Topic
6 essays in this series
Consulting expertise and consulting labor are distinct economic goods. The pyramid has bundled them together for so long that most firms have stopped noticing the difference. AI is forcing the unbundling.
The time-and-materials model is not just a pricing mechanism. It is a lens that exposes a structural misalignment between how consulting firms spend effort and where clients perceive value.
The market has overweighted prompt engineering, treating the quality of the prompt as the primary determinant of AI output quality. It is not. The prompt is the input specification — output quality is determined by model quality, data quality, context quality, and evaluation rigor.
AI-native is becoming the kind of phrase that means everything and therefore nothing. The organizations that will benefit from AI as a structural competitive advantage are those that have built something more substantive than a portfolio of AI tools sitting on top of traditional processes.
Output and judgment are being treated as if they exist on the same scale — as if producing more output at higher speed is equivalent to making better decisions. They are not the same thing.
AI does not replace work. It replaces specific cognitive tasks within work. Everything that requires judgment about what the output means and what to do with it remains human — and the enterprise response to AI has consistently blurred this distinction.