Most traditional businesses are not anxious about AI’s capability. They are anxious about where to start.
We hear it from a manufacturing CEO whose 45% of revenue ships overseas: "I want to use AI. I don’t even know who in my company to put in charge of it." From a law-firm partner: "We know we should be AI-native. We have no idea what that means for a 30-attorney firm." From a wholesaler: "The category moves so fast every week, I cannot tell which tools to bet on."
The gap is not capability. The gap is fluency. And it has become the bottleneck — not the models, not the tools, not the budgets.
A named AI employee solves the fluency gap by giving the business a concrete first step. Not a strategy deck. Not a transformation roadmap. One workflow, owned end to end, by one named role, in 48 hours.
This sounds modest. It is the opposite. The first workflow does three things at once: it builds the customer’s trust, it teaches their team the shape of what AI can do, and it produces evidence the CEO can show the board. The strategy follows from the artifact. The deck writes itself once the work is running.
The bigger pattern is that AI fluency is becoming a service layer. The same way IT became one in the 1990s and cloud architecture in the 2010s — a thing businesses outsource the first 80% of and bring in-house only when the surface area gets big enough to justify it. Most companies will not become AI-native by hiring a Chief AI Officer. They will become AI-native by hiring (and trusting) a service partner who already is.
That is what we are building toward. Not a product. A practice.
Related Map your first workflow →