The Real Cost of AI Adoption Is Friction

I do not think most businesses have an AI problem. They have a friction problem. The tools are powerful enough. The demos are impressive enough. The models are improving fast enough that almost every week there is a new reason to feel behind. But when I talk to operators, the bottleneck is rarely, “Can AI technically do this?” The real bottleneck is usually: Who is going to set it up? Who is going to connect it to our actual tools? Who is going to teach the team how to use it? Who is going to monitor it when it breaks? Who is going to improve it after the first demo stops being exciting? That is the part most AI conversations skip. AI adoption does not fail because business owners are lazy or behind. It fails because the work required to turn a shiny tool into a reliable operating system is much heavier than the sales page admits. The expensive part is not the softwareA lot of AI tools are cheap on paper. Twenty dollars per user. A few cents per thousand tokens. A subscription here,…