The core question
AI cloud spending is profitable only if expensive infrastructure stays highly utilized and customers pay enough to cover chips, power, networking, depreciation, and support.
Cloud capex, GPU clusters, data centers, depreciation, and utilization.
AI cloud spending is profitable only if expensive infrastructure stays highly utilized and customers pay enough to cover chips, power, networking, depreciation, and support.
GPU utilization, data-center buildout speed, depreciation schedules, enterprise AI workloads, and whether AI demand is incremental or replacing older cloud workloads.
Track capex guidance and compare it with cloud revenue growth. If spending grows faster than revenue for too long, margins can compress.
Are hyperscalers spending faster than AI revenue can catch up?
Who profits when everyone else buys GPUs?
Can software margins survive expensive inference?
Why fast revenue can still hide dangerous compute burn.
When do autonomous agents actually save money?
Which AI consumer apps can keep paid users?
Will AI answers grow or shrink advertising revenue?
Free models are not free to run.