Anyone can now have a tool built in five minutes by asking a model, without writing a line of code. That feels like a breakthrough if you build tools for a living. Most people do not. As Benedict Evans puts it, a great lawyer spends the day thinking about the case and the client, not about which software would make that work faster. So the bottleneck sits somewhere else: in seeing that there is something to automate at all, and in working out what the right solution actually is. That second part is rarely obvious. It can take years and several failed attempts before someone finds the right shape for a problem.
Even with the right tool in hand, the work is not done. A process touching fifty to five hundred people across departments and systems stops being an individual decision and becomes a purchasing project that runs for months. Software moves on a sliding scale between improvised (a spreadsheet, an email) and institutionalised (a system with audit, security and ownership), and a task slides toward the institutional end once there is enough revenue or risk attached to justify it. AI leaves that scale intact. It moves where the thresholds sit and which choices you have.
This is why giving everyone ChatGPT never turns into company-wide change on its own. It is the same pattern as putting a PC with a spreadsheet program on every desk in the early eighties: a small group took off with it, the rest used it now and then. The real transformation lives in the slow, concrete work of going through every existing process, one at a time.