This is a brilliant report. The State of the AI Economy by @exponentialview

- $110B real AI revenue over 12 months, after removing double-counting. so $1 spent on Claude is counted once, even if part of it later flows to Amazon or another infrastructure provider.

- $175B current annualized run rate, showing fast acceleration. Measured by end-customer spend, not supply-chain pass-through revenue. Excludes China, internal AI savings, ad uplift, consulting, and systems integration.

- Growth running roughly 3x faster than mobile or internet adoption waves.

- The pace of revenue formation has sharply accelerated. New $1B revenue now arrives in under 2 days, versus 180 days in 2023.

- Enterprise AI has moved beyond pilots, but deep company-wide rollout is still early.

- AI earnings-call mentions reached 31% of tracked S&P 500 firms.

- Only 20% of tracked firms made quantified AI impact claims.

- Hyperscaler AI revenue roughly covers AI infrastructure depreciation for now. GPU economics depend heavily on 6-year compute life assumptions.
Other AI infrastructure gets modeled over 14 years.

- Token price cuts do not automatically reduce revenue.

- Every 10% token price cut drives 12-18% more token usage.

- AI demand looks price elastic, meaning cheaper AI expands usage faster than prices fall.

- Power availability and data-center costs remain major limits on future scaling.