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Technology research

AI capital spending moves into the physical stack

Compute demand now reaches semiconductors, power equipment, cooling, networks and construction capacity.

Core thesis

The investable AI chain is broadening. The scarce inputs are no longer only accelerators, but also power, cooling, network capacity and construction execution.

What the evidence says

01

Microsoft said calendar-year 2026 capital expenditure could reach about US$190 billion, while capacity remains constrained.

02

TSMC reported US$40.2 billion of Q2 2026 revenue and a 67.7% gross margin, with Q3 revenue guidance of US$44.6-45.8 billion.

03

The IEA identifies data centers, advanced manufacturing and electrification as renewed drivers of electricity demand in advanced economies.

Portfolio implication

Own the bottlenecks, but require visible order books, pricing power and funded expansion plans. Avoid treating all AI-adjacent capital spending as equivalent.

What would change our view

Faster efficiency gains reduce compute demand

Grid interconnection delays defer revenue

Capital intensity compresses free cash flow

Primary sources

Public facts are linked to primary sources. Portfolio weights and return assumptions are illustrative.