AI is not an app cycle. It is an infrastructure supercycle — and like railroads, electrification and the internet before it, the money goes to whoever owns the physical layer. This report names the layer: Compute, Data and Energy, and seven companies positioned at the centre of it.
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Training and running AI requires large data centres, advanced chips, high-speed networks and massive amounts of electricity. Software captured the last cycle's value. This one shifts it back to the people who own the hardware, the data and the power.
The chips and hardware that process AI workloads — and the one company whose machines every advanced chip on earth is made on.
The fuel that trains the models and gives them decision-making capability — and who is already paid to organise it for governments and enterprises.
The hidden bottleneck. Data centres need power that is reliable, dense and constant — which is why nuclear is back in the conversation.
Not a list of tickers — each name is placed in the Power Triad and argued for: what it controls, why that control gets more valuable as AI scales, and what would make the thesis wrong. One is below; the rest are in the report.
Why demand for AI compute is outrunning supply — and who else benefits.
The company every advanced semiconductor on earth depends on.
Turning raw data into decisions for governments and the Fortune 500.
Small modular reactors and the uranium that feeds them.
Every new model is a new attack surface.
The seventh pick and the reasoning behind all of them.
Armando's private research desk and investor community — live with him every Monday, every call on the public record, and the full reasoning behind every position.
Join the CNCEducational and informational only. Nothing on this page or in the report is personalised investment advice, an offer, or a recommendation to buy or sell any security. Armando Pantoja and members of the CNC may hold positions in companies discussed. Past performance is not indicative of future results. Do your own research.