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Why team-by-team automation speeds up end-to-end processes less than expected
AI makes the steps inside each team faster, but much of a process's elapsed time is spent waiting between teams. That part rarely changes when each team automates its own work.
How to measure whether an AI pilot changed the process
Pilot dashboards usually show activity, such as how many times an agent ran. Whether the process itself became faster, cheaper or shorter can only be seen against a baseline: how the process ran before the pilot.
Why different teams end up building the same AI agent
When AI agents are introduced team by team, each team automates the part of the work it can see. Real work crosses teams, so the same step often gets automated several times in different places. A map of the end-to-end process shows these overlaps, and agent orchestration builds on it.