The AI trade is broadening, not breaking
This week’s softness in XLK is feeding the usual bubble chatter, but the more important shift is happening underneath the surface: AI spending is spreading beyond chips into networking, power, cooling, and data-center real estate. Nvidia’s latest results reinforced that capex is still durable; the debate now is where the next dollars in the stack get earned.
The cleanest read on this week’s AI wobble is not that the trade is cracking. It is that the market is finally pricing AI as a full infrastructure buildout rather than a one-stock phenomenon. Nvidia just posted $81.6 billion in quarterly revenue, including $75.2 billion from data center, and management still described demand as running at an unprecedented pace. If the capex engine is still that strong, the more useful question is not whether AI spending is over, but which parts of the stack become the next bottlenecks — and therefore the next beneficiaries.
That is why XLK lagging SPY this week matters less than the composition of leadership. When a theme matures, returns stop looking as clean as a single-ticker momentum trade. They rotate into the companies that make the core product deployable at scale. In AI, that means the spend is moving from pure compute toward the physical and network layers that let compute work in the real world: switches, power distribution, thermal management, and the buildings that can actually host dense clusters.
The macro constraint is not subtle anymore. U.S. data-center power demand is projected to rise from 31 GW in 2025 to 66 GW in 2027, and another widely cited estimate sees demand reaching 74 GW by 2028 with a 49 GW shortfall in available power access. That is the broadening thesis in one frame. If chips were the only scarce input, the bubble argument would have more force. But when the limiting factors become electricity, cooling, and siting, the value pool necessarily spreads beyond NVDA
