Is artificial intelligence investment starving other industries of critical resources?
Core argument: Tech capex surged 30% vs. year-ago while non-tech investment fell, driving a 56 pts outperformance of semiconductor stocks over hyperscaler.
Overall tech-related investment increased 30% from year-ago levels, while all other capex fell. This record divergence implies that the AI boom is bidding away physical inputs – electricians, grid capacity and transformers, metals and materials, engineering talent, and construction labor – in quantities that stress the economics of rival projects elsewhere. Perhaps the best illustration of binding real resource constraints was observed inside the AI data center complex itself. In the first half of the year, the average price of semiconductors, labor for assembly and integration, and related materials exploded, as physical supply constraints interacted with insatiable demand. As more economic rent accrued to the compute layer, the stock prices of the semiconductor manufacturers upstream from this physical chokepoint outperformed those of their top customers by 56%. When AI spending gets financed out of internally generated cash flow, “crowding out” isn’t a pressing issue for investors. Credit spreads have not widened materially, financing conditions remain accommodative, and the cost of capital for non-software borrowers doesn’t suggest displacement. But the hyperscalers’ free cash flow has now been exhausted. Over 80% of the projected capex over the next few years will have to be externally financed, including fresh equity issuance.

