AI workflow routing determines where a task or result should go next. A routing decision can use workflow state, role ownership, dependencies, completion evidence, risk and whether human approval is required.
Explicit routing reduces manual coordination and prevents work from disappearing between teams. The system should record why a destination was chosen and preserve a safe exception path when ownership or requirements are ambiguous.
ELI5
Workflow routing decides where a task or result should go next. It can send work to a particular person, AI agent, or software system based on its status, risk, and required expertise.
For example, a normal refund request might go to an automated processor, while an expensive or unusual one goes to a manager for review. Recording why each route was chosen helps prevent work from disappearing or reaching the wrong owner.
What can AI workflow routing send work to?
It can send work to another agent, a human stakeholder, a validation service, a queue or an external engineering tool.
Why should workflow routing be auditable?
An audit trail shows who or what received work, why it was routed there and whether required approvals were respected.
