Sprinkling AI pixie dust on existing processes yields limited results and can actually reduce productivity. The problem is not the tech stack, but the workflows they are being dropped into.
AI adoption is not failing because the technology is immature. It is failing because organizations are layering it onto processes built for a world where every task required a human to execute it. Until those processes are redesigned, the productivity gains stay local and the transformation stays theoretical.
The organizations pulling ahead have one thing in common. They have treated AI adoption as an operating model redesign exercise, not a technology implementation. That requires a different kind of leadership commitment, a longer timeline than many are comfortable with, and a willingness to ask which roles, workflows, and approval structures still make sense when agents are doing the work.