You can see the AI age everywhere but in your P&L. Your team uses it daily. You've paid for the seats. Somebody built an agent. And when you look at output per employee, cycle time, or cost to acquire a customer, the numbers look roughly like last year's. This is not a failure of the technology. It is the same thing that happened to software: in 1987 Robert Solow noted the computer age was visible everywhere except the productivity statistics, and four decades and several thousand SaaS licenses later, the paradox has not been resolved. It has been upgraded. Distributed Intelligence explains why. AI bolted onto a department returns the department's speed, because the constraint was never how fast a task gets done. It was how long a question takes to travel the org chart- roughly a day at every desk it crosses, one to two weeks end to end, versus about a minute when every question goes to one trained intelligence. The book puts a number on that latency, shows where the cost hides in coordination rather than labor, and makes the case for the operating system company: knowledge as infrastructure, decisions the software owns, and the department itself as the application. It closes with a working example- Charlotte, an operating system for marketing, and what it produced. Buy tools and you get tasks back. Change the architecture and you get the year back.