Executives operate in ambiguity by default. Individual contributors are measured on execution of deterministic tasks. AI is non-deterministic. That alignment explains the adoption gap better than any survey data.
The piece from Sidebar makes a structural argument: leaders already have mental models for managing unpredictable outputs, so AI feels like a familiar tool. ICs do not have that luxury. Their performance is tied to precision, repeatability, and accountability for specific deliverables. A tool that sometimes gets it right is a liability, not an asset.
The real value of reading the original is the framing itself. If the adoption divide is structural rather than generational or technical, then no amount of training will close it. The fix, if there is one, lives in how IC roles are defined and measured, not in the AI tools themselves.
[READ ORIGINAL →]