70% of companies say they use AI. Fewer than 1 in 10 have an actual agent running in production.

That gap sits inside Stanford's AI Index, the most cited, least biased dataset on AI that exists, not published by a lab with a stake in the outcome.
Google alone spent over $150 billion on AI infrastructure last year. Frontier lab revenue is climbing at historic rates, and compute spend is climbing right alongside it, not shrinking as a share of revenue the way infrastructure normally does once something scales.
Adoption was never the bottleneck. The bottleneck is running a workload that never stops, checking tools, taking actions, holding state, without a cost structure that eats the revenue before it compounds. That's an infrastructure problem, not an intelligence problem, and it's why 70% adoption is producing single-digit deployment.
The gap between those two numbers is the market nobody has built the infrastructure for yet.