchgear, UPS, busways — into multi-year backlog. The scarce input is no longer compute; it is the grid interconnect and the equipment that conditions power on its way to the chip. The IEA reports wait times for transformers and cables have doubled in three years, and analysts warn a meaningful share of planned 2026 data-center projects face delay or cancellation for lack of electrical hardware. In that world, the companies that make CDUs, cold plates, medium-voltage switchgear and grid transformers hold pricing power that the chip-buyers do not.
High-power transformer lead times have blown out from 24-30 months pre-2020 to as long as five years, with costs up 70-100% by 2025 — the hardest physical constraint on AI build-out.
Switchgear, UPS and busway makers are co-designing reference architectures with NVIDIA, collapsing the boundary between the substation and the rack.
At 120kW+ per rack, direct-to-chip and immersion cooling shift from niche to mandatory; the segment is the fastest-growing layer of the AI stack.
Reinforcement-learning controllers tune chillers, pumps and setpoints in real time — DeepMind cut Google's cooling energy ~40% — turning cooling itself into an AI workload.
Waterless and warm-water designs plus heat-reuse are emerging as siting and sustainability differentiators as water and power permits tighten.
02 · The two clocks
The interconnect clock. Average grid-connection wait times in primary data-center markets now exceed four years, and Microsoft has acknowledged GPUs sitting idle in inventory because it cannot find electricity to power them. Compute is no longer the binding constraint; the wire is. The transformer clock. Lead times for high-power transformers have stretched from 24-30 months before 2020 to as long as five years, with costs up 70-100% by 2025. Analysts warn that more than half of some 2026 U.S. data-center plans risk delay or cancellation for lack of electrical equipment. The thermal clock. New greenfield AI builds in 2025-2026 are specifying 250-400kW per cabinet row as baseline. Direct-to-chip and immersion cooling are projected to grow from roughly $5.3B in 2025 to over $32B by 2032 — the fastest-compounding physical layer of the stack.
03 · Public players & exposure
We plot the listed players on two editorial axes — how exposed each is to AI disruption, against how ready its data, brand and position are to be the answer. The figures in the table are sourced; the placement is our read.
04 · Private flagships
The companies attacking this industry AI-first, with disclosed funding where available:
The clearest pure-play on AI's physical layer, spanning UPS, busway, CDUs and liquid cooling; liquid-cooling revenue is guided to ~40% CAGR through 2028.
Partnered with NVIDIA on the Beam Rubin DSX grid-to-chip platform and raised incremental capacity investment to ~$1.5B for transformers, switchgear and distribution.
Used the early-2025 Motivair deal to bolt a credible liquid-cooling portfolio onto its dominant electrical-distribution franchise, betting on design lock-in.
Owns one of the scarcest inputs in the chain; its electrification backlog has more than quadrupled in four years and is set to double again by 2028.
Strategic-investor-backed challenger pushing dielectric two-phase direct-to-chip cooling that roughly halves cooling energy and removes water from the loop.
British precision-liquid specialist positioned for the density classes where direct-to-chip alone struggles; highest-funded pure-play cooling startup.
05 · Signals
06 · The exposure read
AI rewards clean, structured advantage and punishes friction. The line runs through who owns the data, the brand and the customer — and who is merely a step the technology can route around.
Sources
AI infrastructure backlogs: contracted demand the suppliers can already see
Disclosed order backlogs / contracted figures, end-2025 to Q1-2026. Sources: Vertiv, Eaton, GE Vernova investor disclosures. (USD billion)
Liquid cooling crosses from optional to mandatory
NVIDIA's GB200 NVL72 ships with a pre-plumbed liquid manifold and no air-cooled variant at ~120kW/rack, forcing the chassis and facilities ecosystem to pivot.
Transformer scarcity becomes the build-out's hard ceiling
IEA flags transformer and cable lead times doubling in three years; high-power units now quoted at up to five years against sub-18-month AI deployment cycles.
Electrical orders go vertical
Eaton data-center orders up ~200% in Q4 2025; GE Vernova's Q1-2026 data-center orders alone exceed its entire 2025 total; Vertiv Q4 orders up 252%.
Strategic capital floods cooling startups
ZutaCore raises $100M+ from Mitsubishi, Carrier and Samsung; incumbents (Schneider/Motivair) buy rather than build to close the thermal gap.
Power, not silicon, gates deployment
Hyperscaler capex approaches ~$650B with grid-connection waits over four years; Microsoft admits idle GPUs waiting on electricity.
The clearest pure-play on AI's physical layer, spanning UPS, busway, CDUs and liquid cooling; liquid-cooling revenue is guided to ~40% CAGR through 2028.
Partnered with NVIDIA on the Beam Rubin DSX grid-to-chip platform and raised incremental capacity investment to ~$1.5B for transformers, switchgear and distribution.
Used the early-2025 Motivair deal to bolt a credible liquid-cooling portfolio onto its dominant electrical-distribution franchise, betting on design lock-in.
Owns one of the scarcest inputs in the chain; its electrification backlog has more than quadrupled in four years and is set to double again by 2028.
Strategic-investor-backed challenger pushing dielectric two-phase direct-to-chip cooling that roughly halves cooling energy and removes water from the loop.
British precision-liquid specialist positioned for the density classes where direct-to-chip alone struggles; highest-funded pure-play cooling startup.
| Company | Stance | The sourced fact |
|---|---|---|
| Vertiv Holdings VRT | Category leader | Posted $10.2B revenue in 2025 (+28% YoY) and ended the year with a $15B order backlog, Q4 orders up 252% YoY; liquid-cooling revenue more than doubled in Q1 2025. |
| Eaton ETN | Grid-to-chip play | Record 2025 sales of $27.4B; data-center revenue grew ~40% in Q4 with orders up ~200%, and Electrical Americas backlog hit a record $13.2B. |
| Schneider Electric SU.PA | Design lock-in | Acquired control of Motivair in early 2025 and launched an end-to-end liquid-cooling portfolio including a 2.5MW CDU; Motivair tech runs in six of the world's top-ten supercomputers. |
| GE Vernova GEV | Transformer gatekeeper | Called Q4 2025 its largest-ever hyperscaler quarter in Electrification; Q1 2026 data-center orders of $2.4B already exceeded the full 2025 total, with total backlog at $163B. |
| ABB ABBN.SW | MV switchgear | Launched the AI-ready MegaFlex UL 415V UPS for large-scale data centers in June 2025, competing with Eaton in medium-voltage switchgear for AI loads. |
| Hitachi Energy HTHIY | Capacity-constrained | Undertaking 2025-2026 transformer capacity expansions to ease grid-component shortages, including large multi-billion-dollar grid-infrastructure commitments with hyperscalers. |
| ZutaCore PRIV-ZUTA | Two-phase challenger | Raised a $100M+ Series C in 2026 from Mitsubishi Electric, Carrier Ventures and Samsung Ventures (~$600M valuation) for waterless direct-to-chip two-phase cooling. |
| Iceotope PRIV-ICE | Precision liquid | Closed a $26M Series B in 2025, taking total funding to ~$81.4M — the highest-funded pure-play in the data-center cooling-systems category per Tracxn. |
| JetCool PRIV-JET | Microconvective bet | Raised $17M for microconvective direct-to-chip cold plates targeting higher heat-transfer efficiency at the chip surface. |
| Legacy air-cooling OEMs AIR | Stranded architecture | At 120kW+ racks the GB200 reference design has no air-cooling variant, structurally eroding demand for air-only CRAC/CRAH product lines. |