AI spending enters its 'run-rate reality' phase
The investment wave is no longer theoretical it's here in full force. Analysts chart double- and triple-digit growth in infrastructure spending, from hyperscale GPU clusters to private inference stacks. A defining trend emerges: enterprises aren't just experimenting anymore; they're budgeting.
The power shift toward compute and tooling
- A growing slice of budgets now goes directly to GPU capacity, networking fabric, and inference optimization tools, rather than front-end experimentation.
- Investors are increasingly scrutinizing efficiency metrics training cost per parameter, inference cost per thousand tokens as signals of business maturity.
Why investors are still optimistic
Despite cyclic fears, analysts argue the wave is sustained by real operational use cases in productivity tooling, automation workflows, and customer-facing agents. The investment landscape is starting to resemble cloud's early 2010s moment, but with heavier hardware dependencies and far faster iteration cycles.