AI supply-chain thesis — mapping bottlenecks, focus companies, and supply-chain exposure for investors.
**Bottleneck theme:** Power & Grid **Focus:** $GEV — GE Vernova Inc. GE Vernova is one third of the global gas-turbine triopoly (with Mitsubishi Power and Siemens Energy) and is sold out on F-class and HA-class turbines through 2030. The AI-driven gas-build cycle is the strongest in two decades — hyperscalers and IPPs are ordering combined-cycle gas plants as the only credible path to multi-GW dispatchable power inside 4-5 years (vs 8-12 for nuclear). Beyond gas turbines, GEV's grid franchise (Hitachi Energy partner, transformers, HVDC) and wind business round out a full electrification platform. The investment case is multi-year backlog visibility on gas, plus growing optionality in nuclear (SMR-class BWRX-300 with Hitachi), HVDC transmission (the long-haul renewables and AI-load enabler), and grid software. The bear case is gas-cycle digestion if hyperscaler capex resets, persistent execution issues in the wind segment, and a multiple that has rerated significantly since the spin-off. Pair with $ETN, $HUBB, $POWL on the upstream electrical side and $VST/$CEG/$TLN on the customer/utility side.
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