I've said it a hundred times but I’ll keep saying it: AI adoption and behavior change are slow — and will stay slow — no matter how fast capabilities improve. The stat in the screenshot is worth pondering: nearly a year after the release of "thinking" models, only a tiny fraction of users were using them (until GPT-5's automatic switcher quietly bumped the numbers). This is exactly what we should expect. The dominant narrative is that AI is being adopted at unprecedented speed, but that's based on how many people have tried it, ignoring how they are using it, for how long they use it each day, and how much they are getting out of it. Even lifesaving innovations take a long time to percolate through the population. This is a property of human behavior, not the technology in question, so we shouldn't expect AI to be any different. (For more on this, see AI as Normal Technology.) Some will argue that GPT-5’s automatic switcher proves developers can basically force AI on people quickly. Absolutely not. The model switcher was a problem of OpenAI's own making, so OpenAI was able to solve it. Switching to a thinking model under the hood doesn't require the user to learn new skills or behaviors or change their workflows. It is telling that OpenAI has not been able to similarly integrate Deep Research or Agent Mode, which do require user adaptation — especially the latter, where users have to learn to supervise the model, communicate the task requirements precisely, make complex and potentially risky decisions about security, and find all of this useful enough to want to open up their wallets.