ai-adoption

When one step becomes cheap, the optimal shape of the whole process changes. This lesson covers the six moves that follow, why the review stage almost always needs relocating, what business process reengineering actually taught, and the honest state of the evidence on how often these efforts succeed.

You cannot redesign a process you have not observed, and the documented process is rarely the real one. This lesson covers task-level decomposition, finding where time and waiting actually go, identifying the constraint that governs throughput, and the measurements to take before any AI is introduced.

Mandated adoption produces compliance behaviour and licence-seat metrics that measure nothing. This lesson covers why mandates fail, what resistance is actually telling you, measuring adoption in a way that survives scrutiny, the equity problems that appear inside a team, and how to run the change without losing the people carrying it.

Delegating to AI is a management decision with the same structure as delegating to a person, and one crucial difference. This lesson covers the criteria that make a task a good candidate, the verification tax that determines whether delegation actually saves anything, disclosure norms, and redesigning a workflow rather than bolting AI onto it.

AI changes tasks rather than jobs, which means it redistributes work inside a role instead of removing the role. This lesson covers what that does to a manager: where review load lands, why self-reported productivity is unreliable, the skill-formation problem for junior staff, and which management assumptions stop holding.